How to Prepare for a Case Interview at the Big 4 Firms

If you are applying for a role within management consulting for one of the Big 4; Deloitte, EY, KPMG or PwC, you may be asked to undertake a case interview. A case interview is a type of job interview in which you will be presented with a specific business situation, and asked to answer questions on how you would handle this specific situation. It may be a situation you are likely to encounter in your day to day job or it could be a question unrelated to your role. For example, you may be asked how you would determine the market for a new product launch, and you’d need to be able to ask questions and extract information to be able to determine this. Case interviews can be complex, but it is important to take a deep breath and think things through carefully before you start.

Interviewer Expectations

A case interview may be different to what you’ve done before, and as such, it can be difficult to know exactly what is expected of you from the interviewers. The good news is that there isn’t really a right or wrong answer to the question, the interviewer is looking to see how you reach your solution. This includes the questions you ask and the logic you use. They are looking for you to ask questions which will help you reach a solution and to carefully consider the information you have to reach a final conclusion.

Case Interview Topics

As you are being interviewed for a management consulting role, there are general case interview topics which will usually be used by most organisations. These include:

Business Analysis – the question may be related to your ability to analyse a specific business. This may include understanding its market potential, profitability, growth etc. For instance, you may be asked whether the company should start exporting to a specific country. In this case, you would need to determine the cost, and calculate the profitability to reach a conclusion. This type of question would come down to your ability to ask the right questions, to make calculations and to problem solve.

Estimations – it is not always easy to know the answer in business. For example, you might be asked to estimate the company profits over the next 5 years’. In this case, the interviewer is looking for your ability to extract information, calculate, problem solve and reach a conclusion, without having hard facts on hand. There is no way of knowing exactly what you will be asked during the case interview, but by looking up business case studies, you’ll get a good idea of how to work out the answer. It’s more about structure and problem solving, than anything else. If you can reach a strong conclusion, all the better.

How Do You Succeed in Case Interviews?

Case interviews, especially with one of the Big 4; Deloitte, KPMG, EY or PwC can be challenging, but there are some steps you can take to prepare for these. Practice

Like most things in life, practice makes better and by understanding exactly what is expected of you, you’ll be in a better position to be able to answer the questions. Reading cases and practicing online case study tests will help you get prepared for the interview. If you can get a buddy to help you practice, this will also benefit you. Ask for feedback from a friend, as this will give you a better understanding of what you’re doing right and what you need to work on. If you can’t find a buddy, practice by reading the cases aloud. The key to success with the case interviews is preparation and practice. It is also a good idea to practice calculations too, as this may be part of the process during case interviews. You may need to work out numbers and it’s important to have an understanding of how to work these out, especially when you’re on the spot.

Confirm the question

Make sure you completely understand the question before you start, as if not, you may go down the completely wrong track with your calculations and answer. The interviewers will not be concerned if you need clarification of the question. They would much rather that you communicate with them and ensure you understand everything before you start. This approach is the one they’d expect you to take with a client, so don’t feel like you’ll mess it up by asking for reassurance.

Slow and steady

Candidates often think that they shouldn’t take their time when it comes to interviews, and rushing through them usually ends with making mistakes. There’s no need to rush through the case interview, it is much better if you take your time and carefully consider the question. If you rush, you are more likely to make mistakes. If you go slowly and carefully, you will make better progress with the interview. If you don’t understand anything at any point, just ask for clarification.

Ask questions

The interviewer will start by giving you details about the case. They will then usually ask if you have questions – always say ‘yes’ to this. This is your only chance to obtain as much information as you need to be able to answer with clarity. Make sure you understand what the situation and problem is. If anything is unclear, ask for clarification. If you show you are genuinely interested in the case, you will come across well to the interviewer. Think about it more in real terms than just trying to pass your interview, and ensure your listening skills are as good as your verbal communication skills. The interviewer will be expecting you to ask questions to be able to reach your conclusion. Don’t worry about asking questions, the interviewer will be more concerned if you don’t ask anything.

Engage with the interviewer

Try and think about the case interview as a conversation between two people. Use positive language and try to build rapport with the interviewer. The more you engage with the interviewer, the more likely they will be to give you additional information and maybe even some clues. In the Big 4 organisation; Deloitte, PwC, KPMG and EY, you will be expected to be able to engage well with a wide range of different people. It is important that this comes across during the interview.

Follow a Structure

In order to deal with a case correctly, it is a good idea to follow a structure. The interviewer will be looking for you to follow a logical process and to figure out your answer from this structure, not just ‘winging it’ to get a result. It will also make it much easier for you to reach a conclusion. For example, if you were asked how to determine the market for a product. You might start by defining the characteristics of the product and asking related questions to break down the answer into components. This will make it easier for you to draw a conclusion. If you get to the end and you decide that the answer isn’t right or you need more information, you will still have a basic format to work with, rather than having to start from the beginning again. Even with case interviews for the Big 4; EY, PwC, Deloitte and KMPG, the interviewers are not specifically looking for a ‘right’ answer, they are looking to understand how you reach your conclusion. This is often more important than the answer itself.

What are interviewers looking for?

The case study interview is firstly, about your ability to communicate – both listening, speaking and writing. The interviewer is looking for your ability to engage and extract the right information. Don’t just ask questions for the sake of it, ask questions which will help with problem solving and reaching a conclusion. The interviewer is also looking to see a desire and motivation to problem solve. For example, establishing the most relevant information, connecting facts together with evidence to reach a conclusion. They will want to see that you are questioning yourself and A strong structure will also be important to the interviewer and your ability to make calculations. It is highly likely that your case study will include problem solving and numerical abilities, as ultimately, business success comes down to profit and loss.

The Structure

A good way to create a structure for the case interview is to look at the problem or the question you are trying to answer. This is the first part of the building blocks. An issue tree can be a good way to break your problem down to sub-problems, in order to reach your conclusion. For example, should we sell our product in China? This can be further divided into what the product is, what the market is for the product, what the demographics are in China, what the cost would be etc. The structure is about dividing each issue into further issues until you reach a final conclusion. Then you should make recommendations based on this. It might not just be one straightforward answer, you may have many different recommendations based on your studies.

35 Case Interviews Examples from MBB / Big Four Firms

Studying case interview examples is one of the first steps in preparing for the  management consulting  recruitment process. If you don’t want to spend hours searching the web, this article presents a comprehensive and convenient list for you – with 35 example cases, 16 case books, along with a case video accompanied by detailed feedback on tips and techniques.

A clear understanding of “what is a case interview” is essential for effective use of these examples. I suggest reading our  Case Interview 101  guide, if you haven’t done so.

McKinsey case interview examples

Mckinsey practice cases.

  • Diconsa Case
  • Electro-Light Case
  • GlobaPharm Case
  • National Education Case

What should I know about McKinsey Case interviews?

At McKinsey, case interviews often follow the interviewer-led format , where the interviewer asks you multiple questions for you to answer with short pitches.

How do you nail these cases? Since the questions can be grouped into predictable types, an efficient approach is to master each question type. However, do that after you’ve mastered the case interview fundamentals!

For a detailed guide on interviewer-led cases, check out our article on McKinsey Case Interview .

BCG & Bain case interview examples

Bcg practice cases.

  • BCG – Written Case – Chateau Boomerang

Bain practice cases

  • Bain – Coffee Shop Co.
  • Bain – Fashion Co.
  • Bain – Mock Interview – Associate Consultant
  • Bain – Mock Interview – Consultant

What should I know about BCG & Bain case interviews?

Unlike McKinsey, BCG and Bain case interviews typically follow the candidate-led format – which is the opposite of interviewer-led, with the candidate driving the case progress by actively breaking down problems in their own way.

The key to acing candidate-led cases is to master the case interview fundamental concepts as well as the frameworks.

Some BCG and Bain offices also utilize written case interviews – you have to go through a pile of data slides, select the most relevant ones to answer a set of interviewer questions, then deliver those answers in a presentation.

For a detailed guide on candidate-led cases, check out our article on BCG & Bain Case Interview .

Deloitte case interview examples

Deloitte practice cases.

Undergrad Cases

  • Human Capital – Technology Institute
  • Human Capital – Agency V
  • Strategy – Federal Benefits Provider
  • Strategy – Extreme Athletes
  • Technology – Green Apron
  • Technology – Big Bucks Bank
  • Technology – Top Engine
  • Technology – Finance Agency

Advanced Cases

  • Human Capital – Civil Cargo Bureau
  • Human Capital – Capital Airlines
  • Strategy – Club Co
  • Strategy – Health Agency
  • Technology – Waste Management
  • Technology – Bank of Zurich
  • Technology – Galaxy Fitness

What should I know about Deloitte case interviews?

Case interviews at Deloitte also lean towards the candidate-led format like BCG and Bain.

The Deloitte consultant recruitment process also features group case interviews , which not only test analytical skills but also place a great deal on interpersonal handling.

Accenture case interview examples

Accenture divides its cases into three types with very cool-sounding names.

Sorted in descending order of popularity, they are:

These are similar to candidate-led cases at Bain and BCG. albeit shorter – the key is to develop a suitable framework and ask the right questions to extract data from the interviewer.

These are similar to the market-sizing and guesstimate questions asked in interviewer-led cases – demonstrate your calculations in structured, clear-cut, logical steps and you’ll nail the case.

These cases have you sort through a deluge of data to draw solutions; however, this type of case is rare.

Capital One case interview examples

Capital One is the odd one on this list – it is a bank-holding company. Nonetheless, this being one of the biggest banks in America, it’s interesting to see how its cases differ from the consulting ones.

Having gone through Capital One’s guide to its cases, I can’t help but notice the less-MECE structure of the sample answers. Additionally, there seems to be a greater focus on the numbers.

Nonetheless, having a solid knowledge of the basics of case interviews will not hurt you – if anything, your presentation will be much more in-depth, comprehensive, and understandable!

See Capital One Business Analyst Case Interview for an example case and answers.

Other firms case interview examples

Besides the leading ones, we have some examples from other major consulting firms as well.

  • Oliver Wyman – Wumbleworld
  • Oliver Wyman – Aqualine
  • LEK – Cinema
  • LEK – Market Sizing
  • Kearney – Promotional Planning
  • OC&C – Imported Spirits
  • OC&C – Leisure Clubs

Consulting clubs case books

In addition to official cases, here are a few case books you can use as learning materials.

Do keep in mind: don’t base your study on frameworks and individual case types, but master the fundamentals so you can tackle any kind of case.

  • Wharton Consulting Club Case Book
  • Tuck Consulting Club Case Book
  • MIT Sloan Consulting Club Case Book
  • LBS Consulting Club Case Book
  • Kellogg Consulting Club Case Book
  • INSEAD Consulting Club Case Book
  • Harvard Consulting Club Case Book
  • ESADE Consulting Club Case Book
  • Darden Consulting Club Case Book
  • Berkeley Consulting Club Case Book
  • Notre-Dame Consulting Club Case Book
  • Illinois Consulting Club Case Book
  • Columbia Consulting Club Case Book
  • Duke Consulting Club Case Book
  • Ross Consulting Club Case Book
  • Kearney Case Book

case studies big 4

Case interview example – Case video

The limitation of most official case interview examples is that they are either too short and vague, or in text format, or both.

To solve that problem for you, we’ve extracted a 30-minute-long, feedback-rich case sample from our Case Interview End-to-End Secrets Program .

This is a candidate-led, profitability case on an internet music broadcasting company called Pandora.

In 30 minutes, this candidate demonstrates the exact kind of shortcoming that most candidates suffer during real case interviews – they come in with sharp business senses, then hurt their own chances with inadequate techniques.

Here are seven notable areas where the candidate (and you) can improve:

Thanking Throughout the case, as especially in the opening, he should have shown more appreciation for the time the interviewer spent with him.

Structured opening The candidate’s opening of the case feels unstructured. He could have improved it by not mixing the playback and clarification parts. You can learn to nail the case in a 3-minute start through this video on How to Open Any Case Perfectly .

Explicitness A lot of the candidate’s thought process remains in his head; in a case interview, it’s better to be as explicit as possible – draw your issue tree out and point to it as you speak; state your hypothesis when you move into a branch; when you receive data, acknowledge it out loud.

Avoiding silence The silence in his case performance is too long, including his timeout and various gaps in his speech; either ask for timeout (and keep it as short as possible) or think out loud to fill those gaps.

Proactivity The candidate relies too much on the interviewer (e.g: asking for data when it can easily be calculated); you don’t want to appear lazy before your interviewer, so avoid this.

Avoiding repeating mistakes Making one mistake twice is a big no-no in consulting interviews; one key part of the consulting skill set is the ability to learn, and repeating your mistakes (especially if the interviewer has pointed it out) makes you look like someone who doesn’t learn.

Note-taking Given the mistakes this candidate makes, he’s probably not taking his notes well. I can show you how to get it right if you watch this video on Case Interview Note-Taking .

Nonetheless, there are three good points you can learn from the candidate:

The candidate sums up what he’s covered and announces his upcoming approach at the start and at key points in the case – this is a very good habit that gives you a sense of direction and shows that you’re an organized person.

The candidate performs a “reality check” on whether his actions match the issue tree; in a case interview it’s easy to lose track of what you’re doing, so remember to do this every once in a while.

The candidate prompts the interviewer to give out more data than he asked for; if anything, this actually matches a habit of real consultants, and if you’re lucky, your interviewer may actually give out important pieces you haven’t thought of.

These are only part of the “ninja tips” taught In our Case Interview E2E Secrets Program – besides the math and business intuition for long-term development, a key feature is the instant-result tips and techniques for case interviews.

Once you’ve mastered them, you can nail any case they throw at you!

For more “quality” practice, let’s have a mock case interview with former consultants from McKinsey, BCG, Bain, Oliver Wyman, Strategy& and many other consulting firms. They will help you identify your problem areas and give you actionable feedback, making your preparation much easier and faster.

Hi! This is Kim and welcome to another performance in the Tips & Techniques part of our amazing End-to-end program. You are about to hear a really interesting performance.

There is a common Myth that Profitability cases are easier. Well, for beginners, that’s may make sense, but I would argue that Profitability cases can be really tricky and candidates without good foundation will make about the same level of mistakes regardless of type of cases given.

The profitability case we are about to watch will show that. It’s a very unconventional

Profitability. It started out like a typical one but getting more and more tricky toward the end.

The candidate is fairly good in term of business intuition, but the Tips & Techniques aspect needs a lot of fine tune! Now let’s go ahead and get started! 

It’s actually a little better to playback the case information and ask clarifications. The candidate does not distinguish between the two and do both at a same time. Also, the candidate was asking these clarifications in an unorganized and unstructured fashion. This is not something terrible, but could have been better, especially when this is the very first part of the case, where the crucial first impression is being formed.

My pitch would sound like this:

“That’s a very interesting problem and I am happy to get the chance to solve it. First of all let me tell you my understanding of the case context and key objectives. Then I would like to ask a few clarifying questions regarding a few terminology and concepts. Both of these are to make sure that I will be solving the right problem.

So here is my understanding of the case: The client is ABC. Here are some DEF facts about the situation we just talked about. And the key case question is XYZ.

Does that correctly and adequately summarize the case?”

Once the interviewer confirms, I would move to the clarification part as follows: “Now I would like to ask a few clarification questions. There are three of them: No 1, … No 2, … and No 3, …”

You may see above pitch as obvious but that’s a perfect example of how you should open any cases. Every details matters. We will point out those details in just a second. But before we do that, it’s actually very helpful if you can go back, listen carefully to the above pitch, and try to point out the great components yourselves. Only after that, go back to this point and learn it all together.

Alright, let’s break down the perfect opening.

First of all, you hear me say: “That’s a very interesting problem and I am happy to get a chance to solve it”. This seems trivial but very beneficial in multiple ways:

1. I bought myself a couple of seconds to calm down and get focused. 2. By nature, we as human unconsciously like those who give us compliments. Nothing better than opening the case with a modest compliment to the interviewer.

And (c) I showed my great attitude towards the case, which the interviewer would assume is the same for real future consulting business problems.

You should do that in your interviews too. Say it and accompany it with the best smile you can give. It shows that you are not afraid of any problems. In fact, you love them and you are always ready for them.

Secondly, I did what I refer to as the “map habit”, which is to always say what you are about to do and then do it. Just like somebody in the car showing the drivers the route before cruising on the road. The driver would love it. This is where I said: “Let me tell you my understanding of the case context and key objectives. Then ABC…”.

Third, right at the beginning of the case, I try to be crystal clear and easy to follow. I don’t let the interviewer confused between playing the case vs. asking clarification questions. I distinguish between the two really carefully. This habit probably doesn’t change the outcome of how the case goes that much, but it certainly significantly changes the impression the interviewer has of me.

Fourth, in playing back the case, each person would have a different way to re-phrase. But there are three buckets to always include:

1. Who is the client 2. The facts regarding the client and the situation and (c) The key question and the objective of the case.

Fifth, after playing the case context and objectives, I pause for a second and ALIGN with the interviewer: “Does it correctly and adequately summarize the case?”. This is a habit that every consulting manager loves for young consultants to do. Nobody wants first-year folks to spend weeks of passion and hard-work building an excel model that the team can’t use. This habit is extensively taught at McKinsey, Bain and BCG, so therefore interviewers would love somebody that exhibits this habit often in case interview.

Lastly, when asking clarification questions, you hear me number them very carefully to create the strong impression that I am very organized and structured. I said I have three clarifying questions. Then I number them as I go through each. No.1, No.2, and No.3.

Sometimes, during interviews it’s hard to know exactly how many items you are going to get. One way is to take timeout often to carefully plan your pitch. If this is not possible in certain situations, you may skip telling how many items you have; but you should definitely still number your question: No.1, No.2; and so on. 

Just a moment ago, the candidate actually exhibited a good habit. After going through his clarification questions, the candidate ended by asking the “is there anything else” question. In this case, I actually give out an important piece of data.

Though this is not very common as not every interviewer is that generous in giving out data. But this is a habit management consultants have to have every day when talking to experts, clients, or key stakeholders. The key is to get the most data and insights out of every interview and this is the type of open-ended question every consultant asks several times a day.

To show of this habit in a case interview is very good!

There are three things I would like you to pay attention to:

First, it took the candidate up to 72 seconds to “gather his thoughts”. This is a little too long in a case interview. I intentionally leave the 72 seconds of silence in the recording so you get an idea of how long that is in real situations. But it’s worth-noting here is not only that. While in some very complicated and weird cases, it’s ok to take that long to really think and gather ideas. In this case, the approach as proposed by the candidate is very simple. For this very approach, I think no more than 15 to 20 seconds should be used.

No.2, with that said, I have told I really like the fact that this candidate exhibits the “map” habit. Before going straight to the approach he draws the overall approach first.

No.3. You also see here that the candidate tried to align the approach with me by asking my thoughts on it. As I just said on the previous comment, this is a great habit to have. Not only does it help reduce chance of going into the wrong direction in case interviews, but it also creates a good impression. Consulting interviewers love people doing it often!

Here we see a not-really-bad response that for sure could be much better. The candidate was going into the first branch of the analysis which is Revenue. I would fix this in 3 aspects:

First, even though we just talked about the overall approach, it’s still better to briefly set up the issue tree first then clearly note that you are going into one branch.

Second, this is not a must, but I always try to make my hypothesis as explicitly clear as possible. Here the candidate just implicitly made a hypothesis that the problem is on the revenue side. The best way to show our hypothesis-driven mindset is to explicitly say it.

Third, you hear this a ton of times in our End-to-End program but I am going to repeat it again and again. It is better to show the habit of aligning here too. Don’t just go into revenue, before doing that, give the interviewer a chance to agree or to actually guide you to Cost.

So, summarizing the above insights, my pitch would sound something like this:

“So as we just discussed, a profit problem is either caused by revenue or by cost. Unless you would like to go into cost first, let’s hypothesize that the problem is on revenue side. I would like to look deeper into Revenue. Do we have any data on the revenue?”

And while saying this, you should literally draw an issue tree and point to each as you speak.

There is an interesting case interview tip I want to point out here. Notice how the candidate responds after receiving two data points from me. He went straight into the next question without at least acknowledging the data received and also without briefly analyzing it.

I am glad that the candidate makes this mistakes… well, not glad for him but for the greater audience of this program. I would like to introduce to you the perfect habit of what you should react and do every time you have any piece of data during case interviews. So three things you need to do:

Step 1: Say … that’s an interesting piece of data. This helps the interviewer acknowledge that you have received and understand the data. This also buys you a little time. And furthermore, it’s always a good thing to give out modest compliments to the interviewer.

Step 2: Describe the data, how it looks, is there any special noteworthy trend? In this case, we should point out that revenue actually grew by more than 50%.

Also notice here that I immediately quantified the difference in specific quantitative measurement (in this case, percentage). Saying revenue went up is good, but it’s great to be able to say revenue went up by more than 50%.

Step 3: Link the trend identified back to the original case question and the hypothesis you have. Does it prove, disprove, or open up new investigation to really test the hypothesis? In this case, this data piece actually opened up new investigating areas to test the hypothesis that the bottleneck is within revenue.

My sample pitch for this step 3 would sound like this: “It’s interesting that revenue went up quite a bit. However, to be able to fully reject our hypothesis on the revenue, I would like to compare our revenue to that of the competitors as well.”

Then only at this point, after going through 3 steps above, I ask for the competitors’ revenue like the candidate did.

Notice here that I ended up asking the same question the candidate did. This shows that the candidate does have a good intuition and thought process. It’s just that he did all of these implicitly on his head.

In consulting case interview, it’s always good to do everything as explicitly as possible. Not only is it easier to follow but it helps show your great thought process.

… the rest of the transcript is available in our End To End Case Interview

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11 Big 4 Interview Tips to Pass with Flying Colours

After interviewing for jobs since the age of sixteen, I would like to think I am actually pretty good at interviews by this point. I have worked my way through many roles : a drinks maker, an events promoter, a business analyst, a secondary school Maths teacher, to finally in September 2018, landing myself an external audit graduate position at a Big 4 firm! If this is something you are interested in also achieving, you are definitely in the right place. I am going to share a lot of successful tips with you to pass a Big 4 interview or any interview in fact. Having failed some interviews along the way, I will also share the don’ts too.

Check out my  YouTube video  if you would prefer watching to reading!

Table of Contents

1) nail the logistics, 2) dress to impress, why the company, why the role and role expectations, competency based interviews, scenario/behavioural based interview, 4) big 4 interview – additional preparation, 5) commercial awareness, 6) get comfortable and be yourself, 7) water is your friend, 8) interview notes to hand, 9) mock interviews, 10) other resources to help prepare, 11) final questions for your interviewer, big 4 interview tips summary.

We may as well start with the less exciting area first although it is equally important to passing the interview. In order to pass an interview, you of course need to be able to show up ! If the interview is in person, I would highly recommend planning your route beforehand. You should allow time for any traffic as you definitely do not want to be late. A good idea would be to plan to arrive half an hour early , find a local café and compose yourself before heading in 10-15 minutes in advance. A tricky topic around travel is travel reimbursement . I personally would not ask you hear back from the interview regarding this if you have not been told anything.

If your interview is online , you will not have this stress but you must ensure Zoom or whichever application you need is opened beforehand . I recently sat a case study assessment for a Big 4 secondment opportunity where I had to join the initial briefing on Zoom. I had closed every application on my laptop as I was working in the morning and went to get changed. When I came back, my laptop had stated it needed to be shut down for an update. It must have been the nerves but I thought 5 minutes would have been enough – BIG MISTAKE! I ended up being at least 10 minutes late. Although I had emailed in this time, it was not a good start.

Unfortunately I was not successful and I will be sharing further details about this in the upcoming months. Join my journey to learn from my mistakes. Being late was not a reason for my rejection but it definitely contributed to the feeling of being flustered and overwhelmed during the case study.

This is another obvious one but you should definitely ensure to dress the part. Whether it is the full outfit or the waist up for a virtual interview, look sharp . It apparently takes 7 seconds to make a first impression . You do not want your choice of outfit, hairstyle, make-up or even bad smell to have a negative impact on this. I would advise to dress for the role . If you are going to a Big 4 interview, ideally you should wear business dress. The interview is likely to be with a senior manager or partner and they will be looking for a candidate they would be comfortable putting in front of a client. Bear that in mind when choosing your outfit.

3) Interview Question/Answer Preparation is Key

Through all my years of interviewing, I have found the interview can go one of two ways: a competency based interview or a scenario based interview. However, before I get into these and share more details about my Big 4 interview, I will cover the two important questions you will always need to prepare for, for any interview.

First and foremost, why that specific company. This is usually the opening question in the majority of interviews and I would actually be quite surprised if this was not asked in an interview unless of course, it was an internal role. If I remember correctly, this was asked in my Big 4 interview. You definitely need to prepare an answer to this type of question because this is your chance to really show you have done your research . There are many different areas you can look into as I will outline below.

Here are tips for some key areas you can research or points you can make when answering why that specific company:

There are clearly a lot of different areas you can research and you may end up having a lot of different reasons for why the company. I would usually write my answers down in a bullet point list and try to memorise it beforehand. Sometimes it can feel you are speaking for ages when answering this question but more is better than less, especially where your answers are less generic. Ensure to be concise with each point but definitely get those reasons that are most important to you in first. If you have a long list by the end of it, if you miss a few out you would still have given a very robust answer to this question.

Note : if you really prepare with answers that are tailored to you and that specific firm , you should find it much easier to answer how this Big 4 firm differs to the others. For examples, the awards, culture, news articles, etc. Also, if the route to manager is quicker at one firm than another, mention this.

The second question I would then expect and again be surprised if you did not get asked is why you want to do that specific role . Again, I believe this was asked in my Big 4 interview. This question is one you do really need to nail as it will go a long way in leaving that lasting impression . Here you can show if you actually understand the role you are applying for and get your passion across. I have had an interview for a summer internship at an investment bank where I really did not understand that role at all and it showed. It was safe to say I did not get this internship.

When covering why the role, I think it is very important to know the following :

  • What the top skills are that are required to do well in this role
  • What the day-to-day role will involve (click here to find out about external audit)
  • Whether there are any professional qualifications required as part of the role
  • The outline of the whole graduate scheme and what you expect to happen over the full course of the scheme

If you really understand the above, it will shine through in your interview. However, to answer why the role you would need to put a spin on the above. For example, knowing the top skills does not say why the role. If you can link these skills to your strengths and what you enjoy , you will be off to a great answer. Additionally, if you are really excited about a client-facing role with team work, say it. You need to make the links here to your why. If you want the ACA and want to keep learning, let the interviewer know.

The interviewer is not expecting you to be amazing at the role but instead want to see that you do have a genuine interest .

Tip : When you answer an interview question such as where do you see yourself in 5 years, make sure you understand where being in the role for 5 years will get you.

If I remember correctly, my Big 4 interview, the interviewer had my CV laid out and it was definitely more competency based than scenario. However, I will reveal it was actually more of a conversation getting to know each other and I will share more about this further on. For now, I want to discuss how to go about preparing for a competency based interview.

From the above section, you must know the top skills required to do well in the role. These are likely to be the focus of the competency based questions. For example, in external audit you will need to develop your leadership skills as during your graduate scheme you should progress to be an assistant manager. Therefore, a potential question is “tell me a time you have demonstrated leadership skills”. Other potential questions could be on team work, communication, time management, analytical skills, etc.

The best way I have found to approach these questions are to list all your previous experiences , both academic and non-academic. From this list, then break these down into the different skills you have developed. You should think of specific scenarios and examples you can pinpoint to portraying a specific skill. If you have these examples in your head where you can apply them flexibly or adapt these where needed, you should do well here. A key point though is to make sure not to keep using the same example throughout!

Note: I would like to stress here to make sure not to lie or exaggerate too much in your interview. Any follow up or probing questions could show cracks here.

The type of interview I am referring to here is where the questions are quite hypothetical . For example, “what would you do if…?”. These are trickier to prepare for. The tip I would give here is to think carefully before answering and really think about what the question is asking . You should also think back to the firm’s values . If the scenario is about doing something unethical, if integrity is a core value, you should definitely think about doing the right thing.

In my Big 4 interview not only was it an interview but I also had to prepare a presentation . I do not know if they still do this but I will share the details anyway. I was given the details beforehand for what I needed to prepare this presentation on and then I had to present this at the Big 4 interview. This was extremely daunting as you of course want to do a good job and you do not want to look clueless or unprepared. Speaking to somebody you know who has successfully been through the same process may help and the internet is always helpful.

Definitely take the time to prepare here. You should not let it take away from your interview practice but it should not be left until last minute. Follow the outline you are given and stick to the brief to a T. Make sure your presentation fits with the format of the firm. For example, if the firm is more creative then you too should be more creative in your presentation. However, Big 4 presentations are usually quite formal and professional so this is the style I went for.

My presentation was on Microsoft PowerPoint. Before the Big 4 interview, I had not been told much about how the presentation would run. This can be nerve-wracking as you do not know whether you will be stood up, sat down, using a projector or laptop or what. The other scary part is if the USB does not work or if the email does not send with the presentation attached. I would therefore bring a USB , email it across to yourself AND print it out . In the end it was a 1 on 1 presentation sat down, I think using the print outs.

This is the area of an interview I would always dread . I have never been one to constantly keep on top of the news and know everything that is going on. However, it is important to do your research beforehand as you could definitely be asked what issues the industry is facing. That being said, I do not think I was asked this specifically in my Big 4 interview as I think I covered this as part of the presentation.

If you are applying to external audit for example, I would recommend looking into articles about audit quality and the Big 4 break up.

Like I said, my Big 4 interview was more of a conversation. It was actually a very pleasant experience but I do not think it would have ran as smoothly had I not adapted to the interviewer’s style. I allowed myself to be comfortable and to have a conversation, speaking about where I grew up and finding common ground. Your Big 4 interview may be more formal where it sticks to a specific structure of questions but if not, adapt and just be yourself .

Being yourself is one of the most important tips I can give you. You have already done the hard parts to get to the final Big 4 interview. It may of course feel unnatural to blow your own trumpet but as long as you let your personality shine through , you are likely to do well. Remember, the interviewer is likely looking for someone they can put in front of a client , depending on the role you are applying for. They also want someone who will fit in their current team . I am sure you will tick this box and connect more with the interviewer if you are your natural-self.

You might be wondering what I am even suggesting with this sub-heading. It is actually very simple and a tip I made sure to follow in my Big 4 interview. I have mentioned that you should take the time to think before answering questions. It of course can become quite awkward early on if you stare in silence . You have a few options here:

  • Ask for the question to be repeated to bide time
  • Ask for a moment to think
  • Take a long sip of water before answering

It does depend how hard you think the question is and how long it takes for an answer to come. Sipping water is also helpful whilst you answer as you can take a moment to collect your thoughts and make sure you have not missed anything important. I have found water to help with any awkward pauses.

A tricky area is knowing whether you should keep interview notes with you and if you should ever read off these. For example, this can be very tempting with answering why the firm or the role. However, I would probably avoid reading off notes as nerves can make you over reliant on the notes and could have you reading off the paper. This is not ideal for obvious reasons as well as resulting in less eye contact with the interviewer.

Alternatively, you could have these with you on the side as a comfort blanket . If you choose to do this, I would have a separate set of notes that are very concise and in bullet points. Rather than full sentences, these should be a few key words that would then prompt you to talk about something in more detail. This ensures you cannot rely on the notes entirely during the Big 4 interview.

Mock interviews are very important. I definitely ran through my mock interview questions/answers with my sister before my Big 4 interview. I rehearsed how I would answer why the company or why the role as well as got her to ask potential competency based questions. This is a vital step in passing any interview because you start to realise whether your preparation has sank in and you have memorised it successfully or not. I found that I was sometimes talking for too long and needed to brush up on certain answers before the real Big 4 interview. It also made me ok with not giving the perfect rehearsed answer but one that was more natural and realistic .

Being completely transparent and honest with you, I did actually have one Big 4 interview, with a different firm to my employer of course, that I did fail . In my feedback I was told I was going off on tangents with some of my answers. In hindsight, I thought I did well but perhaps more mock interview practice could have helped here.

I have stated several times in this article to reach out to your network or people on LinkedIn . However, a resource I have not touched on that can definitely help with interview preparation, especially Big 4 interview preparation is The Student Room . Many students who are also in the same position as you are usually on this website. They will discuss their upcoming interviews and sometime even share their questions. You should not expect yours to be the same but preparing for these will give you more confidence you will do well.

Every interview usually ends with the opportunity for you to ask questions to your interviewer. I would definitely avoid going down the route of salary questions but instead, take the opportunity to get to know the interviewer more. My favourite question is asking the interviewer about their experiences and whether they enjoy their role. You could ask if they enjoy working at the firm or even what the most enjoyable part of their job is. People tend to love sharing this sort of information.

You could also take the opportunity to ask something that has come out of the interview. For example, if the interviewer briefly mentioned they travelled abroad during their time at the firm, ask more about this. It shows you really listened and have a genuine interest.

Another route you could go down is asking about their opinion on the future of the role you are applying for. It is up to you how you choose to proceed. I think asking a question is better than not asking anything at all. It is your chance to leave that final great impression.

I have covered a lot here but hopefully there is something you can take away from this article, Big 4 interview or not. I would like to take this moment to congratulate you on getting to the interview and to wish you good luck!

If you enjoyed this article, feel free to share and to even join my journey for more upcoming posts and a few goodies too.

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Ace your EY advisory case interview with this easy technique

by Nkem | Advisory , Interviewing | 3 comments

big 4 advisory interview

Need some help preparing for your EY advisory case interview? We’re here to help! Ernst and Young (EY) was one of the first Big 4 firms to start requiring a case interview as part of the Advisory interview process, following in the footsteps of the famous strategy consulting firms like Bain, Mckinsey, and BCG.

Case interviews have become an increasingly popular way for firms to gauge a candidate’s problem-solving, technical, and intrapersonal capabilities. They are usually longer than your average interview, hovering around the 60-minute mark.

During a case interview, you will receive a business conflict to read, review, and analyze. After some time of brainstorming, you will discuss with your interviewer your suggestions and conclusions. The goal is not to accurately solve every issue presented nor is it to devise an entire business plan on the spot. Rather, you want to demonstrate that you understand the facts and dilemmas of your client, you are capable of developing strategic action plans, and recognize there is room for flexibility and diversity in problem-solving. Keep in mind this case will likely be the first time you lay your eyes on it, so you must be rational with yourself.

Often, you should know you are walking into a case interview- if not, well either you don’t read your emails well or your recruiter isn’t the best.  Anyways, start by reading the case once just to understand the basics – “who, what, when, where, why, & how.”  Then, of course, read it again, but this time identify the problem(s). Circle, highlight, underline, and do something to help you recognize each conflict you come across. Try not to have too many; remember you’re being timed. Five at MOST is a good start.

SWAT away the competition at your EY Advisory case interview

Next and quickly, perform a SWOT analysis. This stands for Strengths, Weaknesses, Opportunities, and Threats. The definition of each is pretty self-explanatory, but if you want more description check out this https://www.mindtools.com/pages/article/newTMC_05.htm .

This will be a great way to open up your discussion later with your interviewer, but for now, use it as a way to organize your thoughts about the company.

Once you have a handle on the issues this is where your beautiful noggin comes in!

Strategize; think of ways to solve the issues.  Here are some thought-provoking questions to help you think of solutions.

Can the company consolidate its product, finances, or operations?

Is it best for the company to seek external or internal assistance?

What are they already doing well (a strength) that they can leverage in this issue?

Are costs the issue or is it a personnel issue?

What type of value does this company have and need to maintain to its consumers?

Does this company have the capacity or should they integrate/merge with another?

Will your solution drive costs up?

Ethics vs Profits-how would you balance this for the company?

When you believe you have developed convincing and practical solutions to your case, alert your interviewer. Try to choose two with two or three conflicts so that you have a detailed plan rather than several short ideas. You can use your SWOT analysis as an opening to start off strong and then dive into your solutions. Make sure your thoughts and suggestions are well-organized; perhaps in order of what is most problematic -this will really demonstrate you have great management and comprehension skills. Approach your discussion in a similar manner that you would with a potential client. Be clear in your recommendations and explain your thought process. Make sure to address possible mishaps in your proposition. It is okay to recognize that your ideas are not bulletproof.

Once you have presented your case, be prepared for questions, and further discussion with your interviewer. They may want to walk through your thought process with you or have you explain an idea further.

Breathe!!  It is over and you have probably impressed your interviewer more than you know. Confidence and patience in yourself are key in this type of interview. Whether you have the perfect answer or not is not going to determine if you get the position, but simply how well you receive information and can form an analysis. For more practice keep up with current cases and journals. You can also find other EY job tips by following the link.

Wow, the above inputs provided me good hints on how to take part in case study discussion

That’s a good one. Thank you.

Thanks for the love, Parvathy!

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The Big 4’s Tax Problem

The S.E.C. is reportedly reviewing conflicts of interest at top accounting firms.

By Andrew Ross Sorkin ,  Vivian Giang ,  Stephen Gandel ,  Lauren Hirsch ,  Ephrat Livni and Jenny Gross

case studies big 4

Too big to audit

Regulators are turning up the heat on the Big 4, the largest accounting firms in the U.S. — Deloitte, PwC, EY and KPMG. Increasingly, their size and the variety of services they offer, like tax consulting, are raising questions about the independence of their audits and landing the firms in hot water, writes The Times’s Jesse Drucker .

The giant advisory firm EY, for instance, has faced criticism for an elaborate arrangement that its tax consultants set up for Perrigo, one of the country’s leading makers of nonprescription drugs. In 2008, Perrigo’s auditors — at the time C.P.A.s from the accounting firm BDO — questioned the arrangement, which would enable Perrigo to save more than $100 million in federal taxes. Perrigo soon replaced the BDO auditors with ones from EY, who blessed the transactions, which federal regulators now claim are shams. Perrigo is fighting the I.R.S. over fines the agency assessed because of the tax maneuver. EY says it stands by the work it did for the drug company.

The Big 4 are behemoths. EY, the world’s third-largest accounting firm, generates an annual revenue of about $40 billion and employs more people than Apple, Exxon and Pfizer combined.

Conflicts of interest among accounting firms aren’t new, but Biden administration regulators are increasing the scrutiny of them. The S.E.C. is reportedly conducting a broad review of conflicts of interest involving the services offered by the Big 4. Senior officials at EY and another big accounting firm, Deloitte , are now discussing plans to split their auditing and consulting arms into separate companies. And this morning, the Senate Finance Committee released its initial findings from a yearlong investigation into how drug companies have utilized subsidiaries in low-tax nations to exploit loopholes in a 2017 corporate tax reform law.

How Perrigo’s tax shelter worked: In 2005, EY devised a plan to help Perrigo, then based in Allegan, Mich., avoid U.S. taxes on its popular anti-heartburn medication, omeprazole . If Perrigo had bought omeprazole from a manufacturer and then sold the pills to customers in the U.S., its profits would have been taxed there. Instead, EY advised Perrigo to set up a subsidiary in Israel, with no employees and no offices, to buy the omeprazole. The shell company then sold the pills to Perrigo in the U.S. at a profit. That meant that Perrigo’s income on the pills largely remained in Israel rather than in the U.S., out of reach of the I.R.S. And because of the vagaries of Israeli tax law, the profits weren’t taxed in Israel, either.

The I.R.S. eventually questioned the transactions and required Perrigo to pay $163 million in back taxes. In a related case, Justice Department lawyers representing the I.R.S. accused EY of enabling a “shell game” and a “flagrant tax scheme gone awry.” The fight went to a federal trial last year. The judge hasn’t announced a verdict yet.

HERE’S WHAT’S HAPPENING

Boris Johnson says he will resign as Conservative Party leader, but he plans to stay on as prime minister until a successor is in place. The development comes after a dizzying 48 hours in British politics that involved a rebellion of Johnson’s cabinet and a wave of government resignations in response to his handling of the party’s latest scandal.

The directors of the F.B.I. and MI5 issue a joint warning about the threats of Chinese spying. In a rare joint appearance, Christopher Wray of the F.B.I. and Ken McCallum of MI5 told business leaders yesterday to be aware of Chinese espionage aimed at stealing intellectual property of Western technology companies . Wray warned that the Chinese government was “set on using every tool at their disposal to do it.”

For the first time in three years, start-up funding is dropping. Investments in U.S. tech start-ups plunged by 23 percent over the past three months, to $62.3 billion, the steepest decline since 2019 , according to figures released yesterday by PitchBook, which tracks young companies. Over the past decade, quarterly funding to high growth start-ups has fallen just seven times.

The Dallas Cowboys face backlash after announcing a partnership with a gun-themed coffee company. The team announced the marketing agreement with Black Rifle Coffee the day after a deadly shooting at a Fourth of July parade in Highland Park, Ill. On social media, people criticized the team for the timing of the announcement.

Shell sees its refining profits nearly triple, adding $1 billion to its bottom line. In a trading update, the company forecast that the profit margin it earns by refining crude oil into products like gasoline and diesel rose in the second quarter to $28.04 a barrel, up from $10.23 a barrel in the January to March period. The prices of oil products are being driven up by a lack of refining capacity.

The incredible consolidating crypto industry

It may be peak summer, but the cryptocurrency sector is feeling the chill of winter, as major firms like the lender Celsius freeze withdrawals , and bankruptcies ripple through the hedge fund Three Arrows Capital and the broker Voyager Digital.

In an attempt to salvage what remains , big players like Sam Bankman-Fried, the founder of the FTX exchange, are swooping in with emergency infusions of capital for companies like the crypto lender BlockFi.

It looks as though a major consolidation is in the works, so DealBook asked veterans of previous tech bubbles what we’ll see in the coming months. They expect more pain — as well as new government policies — as the sector shakes out.

“There is a great parsing taking place,” said Chris Lehane, the chief strategy officer of the crypto venture firm Haun Ventures and a former Airbnb executive. The crash will separate the short-termers from the more committed players, he said, and distinguish between “builders and bandwagoners.” That urgency, he said, could accelerate much-needed policy solutions: “Regulations are part of the parsing.”

A few big players could significantly expand their influence, said Jeremy Allaire, a founder and the C.E.O. of the stablecoin issuer Circle, who took two companies public before blockchain was a big thing. Allaire said he expected his company as well as the exchanges Binance, Coinbase and FTX to thrive and advance the development of new rules for the industry.

Allaire and Lehane see shades of crises past in today’s markets but are dubious that crypto will end up as centralized as the internet did after the dot-com crash — as long as policy is done right. Still, there are already signs that there might be giants emerging.

What’s up for grabs? Tomorrow’s customers, among other things. FTX’s Bankman-Fried, in the recent industry cleanup , says he steps in where businesses have customers to protect, which also helps maintain market integrity. In recent credit agreements with Voyager Digital and BlockFi, his businesses subordinated their debt to that of customers’ — a brand-building gesture that arguably helps advance his ambitions to win fans and dominate crypto regardless of whether the underlying companies survive.

“Private equity owns a piece of the waterfront now. Remote ownership is always going to be driven by dollars and cents. Without any loyalty to the place, business decisions can become cold and harsh.”

— Jon Mitchell, the mayor of New Bedford, Mass., tells ProPublica about how a foreign private equity firm has become a dominant force in the city’s fishing port, passing on costs to local fishermen .

The strange case of Ben & Jerry’s v. Unilever

Ben & Jerry’s, in an unusual case, is suing its owner, the consumer products giant Unilever. The lawsuit seeks to stop Unilever from selling the distribution rights and decisions of the ice cream brand in Israel to a local licensee. Last year, Ben Cohen and Jerry Greenfield, the founders of the company famous for its stances on hot-button issues , said they would end sales in Israeli-occupied territories . The licensee is expected to continue selling Ben & Jerry’s in those areas.

The rift between Ben & Jerry’s and Unilever dates to Unilever’s acquisition of the ice cream brand in 2000. As part of that deal, Unilever agreed to let Ben & Jerry’s independent board, of which Unilever appoints only two out of the 11 seats, continue to oversee the brand and its image.

The unusual arrangement gave the founders continued control despite the sale of their company. Typically, shareholders vote in elections for the board of directors. But this contract is between Unilever and Conopco, which is officially the only shareholder of Ben & Jerry’s. Conopco is obliged to vote for the founders’ board picks and their successors, who are also named by Ben & Jerry’s board. Unilever is able to choose the brand’s C.E.O., which is something a board typically does, but even that person is supposed to defer to Ben & Jerry’s independent board when it comes to maintaining “the social responsibility aspects of the company,” Ann Lipton, a professor in business law at Tulane University Law School who has studied the acquisition, told DealBook.

But Unilever appears to have a possible out , Lipton said. The contract itself might not be enforceable in court. Traditionally, a contract is between two parties. In this case, the agreement could have been between Unilever and Ben & Jerry’s founders, but it’s not, Lipton said.

“That’s like having a contract with yourself,” Lipton told DealBook. “If you’re the only shareholder of the company, the idea that the company can make a contract with you is sort of unheard-of. It’s very strange.” Lipton said she hadn’t heard of a similar case, adding, “it’s a case study in business law class.”

THE SPEED READ

The pharmaceutical giant Merck is reportedly in advanced talks to buy Seagen , a cancer biotech company. (WSJ)

An investment group based in Britain, backed by Russian oligarchs, is suing Pamplona Capital Management , the private equity firm that manages its money.

GameStop’s board approves a stock split , which makes shares more affordable for individual investors. (Reuters)

These are some of the potential candidates to take over as prime minister in Britain with Boris Johnson poised to eventually step down.

Two top former F.B.I. officials, both of whom Donald Trump wanted prosecuted, have faced tax audits . (NYT)

Crypto A.T.M.s are confounding rule makers concerned about oversight and illicit use. (Politico)

“Big Shot,” the Chinese tycoon, whose wrong-way bets on nickel crashed the market this year, walks away with most of his billions . (Bloomberg)

Best of the rest

Vanguard will pay about $6 million to investors in Massachusetts hit with unexpected tax bills. (WSJ)

Bill Ackman donated $18,000 to the toddler whose parents were killed in the Highland Park shooting . (Insider)

Rajeev Misra is stepping back from his role at SoftBank . (Bloomberg)

Peloton is reportedly offering new incentives to employees to bolster morale . (CNBC)

We’d like your feedback! Please email thoughts and suggestions to [email protected] .

Andrew Ross Sorkin is a columnist and the founder and editor at large of DealBook. He is a co-anchor of CNBC’s "Squawk Box" and the author of “Too Big to Fail.” He is also a co-creator of the Showtime drama series "Billions." More about Andrew Ross Sorkin

Vivian Giang joined The Times as a senior staff editor in 2019. Prior to The Times, she was a freelance writer and editor covering the workplace. More about Vivian Giang

Stephen Gandel is a news editor for DealBook. He was previously a senior reporter for CBS News, and a columnist at Bloomberg. He has covered Wall Street and financial firms for most of his career. More about Stephen Gandel

Lauren Hirsch joined the New York Times from CNBC in 2020, covering business, policy and mergers and acquisitions.  Ms. Hirsch studied comparative literature at Cornell University and has an M.B.A. from the Tuck School of Business at Dartmouth. More about Lauren Hirsch

Ephrat Livni reports from Washington on the intersection of business and policy for DealBook. Previously, she was a senior reporter at Quartz, covering law and politics, and has practiced law in the public and private sectors.   More about Ephrat Livni

Jenny Gross is a general assignment reporter. Before joining The Times, she covered British politics for the The Wall Street Journal. More about Jenny Gross

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AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY

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Daniel Faggella is Head of Research at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and leading enterprises, Daniel is a globally sought-after expert on the competitive strategy implications of AI for business and government leaders.

AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY

Deloitte, EY, PricewaterhouseCoopers (PwC) and KPMG are among the largest service providers in the accounting industry— collectively referred to as the Big Four. Many of the financial and consulting services offered by these firms – such as advising on investment decisions – involve finding patterns in very large sets of data. This data is often beyond the understanding of a single person (or team of persons) and is often “noisy” and without a set format.

The Big Four all seem to have artificial intelligence initiatives – and the goal of this article here is to compare and contrast their AI-related efforts (and purported results). A few of the Big Four have invested heavily in innovation labs and claim to embrace a new era of automation and augmentation.

In the article below we aim to answer the following three questions:

  • What are the different AI technologies the Big Four are implementing and how?
  • Which services are most likely to be automated first?
  • What are the similarities and differences in the AI initiatives and strategy for each of the Big Four?

We’ll explore the AI investments and initiatives of these companies one-by-one, starting with Deloitte.

case studies big 4

It is one of the biggest accounting brands under which lie several professionals and firms that offer auditing, strategy consulting and tax preparation related services.

As with most large consulting firms, Deloitte vies for market share and press through thought leadership – and like the other Big Four – it has increasingly focused it’s white papers and research on the topic of artificial intelligence. A recent Deloitte article  breaks down AI technologies into the following discreet categories:

  • Product: AI technology embedded into the product or service itself to provide all the associated end-customer benefits.
  • Process: AI technology to streamline daily workflow and operations to automate and increase day-to-day productivity. Automation can happen in two forms: by either reducing manpower directly or augmenting a worker’s ability to perform a task better/faster.
  • Insight: AI is used to make informed and strategic decisions to provide targeted advice to a company to new or existing businesses.

Based on our assessment, most of Deloitte’s own AI-related initiatives seem to fall into the categories of Process and Insight, as we’ll see below.

A concrete example of an AI-enabled process is the document-review platform developed by Deloitte US innovation that went live in 2014. Deloitte claims that this platform has automated the process of reviewing and extracting all the relevant information from contracts, and reducing meticulous, laborious human efforts.

The company claims that this technology has helped reduce the time spent on reviewing legal contract documents, invoices, financial statements and board meeting minutes by up to 50 percent or more .

Deloitte has recently partnered with IBM Watson. The Deloitte touts the partnership as a way to provide end users with cognitive-technology-enhanced solutions for their businesses. Following are some business use-cases as a result of this partnership:

  • LeasePoint – It is powered by IBM TRIRIGA and utilizes Deloittes knowledge in leasing industry to teach the AI-enabled system to develop an end-to-end leasing portfolio
  • Visual inspection of assets – Using IBM’s Maximo technology Deloitte claims to be improving asset inspection on wind farms. Learn more in this video .

Deloitte Catalyst – another recent AI initiative from the global consulting giant – is a network of startups, that are working together to translate AI technologies into practical business solutions for client firms.

Deloitte offers Catalyst companies funding, and access to Deloitte’s client base in order to partner and flesh out their business applications. Most AI firms are still figuring out exactly how to drive business value with their technology, and Deloitte hopes to forge partnerships with these cutting-edge firms to help bring the latest AI innovations to their clients. The video below explains the initiative (starting around 55 seconds):

Ayasdi, Narrative Science, and Kira are claimed to be among the businesses partnering with Deloitte in their Catalyst program.

“Technology like AI can help make these processes more efficient, accurate and comprehensive, helping us get better insights to clients sooner, and empowering our professionals to deliver high-value services to our clients”. – Craig Muraskin, Managing Director, Deloitte U.S. Innovation Group

Formerly known as Ernst & Young, EY is one of the largest professional service providing firms in the world. It operates as a network of firms which function independently in different countries, collectively offering assurance, audit, tax, consulting and advisory services to companies.

The company has recently applied AI to the analysis of lease contracts. The company claims that the use of AI has made it easier to capture relevant information from contracts such as lease commencement date, amount to be paid, and renewal or termination options.

According to an article in Accounting Today, EY is working to automate the auditing process. They claim that this reduces the administrative time spent on reviewing audit documents and gives employees more time to participate in the judgment and analytical part of the process. These applications appear to be in pilot phase (which is to be expected).

as sifting through the auditing or lease documents can be extremely time consuming. According to EY Global Assurance Innovation Leader Jeanne Boillet in a June 2017 report :

“These pilots show that AI tools would make it possible to review about 70%-80% of a simple lease’s contents electronically, leaving the remainder to be considered by a human. With more complex leases (in real estate, for instance), that figure would be more like 40%, but as the tools improve, and the machines learn, it is likely that more complex contracts and data can be read, managed and analyzed.”

Another area where EY has applied AI technology is the automation of routine tasks, such as auditing (which we covered in greater depth in our full article on AI in insurance ), by using it’s own proprietary Robotic Process Automation (RPA) system. EY claims that this technology, known as  , helps the firm deliver more accurate, efficient audits for its clients.

EY Australia has already adopted this digital auditing technology, claiming that 50% of its bank audit confirmations were lodged using the AI-enabled system. This AI-enabled system can accept and confirm audit requests, process and provide the auditors with the relevant documentation for final analysis and judgment.

EY has also launched an AI proof-of-concept, using computer vision to enable airborne drones to monitor inventory during the auditing process. For example, this drone can count the number of vehicles in a production plant under audit, and communicate this data directly into the EY Canvas – the global audit digital platform.

According to EY, use of drones allows more data to be captured in the process of auditing. It also allows auditors to focus on risk areas rather than taking stock of inventory manually. This drone initiative seems to be in research and development mode at the time being and doesn’t seem to be a service offered broadly to EY’s client base.

EY Drone press release

While overtly embracing the developments in AI, EY is also aware of the threat AI poses to white-collar work, and they appear to be addressing automation seriously in their thought leadership. EY’s recent report on the future of work highlights some of the societal and regulatory concerns of job automation in the decade ahead.

EY job automation

Predictably, much of EY’s thought leadership touts the benefits of augmentation instead of automation. EY Global Assurance Innovation Leader Jeanne Boillet says that Artificial Intelligence “has the potential to transform audit, but it will never replace the auditor”.

We find the word “never” to be downright ridiculous, but we cannot blame EY leadership from having to tout this opinion, and there is no reason to blame Mrs. Boillet for being so black-and-white about the matter, anyone in her shoes would say the same thing.

This belief in an “augmented”, not an “automated” future is a common theme among large, people-heavy legacy businesses. Many would argue that businesses of this kind (chock full of knowledge workers working in spreadsheets) are among the biggest “low-hanging fruit” for automation, and it behooves older people-heavy businesses to dispel disturbing thoughts about massive layoffs.

By no means are we suggesting that the Big Four are inherently doomed to perish by nimbler, less human-laden competitors. Rather, we want to address the fact that these firms can be expected to have only one opinion on this matter.

The impact on employee morale and shareholder value would likely be tragic if EY’s leadership (or the leadership of Accenture, Deloitte, or any other large consulting firm) were to state openly that many of their current jobs may be fully automated, and that some of these jobs would not be replaced. Hence, large firms of this kind are only permitted to give one opinion, an inherently self-serving one, one with a commitment to stave off risk and ensure it’s own survival.

We don’t consider this immoral, it’s the same kind of self-preservation we’d see in any other sector or industry. It may not be blameworthy, but it is our job here at TechEmergence to make it known that these opinions should not be taken at face value.

Whenever a company has no choice but to tout a single perspective, we’re likely to lay those facts outright so that business readers (like yourself) can make more informed decisions. We should expect to see large, people-heavy legacy companies

(For more insight into the kinds of jobs that might be first – or last – to automate, read or listen to our previous interviews with Martin Ford , Kevin LaGrandeur , and Marshall Brain – all of which are focused on the impact of automation on the job market.)

The second largest professional services firm by revenue, PwC, claims to have begun adopting AI as well. The International Accounting Bulletin awarded the ‘Audit Innovation of the year’ for PwC’s technology GL.ai in October 2017. GL.ai was developed in collaboration with H2O.ai, a Silicon Valley company that developed an AI-enabled system capable of analyzing documents and preparing reports.

Using AI approaches like reinforcement learning, PwC claims that GL.ai learns and becomes more capable with every audit (a common capability for ML applications). GL.ai has already been trained on audit data from Canada, Germany, Sweden and the UK. We were unable to find robust case studies of the technology in our analysis, and – like most of the AI applications at Big Four firms at this time – the technology seems to be in development.

They claim to have made a significant investment in Natural Language Processing (NLP)- an AI-enable technology for this purpose. NLP makes sense of complex lease agreements, revenue contracts, and board meeting minutes to form meaningful insights for clients.

Anand Rao – Global AI lead at PwC – told TechEmergence about another PwC AI use-case in the automotive industry:

“Using ‘digital twin’ technology and ‘future power’ we have helped large auto manufacturers visualize and navigate over 200,000 go-to-market scenarios to fine-tune their strategy and launch a new multi-billion dollar business in ridesharing and autonomous/electric vehicles. This particular application has won the Best Enterprise Award recently and is the wave of next generation of AI on ‘Gamifying Strategy’ – it takes the methods used to create AlphaGo and other game playing programs to the Boardrooms and Strategy Groups. We have done this at more than half-a-dozen clients”.

Like the other Big Four firms, PwC is actively involved in publishing thought leadership (articles, white papers, and more) on the implications of artificial intelligence. A recent PwC analysis of the financial services sector identifies a number of automation and augmentation concerns related to AI – and advice from PwC on how firms might adapt to AI in the future.

PwC Fintech AI

PwC’s “ AI: Sizing the prize ” report estimates the percent increase in GDP to be attributed to AI in various economic regions (see below). The image below is only a small snapshot, because of the complexity of the topic (and the inherent challenges in predicting the future), we advise the reader to assess multiple sources and develop their own conclusions.

PwC economic impact of AI

“Artificial intelligence can help people make faster, better, and cheaper decisions. But you have to be willing to collaborate with the machine, and not just treat it as either a servant or an overlord”. – Anand Rao, US Analytics Group Innovation Leader

KPMG has built its own portfolio of AI tools called KPMG Ignite. The KPMG Ignite offering is designed to enhance business decisions and process on a digital platform.

Key features of KPMG Ignite include AI tools (a few examples of which are listed below), AI integrators to make these tools compatible with existing IT infrastructure, guidance for client firms and testing, prototype development, and innovation on emerging AI applications.

KPMG is also using AI to analyze and extract information from leasing or investment agreements. Following are some of the business process where KPMG claims to have applied AI-enabled technology-

  • Call Center Analytics Engine- U tilizes NLP to design a model to predict future events and even convert customer calls to unstructured text, which is then streamlined to identify keywords, customer sentiment and predict future trends.
  • AI Anomalous Event Predicting Tool- Uses AI techniques to develop a model to predict future business events.
  • Document Compliance Assessment Engine- Uses AI to read a documentation- contract, leasing and investment agreement- in its entirety and yield relevant information.

(Learn more about Business implications of AI from KPMG here )

KPMG signed a “Participation Agreement” with IBM in June 2016 – apparently with the intention of using IBM Watson to automate audit-related processes. It isn’t clear if this “Participation Agreement” involved paying IBM, or if both firms are looking to prove out a use-case together in a kind of barter. Little seems to be available about the present progress of said agreement.

In a 2016 press release , KPMG’s John Kelly (Senior Vice-President, Cognitive Solutions and IBM Research) states:

“Auditing and similar knowledge services are increasingly challenged with tackling immense volumes of unstructured data. Cognitive technologies such as Watson can transform how this data is understood and how critical decisions are made. By applying Watson, KPMG is taking a forward-looking approach to extending its expertise, helping professionals and clients gain new insights from critical enterprise information”

As we might expect, KPMG has joined the thought leadership game around artificial intelligence – with the intent of informing their clients and appearing ahead of the curve. Like Deloitte, they’ve created a number of layperson-friendly AI explainer videos to explain AI’s potential impact on their work:

KPMG’s “ ethical compass for automation ” highlights some of the societal concerns that they consider to be important in the years ahead. KPMG’s Automation Practice Lead, Todd Loar, explains the fundamental findings of their report in the 5-minute presentation below:

On the Game of Thought Leadership for Consulting Companies

As analysts in the AI industry, we’re tasked with sorting out truth from hype.

With the popularity of AI (and the growing sentiment of its inevitability in effecting all business sectors), it often behooves companies to seem ahead of the AI curve.

In the world of startups, companies increasingly see their competitors use “artificial intelligence” in pitch decks and on their “about” page – and the pressure mounts to do the same (even if they have no AI skills or talent, and even if the product is in no way predicated on artificial intelligence).

In the world of consulting firms, the same phenomenon occurs. Businesses must “keep up with the Joneses” in the perception game of AI competence, or else they’ll lose business to someone who puts up a better front. As in the startup world, this leads to a vicious cycle of mutual one-upmanship without the prowess to back up the claims.

For some reason I find that business readers often know intuitively that a startup’s pitch deck is self-serving, but they’re often unable to apply that same “taking it with a grain of salt” mentality to white papers and reports, which – like pitch decks – serve the goal of filling a company’s bank accounts, not of portraying truth for its own sake.

This disclaimer is important:

Thought leadership is perception management , not objective analysis .

This isn’t to say that we don’t believe that the Big Four are using AI. These companies have massive revenues and thousands of talented people – and based on our assessment, all four of the Big Four claim to have integrated AI into some of their service offerings, and we’d suspect that this is, in fact, the case.

Rather we imply they have no choice but to say that they are on the cutting edge of AI (or they risk losing business to their better-marketed competitors). This isn’t blameworthy, it’s business – and we aren’t here to point fingers, but to lay the situation out as it is. Time will tell which of these companies is leveraging the technology most fruitfully, and we imagine that there will be a rather intense competition among these top firms to improve their service quality and profit margins through automation.

Indeed part of our job here at TechEmergence is to do the “digging” ourselves and aim to get behind the bluster of press releases, but we’d like to remind our readers to think like an analyst as they consume information that might affect their strategy and procurement.

Concluding Thoughts on AI in the Accounting Big Four

In the sections above, we reviewed how AI is being used by all the Big Four. Based on our research on these companies, two common trends seem clear:

First, they seem to be investing in AI technologies for accounting services. AI is being integrated into the core of the business and its use is showing a gradual increase.

Second, the Four also purport to see AI as a critical factor to give them an edge over others and are in some sense competing with each other to gain AI supremacy.

The use of AI holds many promises for the future of these consulting giants. It may take away the pain of flipping through hundreds of pages for hours and making reports. A lot of data collected during auditing and tax preparation is unstructured and prone to human error. AI-enabled technology, trained on this unstructured data is increasingly capable of recognizing the errors and streamlining parts of the process.

Next in line for augmentation and automation are advisory services. Using consulting and advisory data, firms are now training AI networks to learn how to interact with client firms looking for business solutions.

The decision to relying on AI solutions requires administrative streamlining and strategic planning on many levels. The firms have worked hard to define these strategies to implement and integrate AI technologies in the workplace. For example, Deloitte aims to create process maps to keep track of the organization’s core business processes.

Our analysis of machine learning in the finance sector indicates that this industry is among the most likely to adopt more white-collar automation in the years ahead – a trend we see clearly in the analysis of the Big Four.

This will help identify business processes where AI might have the most impact. PwC, advises choosing areas that are operational or explanatory in nature and explore AI solutions to these problems before others (source). These strategies can help to facilitate a judicial use of budget, resources, and planning that goes into the use of AI in a business.

Given the impact that AI is poised to make, there has to be a discussion about the extent to which we rely solely on machine-based intelligence and decisions. Every industry embracing AI for a business solution is concerned with the impact that this technology can have on humans in the workplace. For the Big Four, this is reason for greater concern, as they operate in a people-centric business – and one that some experts would presume to be ripe for massive disruption through automation.

Our analysis reveals that the Big Four are investigating the concerns of workforce automation – though most all of their published thought leadership paints an optimistic future of augmentation, rather than one of automation. Time will tell when it comes to the effects of AI on the knowledge workers within the Big Four. My fingers are crossed that their industry – as with many others – have insight and ability to adopt. They’re certainly working on it.

Header image credit: b4f.eu

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case studies big 4

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Big Four Case Interviews

can you give me some insights on what to expect in big four case interviews? Are they similar to the normal MBB interviews? Are there differences between first, second and third-round interviews? I would be happy to gain some insights as I just applied.

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Hi Anonymous,

if you are referring to the strategy branch of big 4 (Monitor Deloitte, EY-Parthenon, S&) – cases are quite similar. There are differences between different companies and geographies though, thus would be helpful if you could disclose it for specific advice. I helped several people for Monitor, Parthenon and Strategy& in different geographies, please feel free to PM me for more info if interesting.

The structure of the final round is the same as the first one (fit + case+ your questions); however, there is far more emphasis on communication and fit.

Specifically, the main difference you will find in a final round with partners is that at that stage they:

  • spend more time on fit questions and your alignment with the company
  • check more closely your communication (eg how you react to challenging questions)
  • may not have a “proper” structured case to present – during some of my finals I had one interview which was made by two market sizing questions and a brainteaser, without any business case. That's because at the final they know you can structure and crack a case (you passed 1 or 2 rounds already) and are more interested in your logic, personality and fit with the company

So in order to prepare I would concentrate on:

  • Review in details your fit stories – they will matter more than in the first round. In some finals I had almost exclusively behavioral questions
  • Work on your communication (reaction under pressure, how to gain time when you do not have a structure ready, connect with the interviewer, etc). This is something you can test almost exclusively in p2p mocks with peers/experts.
  • Prepare on cases as you did for the first round. More market sizing practice could be useful to think outside the box if you get unusual questions.

Best, Francesco

If you are applying to the consulting team as a generalist, then the cases should be very much similar to what you'd prepare for MBB or other tier 2 firms. If you are applying to a specific team/role as experience hire, the fundatmental case solving remains the same, but the interviews might be more focused on the specific industry/function. E.g. if you are applying to the deal advisory team in Big 4, then expect your cases might be more centered around M&A, Investment decision, etc.

Hope it helps,

It really depends on who you are interviewing with.

If the interviewer is MBB alum, the interview will be very similar to MBB ones

If the interviewer is non-MBB:

  • No clear guidelines for cases, so the case depends on the interviewer
  • 60% chance that it will be marketsizing
  • 40% chance - profitability and general frameworks
  • Interviewers are less demanding than at Big3. unless you meet an ex-big3 consultant as an interviewer
  • For fit I would prepare: Story about yourself; Why consulting; Why Accenture; Leadership; Team work; Your questions to the interviewer

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Learn the basics of a real consulting case interview and repeatedly train the skills you need to ace your real case interview at MBB or the Big Four.

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case studies big 4

Big 4 Accounting Firm

Discover how the firm was able to significantly reduce real estate costs by comparing reservations to actual usage to determine true space utilization rates.

The Company

One of the 10 largest private companies in the United States, with branches in more than 100 countries, this Big 4 accounting firm has 4,500 employees at their New York City headquarters. The firm has large real estate investments in most of the world’s most expensive metropolitan areas.

The Challenge

The firm needed to know how it was using 30 floors at their New York City headquarters. The firm suspected that space was often forgotten, abandoned, or reserved as a contingency plan.

The firm used software that allowed the hundreds of employees visiting headquarters every day to book temporary office space for hoteling. However, the software provided no visibility into whether the booked space was used as planned ― or at all. In general, the firm lacked critical information about their actual space utilization.

The Solution

After selecting and implementing EMS Software, the firm began capturing actual office attendance. Using the check-in and reporting capabilities in EMS, the firm was able to compare bookings to actual use to determine true utilization rates.

The Results

The results revealed that only 49% of assigned offices were being used, while transient employees used only 67% of the hoteling space — leaving 1,665 workspaces vacant daily.

With this insight, the firm was able to reduce their real estate costs:

  • The firm vacated 6 floors and sublet 3
  • The firm realized a savings of $85 million over 5 years
  • Real estate moved from the firm’s second-largest expense to the third

With 695 offices around the world, the firm continues to drive efficient use of their 21 million square feet of space. By expanding their use of EMS, the firm expects to save an additional $97 million over the next five years — translating to about $36 million in annual real estate savings.

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Hertz CEO Kathryn Marinello with CFO Jamere Jackson and other members of the executive team in 2017

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

  • Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
  • Fifty four percent of raw case users came from outside the U.S..
  • The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
  • Twenty-six of the cases in the list are raw cases.
  • A third of the cases feature a woman protagonist.
  • Orders for Yale SOM case studies increased by almost 50% compared to 2020.
  • The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

Supplementing a Big 4 Accounting Firm’s Internal Acquisition Efforts

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Business Case

A big 4 client had recently won several significant new contracts, increasing the number of senior consultants required for additional projects in an already busy year. The speed with which the client had to find qualified people and the large volume needed meant the internal recruiting group would have to be supplemented by outside recruiters.

Our Solution

LHH Recruitment Solutions quickly assembled a specialized recruitment team that consisted of former Big 4 CPAs. By encouraging the client to see the value – in every sense – of allowing the seasonal consultants to work remotely, LHH Recruitment Solutions was able to use its custom recruiting technique to tap into its proprietary database of 4+ million candidates and its Big 4 network. LHH Recruitment Solutions was able to fill 90%+ of the client’s needs on a remote basis, meaning we could save them money and give them access to the best available talent.

The consultants we placed with this Big 4 Firm have enabled it to provide financial consulting services to more than 100 of its own clients. This has meant new revenue streams and professional relationships for the Firm. Our success with this assignment has led to introductions to other departments within the client organization, including Legal and IT. Making use of the vast LHH Recruitment Solutions ecosystem of specialties and service offerings has resulted in cost efficiencies, simplified procurement, and speed to hire for our client.

How Can We Help You?

In the last 30 years, we’ve partnered with more than 5,000 finance & accounting clients and worked with more than 300,000 highly skilled candidates, all vetted and ready to make an impact. We are ready to help you, too. Contact an LHH professional staffing expert today .

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Working with one of The Big 4

The well-recognised professional services firm have an enviable and established employer brand. Their robust application process promoting applicant interaction in an immersive experience.

However, the emerging apprenticeship market and the need to identify and address a fairly specific school-leaver audience left the company facing several challenges. They needed to identify a niche STEM student school-leaver profile to build brand and drive applications, while The Student Room were tasked with a fairly challenging budget.

Our Big 4 partner company recognised our ability to deliver on audience, scale and relevance, putting us on the media schedule alongside ‘conventional’ recruitment media and job boards.

However, a large and unrefined audience doesn’t deliver conversions – we needed to work some magic with our technology to identify the most responsive audience.

Our users’ onsite behaviour allows our Data Management Platform to learn and infer their profile. Every time they engage with content, forums or learning tools we learn something about who they are, what they want and if they are likely to respond to your brand. Through identifying level of study, interest in job opportunities and subject interests we are in a position to identify and overlay key receptive audiences and deliver on client objectives.

“The Student Room’s campaign has driven 85 applications as a result of users clicking on our ads. This has, so far, led to five candidates accepting roles at the company, with a further one at offer stage, and 18 in our process.” – Attraction Adviser at one of The Big 4

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Customer Success Story: Big Australian Bank

One of Australia's "big 4" banks used PubSub+ to modernize their payment processing system with event-driven architecture and microservices.

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Big Data and Analytics for Infectious Disease Research, Operations, and Policy: Proceedings of a Workshop (2016)

Chapter: 4 case studies in big data and analysis, 4 case studies in big data and analysis.

In the two morning sessions, the workshop participants learned about some of opportunities that big data holds for infectious disease surveillance and research and about the challenges that need to be addressed in order to take full advantage of those opportunities in a way that benefits public health. The afternoon sessions presented more in-depth examples of how big data are being applied today in real-world settings to tackle problems related to infectious diseases as well as in areas outside of public health. Assaf Anyama, an associate research scientist at the National Aeronautics and Space Administration’s (NASA’s) Goddard Space Flight Center, described how satellite data can inform vector-borne disease research. Luciana Borio, the Food and Drug Administration’s (FDA’s) acting chief scientist, discussed several ways in which the FDA is already leveraging big data to address disease surveillance, drug resistance, and clinical trial improvement. William DuMouchel, the chief statistical scientist at Oracle Health Sciences, then spoke about the use of Bayesian statistics to analyze FDA’s database of spontaneous adverse drug events to spot potential adverse drug–drug interactions. Chicago’s Chief Data Officer Tom Schenk described the city of Chicago’s program to mine its databases in order to identify public health problems, and William So, a policy and program specialist with the Federal Bureau of Investigation’s (FBI’s) Weapons of Mass Destruction Directorate, discussed the FBI’s efforts to secure medical information from cyberattacks. Dale Griffin, an environmental public health microbiologist with the U.S. Geological Survey (USGS), provided examples of how big data and geographical information systems (GISs) can provide information about the natural environmental background distribution of pathogens, and David

Attaway, a solution engineer at ESRI, 1 discussed another approach that uses big data and GIS to map vector-borne diseases. Adam Sadilek, a senior scientist at Google, then discussed his work using artificial intelligence with big data associated with social media in order to model the spread of disease.

SATELLITE DATA IN VECTOR-BORNE DISEASE RESEARCH

Data generation is one of NASA’s primary functions, and the agency has several big climate- and weather-related datasets that can be applied to research on vector-borne diseases, Anyambar said. These datasets include 35 years of sea surface temperatures and vegetation patterns, 37 years of precipitation amounts, and 16 years of land surface temperatures. These datasets are useful for disease research because, for example, sea surface temperatures affect precipitation, which in turn affects land surface temperatures and vegetation, creating conditions under which different disease vectors emerge and are able to propagate and spread disease. In particular, Anyamba explained, long-term datasets such as these are valuable because they enable the detection of anomalies, which by themselves are not important but their persistence over time is. Long periods of abnormally wet or dry conditions affect vegetation and are important for creating conditions in which vectors flourish, Anyamba said. These periods are also important metrics used in his modeling work.

Rift Valley Fever

As an example of how these datasets are used to track vector-borne disease outbreaks, Anyamba discussed the modeling work he and his colleagues have done for Rift Valley Fever, a mosquito-borne viral disease originally discovered in Kenya in 1930 which causes severe economic and nutritional impacts on humans through illness and livestock loss ( Linthicum et al., 2016 ). The key climate feature tied to Rift Valley Fever outbreaks is the El Niño/Southern Oscillation cycle that warms the waters of the eastern Pacific and Indian Ocean and increases cloudiness in the eastern Pacific and eastern Africa. Anyamba said that almost all outbreaks of Rift Valley Fever in sub-Saharan Africa have been associated with the El Niño cycle.

In addition to climate information, another important component of the model is its representation of the population dynamics of the species of mosquitos that transmit the virus. Aedes mosquitos, the primary vectors that infect livestock and other animals, appear within 5 to 10 days of heavy rains that cause rivers to flood, Anyamba said, while Culex mosquitos, which spread the virus from livestock and other animals into humans, appear in large numbers from 5

___________________

1 A GIS software company formerly called Environmental Systems Research Institute.

to 30 days after flooding. These population spikes occur in concert with grasses sprouting after heavy rains.

The model calculates anomalies in rainfall and vegetation over a predetermined threshold value that persist over the course of moving 3-month periods for sub-Saharan Africa, East Africa, and Southern Africa ( Anyamba et al., 2010 ). Anyamba explained that these regions were selected based on a literature survey and historical records of climate indicating areas that are conducive to Rift Valley Fever outbreaks. The result is a risk map (see Figure 4-1 ) that changes over time. A retrospective analysis of the model’s performance showed that it would have successfully predicted 70 percent of the outbreaks in East Africa and about half of the outbreaks in Sudan, but only 30 percent of the outbreaks in Southern Africa. Anyamba said that the poor performance of the model in Southern Africa is largely a result of the model being created using mosquito dynamics studies from Kenya. He is now collaborating with researchers in Southern Africa to develop better information on vector population dynamics in Southern Africa in order to improve the model’s performance. He also pointed out that outbreaks have occurred in regions that had not previously been classified as an epizootic area. “This may be telling us that our epizootic area map is not well defined or that these are new areas where Rift Valley Fever is expanding,” Anyamba said.

Sharing the Results

This project was funded by the U.S. Department of Defense, whose interest is in protecting troops deployed to high-risk areas. Modeling results are also shared with the U.S. Department of Agriculture (USDA) for the purpose of screening commodities imported from high-risk areas and also with the U.S. Department of State, which alerts the resident ambassadors of potentially affected countries that may need help dealing with an outbreak. Information is also provided to the World Health Organization, the Food and Agriculture Organization, the World Organisation for Animal Health, and other international and U.S. government agencies, including an interagency group that focuses on pandemic prevention. All told, Anyamba said, some 25 organizations and agencies receive the model’s output, which includes detailed Google maps pinpointing where early surveillance efforts should focus. USDA publishes a monthly report based on the model’s output on the Agricultural Research Service website. 2

Early warning provided by this model has had a positive impact with regard to putting preventive measures in place, Anyamba said. In 2007, for example, the model gave an early warning some 3 months prior to an outbreak in Kenya and 5 months before Rift Valley Fever appeared in Tanzania. The result was that health officials were able to mount a response approximately 2 months earlier than in the epidemics that occurred in 1997 and 1998. Anyamba said that for

2 See http://www.ars.usda.gov/Business/docs.htm?docid=23464 (accessed October 31, 2016).

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2016 the model warned of potential high-risk areas 1 year in advance, and early mitigation activities have resulted in no reports of Rift Valley Fever activity in the epizootic regions.

Anyamba and his colleagues are now working to apply the same techniques to modeling other vector-borne diseases, including West Nile virus, dengue, Murray Valley encephalitis, and Zika. He predicted that new data sources, including

higher-resolution imaging of cloud cover, will enable more detailed interrogation and modeling of areas prone to outbreaks. He also said that there is still a need to invest in early ground surveillance and rapid field diagnostic capabilities for vector identification and virus isolation. In addition, he stressed that geo-referenced outbreak information—as opposed to country reports—would be important for improving models or building new models.

BIG DATA AT THE FOOD AND DRUG ADMINISTRATION

The FDA’s soul is data, Borio said, and the bigger the dataset, the better, as long as the data meet a standard for quality and integrity. In the infectious disease space, the FDA and the Centers for Disease Control and Prevention (CDC) have partnered to create the GenomeTrakr program, which uses big data for tracing foodborne pathogens back to their sources. This network of whole-genome-sequencing activities by state, federal, and commercial partners has compiled sequence data from more than 51,000 isolates and comprises 17 terabytes of data (see Figure 4-2 ). According to Borio, this network, which sequences more than 1,000 isolates per month, has enabled a true paradigm shift in the way food-borne outbreaks are identified and investigated. In 2014 case, this database enabled the FDA to trace a multi-state outbreak of Salmonella food poisoning to one nut butter production facility, halt production by the facility, and stop the outbreak ( CDC, 2014 ).

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Drug Resistance

The FDA is also leveraging big data from next-generation sequencing to analyze drug resistance when it reviews new drug applications for antiviral drugs. Next-generation sequencing, Borio explained, allows the agency to identify lower-frequency mutations in viral genomes that would not be detected using more traditional sequencing methods. In one case, the FDA’s scientists used these data to characterize potential pathways by which hepatitis C virus could become resistant to a novel antiviral agent. Although these mutations were relatively rare, they have the potential to reduce the effectiveness of the drug and limit future treatment options, should resistance develop. This information is now included in the drug’s product label and is used by clinicians to inform optimal treatment regimens. To support this type of data analysis, Borio said, the FDA’s Division of Antiviral Products built a new data architecture and infrastructure using the type of process Catherine Ordun, deputy project manager for data science and health surveillance at Booz Allen Hamilton, had described earlier in the workshop. 3

In the area of bacterial resistance, the FDA uses big data to help set what are known as breakpoints, the concentrations of an antibacterial drug at which bacterial species become resistant to a drug. Breakpoints are used to assess the likelihood of treatment success and to inform the care of patients, and the FDA and other organizations update breakpoints to keep pace as new resistance mechanisms appear in bacterial populations. To inform its efforts, the FDA supports a project at Johns Hopkins Medical Institution to create a database with medical information from more than 5,000 patients at multiple hospitals who are being treated for bacterial infections. 4 The data collected include the characteristics of the isolated bacteria, the antibacterial drugs used to treat the infection, patient risk factors, and clinical outcomes. Borio said that these data will allow the FDA to use real-world clinical data to establish and update breakpoints in a clinically meaningful manner.

Designing Better Clinical Trials

One area that Borio singled out as a prime candidate for big data applications is improving the design of clinical trials for antibacterial drugs. Typically, she noted, clinical trials to test the efficacy of antibacterial drugs for serious acute infections are difficult and expensive, and this is particularly true for hospital-acquired and ventilator-associated pneumonia (HAP-VAP). The FDA is funding a large observational study by Duke University’s Clinical Trials Transformation Initiative to identify risk factors for patients who develop HAP-VAP in order to

3 For more information, please reference the “Big Data Architecture and Analytics” section in Chapter 3 .

4 More information is available at http://www.fda.gov/ScienceResearch/SpecialTopics/RegulatoryScience/ucm454721.htm (accessed October 31, 2016).

identify those patients who are at high risk and then pre-consent them to participate in a clinical trial when they first enter the hospital. This will make it possible to enroll these patients in a clinical trial at a much earlier time-point in the course of their illness, Borio explained. This approach will also enable trial sponsors to adjust the inclusion and exclusion criteria for participation in a trial, which she predicts will increase enrollment. “The ability to improve the efficiency of clinical trials is one of the conditions that will be necessary to support the pipeline of new antibacterial drugs,” she said.

MODELING ADVERSE DRUG REACTIONS

Until the last decade or so, statisticians were reluctant to apply formal analysis models to the enormous databases that might yield associations between prescription drugs and adverse outcomes, DuMouchel said. Instead, medical reviewers would analyze spontaneous reports of adverse events and try to determine if there was a problem needing further attention. The reason for this reluctance, he explained, was that statisticians then were not interested in working with noisy data. Datasets containing adverse drug event information are inherently noisy because sample sizes are small—which is a good thing, DuMouchel said, because that means that there are not many safety hazards associated with approved drugs. Furthermore, DuMouchel said, the number of potential safety issues is large, making it difficult to decide which ones to focus on in a statistical analysis using older techniques that require deciding ahead of time what to look for at a pre-specified threshold.

The FDA database of spontaneous reports contains some 7 million records of patient reports of one or more adverse events classified according to a fine-grained vocabulary of some 10,000 different terms for approximately 5,000 drugs. From the resulting 50 million drug–event combinations, the expectation would be thousands of “significant results” simply by chance alone, DuMouchel said, and each of these would require follow-up. Traditional statistical techniques would calculate disproportionalities for every drug–event pair, generating millions of comparisons. However, a crucial insight from Bayesian statistics is that it is possible to consider these combinations as ensembles of similar drugs and similar events. While the statistical details incorporated in what are called Bayesian hierarchical models may be complicated, DuMouchel said, the result is that these models will detect changes quickly without too many false positives.

Bayesian hierarchical models can also isolate problems arising from a drug taken commonly with many other drugs, as is the case for many patients with diabetes, heart failure, or AIDS. These models are also useful for the early detection of adverse events in more structured data, such as from clinical trials, and from unstructured data such as Web search logs ( White et al., 2016 ).

BIG DATA TO IMPROVE DELIVERY OF PUBLIC SERVICES

Chicago, Illinois, like many cities, makes a wealth of data about the city available for download by the public via its website. 5 In Chicago’s case, the city posts nearly 600 datasets, including the results of testing for the West Nile virus in mosquitos trapped in the city’s 100,000 catch basins distributed across 235 square miles. According to Schenk, Chicago uses WindyGrid, an open-source system that brings together over a dozen data sources in real time into a single application in order to improve operational efficiency. Developed by Chicago, WindyGrid will be released for public use as an open-source project in 2016.

Getting Ahead of Rodents

The advanced analytics unit in Schenk’s office is working on a number of predictive applications, including several related to infectious diseases. One project developed analytics that enables the city to more efficiently focus its limited resources on the control of rodents, an important disease vector for both humans and pets. Using citizen complaints, these analytics generate a heat map showing rodent hotpots as they develop across the city. Working with researchers from Carnegie Mellon University’s Event and Pattern Detection Laboratory, Schenk’s team developed a spatiotemporal model to identify correlations among 350 different factors and spikes in rodent complaints across the city. The model identified 31 factors that predict when and where rodent complaints are most like to occur over the subsequent week.

The resulting Web application now informs a city manager who dispatches city sanitation employees to bait and look for rodents. As an aside, Schenk noted that tests showed that the city manager, who had been at her job for 20 years, was just as good at predicting where rodent outbreaks would occur, but doing so took her 1 to 2 days per week of planning. Today, the Web application handles the planning at night, and she handles dispatch duties each morning. One interesting byproduct of this project is that it identified areas of the city where citizens were not reporting rodent infestations, either because there were language barriers or because the residents did not want the city in their back alleys. “Whatever the reason, we are able to provide better service without being asked for it,” Schenk said, “which we think is a good measure of improving customer service.”

Maximizing Limited Resources

Another project, conducted in partnership with Allstate Insurance’s data science team and the Civic Consulting Alliance, was aimed at improving the effectiveness of restaurant inspections and reducing incidents of food-borne illness. As Schenk explained, Chicago has some 15,000 restaurants and 32 inspectors

5 See http://data.cityofchicago.org (accessed October 31, 2016).

who are supposed to inspect every restaurant at least once per year. He called this a classic queuing theory problem in which the object is to assign inspectors to those restaurants that most need inspecting. The project team used over a dozen publicly available data sources to develop a model that predicts the likelihood of a food establishment having a critical violation, that is, one that is most likely to lead to food-borne illnesses. Ultimately, 10 variables proved to be useful predictors of critical violations.

When the city went live with this program, it conducted an experiment comparing the performance of the inspectors without the program’s guidance with the expected performance if they had been given the prioritized list generated by the analytics. This 2-month experiment found that the data-driven approach would have to led to the average violation being discovered 7 days earlier, which would have reduced the public’s exposure time to food-borne illness. These analytics, as well as the underlying statistical model and a technical white paper explaining how the model and associated computer code were developed, have been posted online and are available as an open-source application. 6

Sharing for the Benefit of Others

Schenk said that, in addition to being an example of governments sharing with each other by leveraging open-source applications, posting these models and the underlying code provides the opportunity for others to improve on the model. Schenk stressed how interesting it has been to collaborate with others on open-source projects to improve public services and said he hopes that Chicago’s experience serves as an example for other cities to follow. He added that the city ran a competition through the Kaggle data science website 7 offering a $20,000 first prize for the best model to predict where West Nile would be spotted using data available through the city’s data portal. The city declared three entrants as winners, and his team is now blending the three models to produce a new statistical model that the city hopes to use in 2017. Schenk noted, too, that citizens have created their own applications using city data, including a program that drivers whose cars have been towed can use to find their car. In another instance, a group of citizen scientists took an existing model that had been developed by the federal government and State of Michigan to predict Escherichia coli levels in Lake Michigan and improved the model by using Chicago’s publicly available data. Chicago will pilot the new model as an aid for deciding whether to close the city’s beaches.

When asked what it is about Chicago that enables Schenk’s office to overcome the barriers that many public health officials deal with to get access to data, Schenk said that Chicago’s Mayor, Rahm Emanuel, created the chief data officer

6 See http://github.com/Chicago/food-inspections-evaluation (accessed October 31, 2016).

7 See https://www.kaggle.com (accessed October 31, 2016).

role when he first came into office and put his office in charge of maintaining and controlling all of the data generated by the city’s different administrative offices. He also said, in response to a question about privacy concerns and pushback from citizens and city employees, that his office is careful about publishing some details in the data, such as the exact address where a crime occurred. There have been instances of pushback, but he characterized them as minor.

SECURITY AND HEALTH CARE SYSTEMS

The health care sector is not immune to cyberattacks or attempts to illegally acquire data or analytics, So said. A report issued in 2016 ( Independent Security Evaluators, 2016 ) based on a 2-year study of 12 health care facilities, two health care data facilities, two medical device companies, and two Web applications (such as the one operated by Chicago but for information on health and health care) identified a number of potential adversaries who were targeting both patient health and patient records. This study also described the potential consequences of a successful attack, including impacts on patient health, the loss of patient records and intellectual property, and even, in the event of multiple or consecutive attacks, damage to the nation’s health care infrastructure.

In 2014, the FBI warned health care providers to guard against cyberattacks after a large U.S. hospital operator reported that Chinese hackers had broken into its computer network and stolen the personal records of 4.5 million patients. According to So, the FBI has found that electronic health records with personally identifying information are worth $50 each on the black market, more than a cyber thief can get for stolen credit card information. Gaining an individual’s DNA sequence could someday enable an adversary to engineer a specific virus to target that individual, a scenario first outlined in 2012 ( Hessel et al., 2012 ) and becoming more feasible as science progresses, So said. In fact, one of the authors of that scenario has started a company that claims to be able to engineer an individual-specific virus within 2 weeks to treat cancer. “What are the security implications if this does come to fruition?” So asked.

Personalized Medicine and Data Security

This question is particularly germane given the Precision Medicine Initiative’s goal of getting high-fidelity gene-sequencing data for at least 1 million Americans. 8 This goal also raises additional questions about data sharing and privacy concerns. In addition, So pointed out that there could be national security implications if the resulting data show some genetic vulnerability in specific ethnic groups.

8 See https://www.whitehouse.gov/precision-medicine (accessed October 31, 2016).

Wearable technology presents other security concerns, given that it provides detailed information on individual activities and location and even the mass movement of individuals. “How does that affect our national security posture,” So asked, “and what is a new paradigm for protecting U.S. interests and the U.S. population? Those are some of the questions that the FBI is trying to better understand.” In closing, he noted that these concerns and others related to big data, life sciences, and national security are detailed in a report produced by the FBI, the American Association for the Advancement of Science, and the United Nations Interregional Crime and Justice Research Institute ( Berger, 2014 ).

INVESTIGATING THE NATURAL BACKGROUND DISTRIBUTION OF PATHOGENS

One of the biggest needs in environmental microbiology when investigating a disease outbreak is an understanding of the natural background distribution of pathogens, Griffin said. “The data do not exist to tell us what the natural background distribution in the lower 48 states is for any given pathogen,” he said. “You might be able to tell me Ebola is not here, but you cannot tell me what is here.” Developing such a database, Griffin said, would help determine the risk to any given human, livestock, or wildlife population to exposure to various pathogens and provide insights into the roles that geochemistry and climate play in controlling those organisms.

The process of creating a GIS-based model of pathogen distribution started with the USGS Geochemical Landscapes project, which ran from 2004 to 2010 and determined the geochemistry of soils across the North America from more than 5,000 sample sites ( Smith et al., 2013 ). This survey generated heat maps for 44 different elements and a variety of minerals. 9 From the perspective of a microbiologist, these heat maps can serve as a surrogate petri dish containing a specific type of culture media that some organisms will grow on and others will not.

In a pilot study, Griffin and his colleagues combined the maps from the geochemical landscape project with a map of the outbreaks of anthrax in livestock reported since 2000 to see if there were geochemical differences associated with areas that experienced outbreaks and those that did not. This analysis identified a number of chemical elements whose levels were elevated in counties that had experienced outbreaks compared to outbreak-free counties (see Figure 4-3 ) as well as elements for which higher concentration levels were not associated with outbreaks. Griffin and his collaborators are now developing an application that will enable users to highlight a county and click on each element of the periodic table to search for patterns that may be illustrative for laboratory-based studies.

9 More information and examples of the heat maps are available at http://mrdata.usgs.gov/soilgeo chemistry (accessed October 31, 2016).

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USGS has a wealth of GIS-based models for the distribution of a wide range of climate and environmental variables that Griffin’s team is now combining with the results of polymer chain reaction–based assays for particular microorganisms, including anthrax, Bacillus species, and Naegleria fowleri , a highly lethal amoeba that consumes brain tissue. For the latter organism, low levels of copper and high levels of zinc appear to correlate to where cases of infection with the amoeba have been reported. These models were scheduled to be available on the USGS website for public use in late 2016.

In response to a question, Griffin said it is important to combine knowledge about microbial biology with the information gleaned from the model. For example, Griffin’s analysis identified strontium as an element present in soils where anthrax was found, and when an anthrax researcher questioned him about this, he was able to remind the researcher that strontium is critical to anthrax spore formation.

GIS AND VECTOR-BORNE DISEASES

By combining published information on a variety of climate and geographical data with outbreaks of various infectious disease and known locations of the vectors that transmit the infectious organism and by using a tool called similarity search, Attaway has been able to generate maps that relate environmental and climate conditions to the likelihood of future outbreaks (see Figure 4-4 ). A similarity search, which relies on a statistical application known as cosine similarity, makes it possible to identify the features or candidates that are most similar or dissimilar to specific features or attributes in much the same way that a consumer application such as Yelp makes recommendations based on a customer criteria.

ArcGIS is another tool that ESRI has developed for predictive analysis, Attaway said. This free tool provides the ability to look at suitable locations for outbreaks and offers other applications as well, such as threat detection, drug use, and urban planning, based on historical data. ArcGIS uses a process called pattern-of-life analysis that enables hypothesis testing and retesting over multiple iterations and produces predictive maps. For example, Attaway and his colleagues used ArcGIS to analyze temperature, precipitation, elevation, land cover, population density, and other variables available from public sources to identify locations suitable for year-round Aedes mosquito activity (see Figure 4-5 ). In response to a question, he acknowledged that while the analysis itself can be done in minutes, it depends on the availability of data collected over months and even years. ArcGIS’s strength, he said, is its ability to pull data together from a variety of sources, analyze it, and produce actionable insights.

MODELING THE SPREAD OF DISEASE AT SCALE

The challenge that Sadilek is attempting to address involves using artificial intelligence or machine learning in combination with online data to enable the

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development of new tools for fighting disease. Some 65 percent of adults now use online social media, and much of that activity is via smartphone, which provides real-time, in-the-moment, location-aware data. Sadilek calls this an organic sensor network, and he believes it should be possible to mine the data generated by such a network and derive value from it. Because many of these data have a location component, it could be possible to draw inferences about related events from the data and use them to make predictions.

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Although the technology is new, this approach is not. In the mid-1800s, John Snow went door to door in London asking people how they felt, and he plotted the results to create a heat map of cholera. His brilliant idea, according to Sadilek, was noting where public wells were located in relationship to clusters of cholera and drawing the conclusion that cholera spreads through contaminated water. “I think we can do this at scale now without going door to door in London, but rather by listening to the data we already have that is generated by people running around and tweeting about their environment, acting as sensors,” Sadilek said.

Following the Spread of Influenza in a City

The key challenge in using tweets, he explained, is to extract useful information from these public messages using some form of natural language processing. Simple algorithms that look for a word such as sick will not work because “I am sick of work” and “I feel sick” cannot both be interpreted as having something to do with illness. One approach would be to hire physicians to examine every tweet with the word “sick” and judge whether the person has the flu or is tweeting about something unrelated. Sadilek and colleagues at the University of Rochester took this approach for a preliminary evaluation, but this type of analysis would never scale. To create something that would scale, they developed a statistical word N-gram model, a learning application that takes human-annotated messages representing illness and others that do not and learns from those examples.

With that model in hand, it is possible to analyze all of the tweets published, identify which ones are likely coming from someone with the flu, and then track

all of the other individuals who happen to come in close contact with those individuals, as identified by the geolocation of their tweets. The result, shown graphically (see Figure 4-6 ), predicts that someone is exponentially more likely to get sick as the number of sick individuals that he or she encounters increases. This type of analysis also predicts that having a sick friend increases one’s chances of getting sick.

The value of this model, Sadilek said, is that it provides the ability to infer which specific individuals are going to get sick, something that was not possible before. In fact, one evaluation method that he and his colleagues used was to contact a small number of individuals that the model predicted were at risk, invite them to get tested for influenza, and confirm the predictions. Another approach is to aggregate the data to a zip code or county level and see if the inferred numbers agree with official CDC statistics. Such an evaluation found that the inferences correlated well with the real statistics ( Sadilek et al., 2012 ).

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Tracking Food-Borne Illnesses

Using the same language-processing technique, Sadilek and his collaborators were able to mine tweets to identify restaurants associated with cases of food poisoning in New York City. The output of this model correlated strongly with official health department reports, and Sadilek believes it can serve as a real-time tool to inform restaurant inspections. In fact, a 3-month pilot program conducted with Las Vegas, Nevada, that selected inspections based on an analysis of Twitter feeds and compared the results with a traditional method of assigning restaurants for inspection identified 50 percent more problem restaurants and resulted in 70 percent more closures ( Sadilek et al., 2016 ). Sadilek estimates that over the course of 1 year, adaptive inspections would prevent some 9,000 cases of food poisoning and more than 500 hospitalizations in Las Vegas alone. He also noted that the adaptive inspection list uncovered unpermitted venues, identified a chef with the flu, and resulted in half the normal complaints from consumers about food poisoning that would be otherwise expected. While he has not used this approach to mine data on Zika virus cases, Sadilek said he thought there was an opportunity to do so.

When asked if the growing use of private, encrypted, and closed social media systems posed a threat to this type of application, Sadilek said that while those forms of communication are growing, public venues such as Facebook and Twitter are still seeing growth. He also said that there is more information than just static location in tweets; there is motion data that reflects an individual’s levels of physical activity and driving. In fact, Sadilek has mined mobility patterns for signals of depression and found that individuals whose tweets suggest they are depressed move less and go to restaurants less frequently.

One challenge that these types of efforts face, Sadilek said, is modeling the demographic shifts associated with specific forms of communication. He noted, though, that he and his colleagues were able to generalize their Twitter model for use with Instagram, and he added that the demographics of each particular social media platform are known. Sadilek also addressed the issue of privacy and the potential intrusiveness of this type of analysis and acknowledged that there is a tradeoff between the benefits that these models can produce and the privacy that people will have to give up to reap those benefits.

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With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time. With a wide range of data available for analysis, decision-making and policy-making processes could be improved.

While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop.

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Trump ordered to pay over $355M for fraudulent business practices in New York

Ximena Bustillo headshot

Ximena Bustillo

case studies big 4

Former U.S. President Donald Trump and his lawyers Christopher Kise and Alina Habba attend the closing arguments in the Trump Organization civil fraud trial on Jan. 11 in New York City. Shannon Stapleton/Getty Images hide caption

Former U.S. President Donald Trump and his lawyers Christopher Kise and Alina Habba attend the closing arguments in the Trump Organization civil fraud trial on Jan. 11 in New York City.

A New York judge has ordered former President Donald Trump and executives at the Trump Organization to pay over $364 million in a civil fraud case, handing a win to New York Attorney General Letitia James, who sued Trump and his associates after a three-year investigation.

The Friday decision from Judge Arthur Engoron orders Trump and his flagship organization to pay the bulk of that amount: almost $355 million. Trump's two sons and co-defendants, Eric Trump and Donald Trump Jr., are each liable for $4 million. Allen Weisselberg, a former Trump Organization executive, is liable for $1 million. The total is even higher with interest — more than $450 million overall, according to the attorney general's office.

"Their complete lack of contrition and remorse borders on pathological. They are accused only of inflating asset values to make more money. The documents prove this over and over again. This is a venial sin, not a mortal sin," Engoron wrote in the court filing. "Yet, defendants are incapable of admitting the error of their ways."

Trump himself called the decision a "Complete and Total SHAM" in an emailed statement and repeated his accusation that the justice system overall is politically biased against him.

James, however, declared that "justice has been served."

"This is a tremendous victory for this state, this nation, and for everyone who believes that we all must play by the same rules — even former presidents," the state attorney general said in a statement.

Additional consequences

The judge also decided to limit Trump and his co-defendants' ability to do business in the Empire State. Trump and his companies are prohibited from serving as an officer or director of any New York business or applying for loans for three years. His sons are limited from similar leadership roles for two years.

Jeffrey McConney, ex-controller of the Trump Organization and also a defendant, was not ordered to pay any amount, but he and Weisselberg are permanently barred from serving in the financial control function of any New York corporation or similar business entity registered or licensed in New York state.

"This Court is not constituted to judge morality; it is constituted to find facts and apply the law. In this particular case, in applying the law to the facts, the Court intends to protect the integrity of the financial marketplace and, thus, the public as a whole," Engoron wrote.

The ruling comes at a crucial time for Trump, the front-runner for the Republican presidential nomination. Engoron's decision comes a day after another judge set the date for what could be Trump's first criminal trial, related to hush money payments issued during the 2016 election .

Trump's New York hush money trial will start March 25

Trump's New York hush money trial will start March 25

He is facing a combined 91 state and federal charges, including several related to his role to stay in office after he lost the 2020 presidential election to Joe Biden. But the charges have done little to dent Trump's popularity among his base. Instead, the charges appear to have bolstered his credentials, potentially setting up a rematch with Biden.

The facts of the case

Trump and his two older sons are accused of knowingly committing fraud by submitting financial statements that inflated the value of their properties and other assets. The lawsuit alleges that from 2011 to 2021, Donald Trump and his organization created more than 200 false valuations to inflate his net worth by billions of dollars with the goal of getting better business, insurance and banking deals.

Engoron had already determined that there was fraud and that the former president, his sons and other executives were liable.

Throughout the trial, legal teams argued whether the value of notable Trump properties, such as Manhattan's Trump Tower and 40 Wall Street, were inflated deliberately.

Documents shown during trial ranged from spreadsheets to signed financial statements. In one example, the attorney general's legal team showed that Trump's triplex in his eponymously named Manhattan building was marked as being almost 11,000 square feet in 1994 and later as 30,000 square feet. A Forbes magazine article in 2017 originally shed light on the discrepancy.

The former president and three of his children, Donald Jr., Eric and Ivanka, who is not a defendant, all took the stand to testify about the valuation process and their involvement in the Trump Organization. Testifying in November , Trump argued that the estimated property values were actually conservative, and he said that he relied on others to compile the statements. His sons also testified that they relied on others , including their accounting firm, to come up with the numbers — even as emails and documents showed the Trumps ultimately approved them.

In closing briefs, Trump's team doubled down on the argument that the three members of the Trump family did not have knowledge or involvement in the creation, preparation or use of the fraudulent financial statements.

Closing arguments concludes in Trump civil fraud trial in New York

Closing arguments concludes in Trump civil fraud trial in New York

Trump says he won't testify as planned in his civil fraud trial

Trump says he won't testify as planned in his civil fraud trial

Who else testified.

Witnesses included former Trump allies such as Michael Cohen and Weisselberg , who was also a defendant.

Cohen testified that it was his responsibility, along with that of Weisselberg , "to reverse-engineer the very different asset classes, increase those assets in order to achieve the numbers" Trump had asked for.

Weisselberg, however, testified that he couldn't remember whether he discussed the financial statements with Trump as they were finalized.

The decision on Friday comes as Trump continues to campaign for the presidency. He will likely appeal this ruling, as he has in the other cases where he has suffered legal setbacks. It may take years before he parts with any money in the case.

New York judge brings back gag order on Donald Trump in civil fraud trial

New York judge brings back gag order on Donald Trump in civil fraud trial

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Big 4 Consulting Firm Expands International Capabilities

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Professional Services

Number of Employees

328,000 Employees

Company Revenue

$50 Billion

Areas Served

152 Countries

Total Risk Mitigation

Compliant international travel protocols are in place for all contractors

Expansion Pending

The satisfied firm is actively looking to roll this solution to other departments in the coming months

A Process for Compliant International Engagements

A Big 4 consulting firm wanted a comprehensive and compliant solution to support international business travel by its US-based independent talent, as well as the ability to engage foreign independent workers. GATE International engagements, including any cross-border business travel, can give rise to several risks (immigration, tax, and employment law to name a few), so the firm understood that these needed to be addressed before it could adopt this aspect of its global workforce strategy.  However, moving in this direction was paramount to servicing the firm’s growing network of global clients.  It would also provide a competitive edge and help the firm become a client of choice for independent talent.

A Phased Approach and Detailed Cross-Border Risk Mitigation Strategy

MBO partnered with the firm to allow their independent contractors to conduct international business travel as well as leverage the engagement of offshore talent. Working closely with the firm, MBO started by identifying cross-border risks, key stakeholders, risk tolerance levels, and priority countries to build a series of policies, processes, and procedures.

One of the major keys to success was the firm's project management and overall approach to solutioning the problem. While MBO took the lead in developing a solution, the firm provided valuable input on timelines, coordinated regular check-in meetings to ensure deadlines were met, and communicated progress to company stakeholders to obtain input and approvals.

A fundamental component of the international offering was a detailed cross-border risk assessment, supported by input from a host of renowned subject matter experts, which analyzed the myriad of risks that could arise. This assessment determines how the independent worker can be engaged, whether directly by MBO or through one of MBO’s international partners.

In addition to the cross-border risk assessment, new policies have been adopted to streamline the overall process of traveling internationally. For example, MBO worked with the consulting firm to develop an international business travel expense policy for independent professionals. MBO also monitors travel on behalf of the firm to ensure cross-border travel risks are mitigated in accordance with defined risk tolerance thresholds. Finally, MBO audits travel records to make sure travel dates and expenditures are as expected.

Working in partnership with the firm, MBO’s international solution has enabled the firm to successfully mitigate risk and expand its global workforce strategy.

International engagements, simplified.

Over the last few years, the firm has facilitated more than two hundred international inquiries, in almost 40 countries, through MBO’s international offering. As a result, the firm reaped the benefits of using its independent talent abroad while still protecting itself (and the talent) from any risks associated with international engagements.

Countries represented

International requests since 2019

International requests over the last year

Nicole Cieslicki

Nicole Cieslicki

Senior director of international services.

Nicole is the company's international subject matter expert. She leads our international offering which has been adopted by many of our large enterprise clients.

Nicole is the company's international subject matter expert and leads our international offering which has been adopted by many of our large enterprise clients.

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Grandparents’ support can make a big difference to mothers of young children, study says

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(CNN) - A new study shows grandparents can have a positive influence on a mother’s mental health especially when mothers are separated from their partners.

Researchers in Finland tracked nearly half a million mothers of young children between 2000 and 2014.

They found mothers were less likely to use anti-depressants if their own parents were younger than 70, were still working and did not have their own health problems.

The study found access to grandparents’ help made mothers feel less depressed especially if they were apart from their partners.

But mothers with older parents or in-laws in poor health or living far away were more likely to turn to anti-depressants.

The research appears in the journal Population Studies .

Copyright 2024 CNN Newsource. All rights reserved.

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Tanganyika's hippo calf gets his name

Artificial Intelligence to Automate Health Economic Modelling: A Case Study to Evaluate the Potential Application of Large Language Models

Affiliations.

  • 1 Estima Scientific, Mediaworks, 191 Wood Ln, London, W12 7FP, UK. [email protected].
  • 2 Estima Scientific, Mediaworks, 191 Wood Ln, London, W12 7FP, UK.
  • 3 Bristol Myers Squibb, Uxbridge, UK.
  • 4 Bristol Myers Squibb, Princeton, NJ, USA.
  • PMID: 38340276
  • DOI: 10.1007/s41669-024-00477-8

Background: Current generation large language models (LLMs) such as Generative Pre-Trained Transformer 4 (GPT-4) have achieved human-level performance on many tasks including the generation of computer code based on textual input. This study aimed to assess whether GPT-4 could be used to automatically programme two published health economic analyses.

Methods: The two analyses were partitioned survival models evaluating interventions in non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC). We developed prompts which instructed GPT-4 to programme the NSCLC and RCC models in R, and which provided descriptions of each model's methods, assumptions and parameter values. The results of the generated scripts were compared to the published values from the original, human-programmed models. The models were replicated 15 times to capture variability in GPT-4's output.

Results: GPT-4 fully replicated the NSCLC model with high accuracy: 100% (15/15) of the artificial intelligence (AI)-generated NSCLC models were error-free or contained a single minor error, and 93% (14/15) were completely error-free. GPT-4 closely replicated the RCC model, although human intervention was required to simplify an element of the model design (one of the model's fifteen input calculations) because it used too many sequential steps to be implemented in a single prompt. With this simplification, 87% (13/15) of the AI-generated RCC models were error-free or contained a single minor error, and 60% (9/15) were completely error-free. Error-free model scripts replicated the published incremental cost-effectiveness ratios to within 1%.

Conclusion: This study provides a promising indication that GPT-4 can have practical applications in the automation of health economic model construction. Potential benefits include accelerated model development timelines and reduced costs of development. Further research is necessary to explore the generalisability of LLM-based automation across a larger sample of models.

© 2024. The Author(s).

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‘everything has a potential risk’: largest covid-19 study finds link between vaccine & heart, brain disorders.

Tarik Minor , Anchor, I-TEAM reporter

The latest COVID-19 vaccine study is providing answers to one of the most asked questions since the vaccines were introduced: How will this impact my health?

Global COVID Vaccine Safety Project conducted the study with the collection of data from nearly 100 million people across eight countries.

Since the pandemic began in March 2020, nearly seven million people have died across the globe from COVID-19, including more than one million Americans. It’s estimated that 71% of the world’s population has received at least one dose of the COVID-19 vaccine.

The report specifically looked at the adverse effects of the Pfizer, Moderna and AstraZeneca vaccines and found the following:

  • The study links vaccines to slight increases in neurological, blood and heart-related conditions like myocarditis, pericarditis and Guillan-Barre syndrome.
  • For instance, out of the more than 99 million people studied, researchers observed only 190 cases of Guillan-Barre Syndrome (in people who took the vaccine)
  • Researchers stressed the association between the vaccines and adverse side effects does not prove the vaccine was the root cause of the illness.

RELATED: How to get COVID-19 antiviral pills like Paxlovid | Paxlovid can lessen the chance of a severe COVID-19 illness. Why is it underused?

Elizabeth Foster wonders if the COVID-19 vaccination she took in 2020 has anything to do with the decline she said she’s experiencing in her health.

“I’m going through a lot of mental and physical things now and it wasn’t like that before,” she said.

Dr. Jonathan Kantor, who is an adjunct scholar at the Penn Center for Clinical Epidemiology and Biostatistics, reviewed the study and believes the vaccines’ benefits still outweigh the risks.

“I think what this study confirmed is pretty much what other smaller studies have said in the past. And that’s the following. Number one, vaccines have risks, I think only a fool would say vaccines don’t have risk,” Kantor said.

Kantor said the new research shouldn’t erode anyone’s trust in the vaccine, but instead prompt them to think about their medical condition and their need for protection.

“There’s no such thing as a drug that has an effect without a side effect, so everything has potential risk. The problem is what is the risk of the thing that you are trying to prevent?” Kantor said. “And that’s where it comes into play. So for example, for parents, right, if you’ve got a healthy three-year-old, who’s had COVID, four times already, well, then I’d say, ‘I don’t know what the benefit is that you’re going to get from getting that vaccine today.’”

But Kantor said the best scenario depends on the person.

“If you tell me that you’ve got an 84-year-old in a nursing home, that somehow came out of a time machine, and is now entering the world in 2020 and has never had a COVID vaccine. Well, for that person, I’d say, we really have to think about whether COVID vaccine makes sense for them,” he said.

Copyright 2024 by WJXT News4JAX - All rights reserved.

About the Author:

Tarik minor.

Tarik anchors the 4, 5:30 and 6:30 p.m. weekday newscasts and reports with the I-TEAM.

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