The Human Financial Modeler: AI Insights From 60+ Global Experts

The most important skill that a junior finance professional can become exceptional at is financial modeling because once you are a strong financial modeler, it elevates you and projects you forward in so many other areas. Meet Ian Schnorr, Executive Director at Financial Modeling Institute. After starting his career in investment banking, he spent nearly 30 years working as a professional financial modeler.

You guys are releasing your finance survey from the Global Leadership Council. What this survey is, kind of a little bit of how you went about it.

We assembled a group of 63 financial modelers all over the world. They are in 26 countries. The purpose of the council is to generate thought leadership and through a couple of surveys a year that we would turn into reports.

Why don't you give us kind of some of the highlights of each chapter? Tell us a little bit of some of those key takeaways.

Chapter 1 was all about—

Financial Modelers Corner is the world's premier modeling podcast. It is brought to you by Financial Modeling Institute, the world's leading financial modeling accreditation organization. Welcome to another episode of Financial Modelers Corner. I'm your host, Paul Barnhurst. This is a podcast where we talk all about the art and science of financial modeling. With distinguished financial modelers from around the globe. The Financial Modelers Corner podcast is brought to you by the Financial Modeling Institute. They offer the most respected accreditations in financial modeling, and that's why I completed the Advanced Financial Modeler. This week, I'm thrilled to welcome on the show the Executive Director of FMI, Inge Knorr. Inge, welcome back to the show.

It is really great to be back here, Paul. So glad to be back and chatting with you again.

I think this is what, third time we've done it for this show, probably. And then count Mod Squad. We've done what, 20 episodes together now?

Yeah, probably something like that. I mean, it feels a little bit weird to be doing this just on your other show. We've had so much time together testing tools on the Mod Squad, but nice to be back on this show as well.

No, I think you may have the most episodes someone's been on across my podcast network outside of myself. Congratulations. It must be—

well, thank you. Not sure if that's a good thing or a bad thing for your audience.

I'll let you take that wherever you want. So why don't we start? Just go ahead and take a minute and give the audience your background. Tell them a little bit about yourself.

Oh gosh, my background. Well, my background is that I've been effectively a professional financial modeler for the better part of 30 years now, my entire career. From graduating with a finance degree, I went on to work in investment banking for 6 years. BMO, a Canadian bank, I'm in Toronto, and then at Citibank as well. In those days, it was a bit of the Wild West. This was the late '90s, early 2000s. Modeling was a relatively new discipline at that time. And I was doing a lot of financial modeling for M&A transactions. And I didn't love the way models were built. And I felt like there was opportunity for improvement. So I always took it upon myself not to accept the status quo, but rather to see how we could make them— I always felt that they needed to be beautiful and clean and professional and to tell a story, to make my job easier when I was presenting to clients and to make them comfortable. So I did that for 6 years. I left and then started a training company. Company called the Marquis Group, which was a financial modeling training business. Over 20 years, I spent about 2,000 full days in a classroom. I think I taught 20,000 or 30,000 bankers around the world. I built up that platform and I sold that company a few years ago to a US private equity firm. And during that time, you know, had also started, you know, was involved with a number of people globally in starting FMI as an accreditation body, a credential body where the difference is people learn financial modeling, but through any organization they want, but they can learn it through our materials, self-study, and then they work really hard to prepare for modeling exams to prove to themself that they've actually acquired the skills. So modeling has been front and center in my professional career for a long, long time.

Yes, I know it has. And speaking of career, so we have a new section called the Career Corner. We're going to start that before we get into the survey. I got 3 questions for you today.

Great.

First one is, when did you realize financial modeling could actually be a career path? How far into your career were you?

Well, that's funny you say that. You know, back in the early days, I never actually thought about this. I don't think that I ever thought of myself as a financial modeler for a long time. That identity— and in fact, I'd love to ask that question to people that are around my vintage, I'm not sure if many financial modelers self-identified as a financial modeler until more recently. I was an investment banker doing investment banking work, which required modeling, and then I was a financial modeling trainer teaching young investment bankers and private equity bankers about modeling. I don't know that anyone in the earlier days was identifying as a financial modeler. That feels to me like a newer phenomenon. In fact, it's only in the last 10, 15 years where job postings started saying we want someone that has a finance degree or an MBA or a CFA. And it's only the last 10, 15 years where they say, and strong financial modeling skills, right? That did not happen more than 10 or 15 years ago. Now you have firms that have people that are head of financial modeling, or they work in the financial modeling department. There were no financial modeling departments 25 years ago. So I would say it's more recent actually where that was an identity element and proud of that identity, but that's evolved over the years.

Yeah, and I appreciate you Thanks for sharing that. And I figured that's what you were going to say. And I think it helps people get an appreciation for how new it is as an identity, as it's becoming kind of its own career in some ways, right? It was just something you did as part of another job, which you still can do.

You still can do. It still can be a critical part of other jobs, right? I don't know how many private equity bankers or investment bankers or credit bankers today or corporate development professionals identify as a financial modeler. They might identify as their role, but they know— I mean, you can, you can still identify similarly today as, as in the past. You can be a strong finance professional with excellent modeling skills. But now there's an opportunity to actually work in some organizations as a financial modeler and to have that on your— well, nobody has business cards anymore, but if you did have a business card, it might actually say financial modeler on your business card. I promise you, 20 years ago, nobody put financial modeler on their business card anywhere. But it's nice that that can be a department, a profession, and it should be because it's a critical discipline and a skill set.

Yeah, no, I, I agree. And it— yeah, like I said, nobody's using business cards anymore. Maybe it's on their LinkedIn profile, right? You see that financial modeler for sure.

And it is, and it is on people's, uh, financial model as their primary role. Uh, and that is also newer in the grand scheme of things.

Totally agree. So that leads to a question: if you were starting a career today, how would you go about getting into financial modeling? If you wanted a financial modeling role, like kind of that title, you know, you want to be a modeler, how would— how do you think about that?

I would— well, I mean, financial modeling is a profession and a career if you, as I said, if you choose to be in a role where that is your self-identified title, or if you're in a department, in a financial modeling group. Um, but you can just as easily be an exceptional financial modeler, um, if you work in a traditional role. I mean, if you really want to learn modeling, and I strong— first of all, I strongly— I, I think it's maybe the most important skill that a junior, um, finance professional can become exceptional at is financial modeling. Because, uh, as you know, I'm going to say, once you are a strong financial modeler, it elevates you, uh, and, and projects you forward in so many other areas. Having strong modeling skills ends up doing so much because modeling is so multidisciplinary. It helps you in so many other ways throughout all aspects of your career. I'm also going to throw out a bit of a warning, and some people will appreciate this, and I'm sure some people will not appreciate or not, not necessarily enjoy what I'm going to say. If you want to become a really strong financial modeler, the best time to do that, and for many people the only time, is towards the beginning of your career. Because that's when you're given the time and the space to become truly exceptional. If you have been a finance professional, if you've been working for 10, 15 years already, it's not that you can't do it, but you need to carve time. You'll need to really create time. When you become a more mid-level or senior person in any organization, you're expected to do more people-type work. Client management, right? Um, um, managing teams of people. People, uh, financial modelers that have become exceptional often had many, many days, hours, months just to sit in the weeds with, with headphones, with, you know, with, uh, with headsets on, either literal or just, you know, proverbial headsets, just quietly absorbing. And so if you didn't do that early in your career, you'll have to really find that time to do that later. But anyway, I do think it's tremendous to have as a skill set.

I, and I agree with you. And I think that's true of most technical skills. You really want to master them earlier in your career because you start leadership. You just don't get the opportunity to use them as much. Not that you don't get to use them, but it's, you don't have the time to use them like you will early in your career.

And it's like riding a bicycle or it's like playing golf, right? I mean, if anyone here is a golfer or think of any sport, right? Um, if you become, let's say, 40 years old and you've never played a sport— tennis or golf, uh, or a musical— you can certainly learn it, but it always feels like it's not necessarily your second nature. Whereas, you know, imagine you went— if you're 40 years old and you go golfing with someone who's also 40, and they, they were a child golfer, they golfed years and years as a— and then they didn't do it for 10 years. But I promise you, when they pick up golf clubs after, after a multi-year hiatus, they're just going to look natural. They're just going to feel like it's just part of them. And, and there's something that happens with learning a skill earlier. So the message to your listeners is, if you are in the earlier stages of your career, take advantage. Elevating the skill set— this is the time.

Great advice there. All right, so let's jump into the purpose of, uh, today's episode. The main thing I want to cover is you guys are releasing your, your finance survey from the Global Leadership Council. So why don't we start with— tell the audience what this survey is, kind of a little bit of how you went about it. Give us the, uh, the rundown on this.

Sure. Well, maybe I'll even start 2 seconds before that into what the Global Leaders Council is. I mean, you know, you know, as, as FMI, um, we are the only credentialing or, you know, accreditation body in the world for financial modeling. Um, people learn modeling either with us or from anyone that they want. But they can— they enter the FMI community, they put a date in the calendar to sit a challenging exam. And there's no magic to the exam. The magic is that it forces them to practice and practice and practice that quiet time. And by the way, you know, if you're a little bit more, you know, advanced in your career, it's a great way to really pick up those skills because you're forced to prepare for an exam. And, you know, we view ourselves as trying to be at the forefront of helping to think about the future of the profession. And it's been a wonderful opportunity for me over the years to get to know financial modelers all over the world. And we thought it would be nice to create a group, a representative group of financial modelers that would help collectively put out thought pieces, leadership thought pieces on what do we think the future of the, of the profession looks like. So, you know, we assembled a group of 63 financial modelers all over the world. They are in 26 countries. They have a wide range of day-to-day jobs. These are not the best modelers in the world necessarily. They're not the only modelers. It's just a representative sample set of people who do identify for a part of themselves as a financial modeler. Um, you are of course part of the group because you are instrumental in your podcast and, um, and, and in some of the other work that you've done. Connecting financial modelers. And so the purpose of the council is to generate thought leadership and through a couple of surveys a year that we would turn into reports. So the first report seemed timely to, to talk something about AI, obviously that is. But instead of talking about what AI is going to do in modeling, we decided to flip it and spin it and say, no, no, what's the future of humanity? What's the future human role in financial modeling as a result of this new era of AI? So the report— so what we did is we surveyed the council. We served— we put— we generated an extensive survey report that went to all 63 council members. We had a 100% response rate. Everyone spent a lot of time on the survey. And from those survey results, we created this report. It's coming out tomorrow called The Human Financial Modeler. And it's a very extensive— I think it's a great document. I hope people Enjoy seeing the views of these 63 professionals.

Got it. So comes out tomorrow. You, uh, you surveyed everybody, you put together the white paper. It was on— I like you put a spin on it, not so much AI, but the human side of it. What's the human role going forward?

Is that kind of a way to think of it, or what's the human role? Well, we, we ended up based— so we, the survey had 30 questions, um, and each question had an optional spot for comments as well. So technically there were 60 places for questions. So we collected a lot of data. Um, some of the questions were Likert scale, which is sort of like a range of options, anything from strongly disagree to strongly agree. Some were multiple choice, some were short answer, uh, some were, um, you know, ranges, different ranges. But for every question you had option— the participants had an option to also send us comments. So we collected a lot of information, a lot of data, and we aggregated, um, we looked and we aggregated all the responses into 5 categories. And so the report has 5 chapters. So the first chapter talks about how this group of people is using AI today and the benefits and gains they're seeing from AI. The second chapter deals with, um, where do we— where does this collective group believe It's going to be really important for humans in modeling going forward. What's going to be— where, where will AI— where can we use AI and where is it important that we keep humans involved? The third chapter is all about trust and accountability and the govern— and governance. What level of new governance is in place, is needed with, with the combination of humans and AI working together? Then the fourth chapter is on ethics and what does, uh, what sort of ethics is required. And then the last chapter deals with the future. What do we think jobs look like? And what is— what does the group think that the future of the profession looks like? So that's how it all plays out.

Why don't you give us kind of some of the highlights? You can either take us kind of a little bit of the executive summary if you want to give highlights of each chapter, but maybe just kind of start and tell us a little bit of some of those key takeaways.

Yeah, I mean, I'll— maybe I'll give you a key takeaway from each chapter. And I'm excited for people to see the report and, and share feedback and share thoughts. Again, these are not my views or or FMI's views. They are— it's nice because it's global geographic views of a pretty significant number of people, 63 people. So, Chapter 1 was all about how is this group— we had a number of questions on the survey of how are you, how is the GLC using AI today, and how are they using it, how extensively are they using it, and how beneficial are they finding it Um, sorry, when I say how are they using it, I am specifically talking about using it for financial modeling purposes. Of course, everyone will be very clear about that.

Not using it to write emails, not—

right, not to plan, not to plan your next vacation, which is very, very good at that. But how much are you using it for agentic purposes to help you construct, audit, review, edit, modify financial models specifically, which is very different, we all know now, than um, you know, researching, uh, a travel destination. And, you know, the key takeaway there is that 86% of the council members are using AI for modeling tasks or have used it in the past year, but adoption rates remain shallow. So, um, using it, but, um, but over half of the members have said that it has led to very little to little time savings at this point in aggregate. They're using it, they're trying it. Some have actually given up on it at this point, or they're waiting for further enhancements. Um, only a small number are— have really gone hard and have built in skills automations and invested heavily, um, in, in actually having it build and meaningfully contribute to their modeling processes. Most are still watching and trying it but are— have not fully immersed themselves in it yet.

They're not really using it day to day to build models, but they're testing it, they're playing with it, they're kind of trying to figure out when does it really make sense.

Yeah, or using it for audit purposes or checking or trying to build things, but everyone's encountering some frustrations. Um, Similarly to having whether it's a new associate on your team or a new senior person, that friction and pain point of, "No, that's not what I meant," or "That's not what we talked about," or "Wait, you already did it right. Why are you changing it back to something else?" Right? Everyone's getting a little bit of a scare like, "Whoa, wait a second. When I last checked it, it was right. Now, I'm checking it again and you've changed something without telling me." Oh yes, you're so right. I forgot to tell you that I changed this. I thought it would be good if I modified this formula, but I should have told you that I was— everyone's encountering a little bit of a scare along those lines. Surely you've had those scares yourself.

Well, my background is in FP&A. I am also passionate about financial modeling. Like many financial modelers, I was self-taught. Then I discovered the Financial Financial Modeling Institute, the organization that offers the Advanced Financial Modeler program. I am a proud holder of the AFM. Preparing for the AFM exam made me a better modeler. If you want to improve your modeling skills, I recommend the AFM program. Podcast listeners save 15% on the AFM program. Just use code podcast. Yeah. So this has nothing to do with modeling, but just today and I was doing something for my website and it made a bunch of changes and I thought we were just planning and it's like, oh, okay, undo that one. You completely stuck that in the wrong section. So yeah, we've, we've all experienced it, whether it's in modeling or something else where it does something where you're like, wasn't expecting that.

No. And it's kind of crazy as you sit through it, like a part of your brain is thinking, oh my God, this is amazing. It's incredible. And then the other part of you, you might've felt wants to throw something at your screen and say, like, like you're yelling at, you know, uh, an intern saying, why did you do that? Like, we didn't talk about that. Or, or you didn't tell me that, or you edited something without informing me. Um, you've had that experience, surely haven't you?

What were you thinking? Why did you, why did you do that? Wouldn't you think to talk to me?

Right. And, and, and it didn't. And so if anyone listening has had a frustration using AI for any other type of report, if you've not used AI for modeling or agentic purposes in a spreadsheet, but if you've ever experienced frustration in a, in AI while doing any other task, just overlay that feeling of frustration into modeling. First of all, you might get some great work out of it, uh, and you'll be pleasantly surprised and excited at the same time, you might find that it will do things without telling you that are somewhat shocking, that scare you. And so it requires— so that's what we're seeing here. People are using it. They're cautious. They're hesitant on the council and are not yet finding, you know, earth-shattering time shifts. And what some people are saying is, hey, it just means I've got more time for other stuff. I've just shifted my time. I'm not exactly You know, I'm not exactly checking out at 3 in the afternoon. I'm just getting some things done a little quicker. And now I have time for other things that— right, perhaps.

Well, it's like you said when we were on the Mod Squad one time, we were talking about this. He goes, I guarantee you the lights aren't going off at 5 on, you know, in Manhattan in the finance district. The investment bankers are just— they're gonna be working the same hours. They're just able to get more done.

They're going to get more done. And instead of going to the pitch tomorrow and meeting the CFO with one model that's half-baked, they'll have 5 models that are mostly baked, and they'll have more insights, and they'll have more. But of course, as we all know, I mean, this is what all professionals have done whenever we've had productivity tools enter our professional toolkits. Um, it means you can generate more, but every time your pitch deck goes from 10 pages to 100, there is more opportunity for a number to be wrong, and the CFO will notice on page 92 you have a number and that's inconsistent with another number on page 12. And then suddenly credibility goes down, you know, the tube, and you're like, oh my gosh, I missed that. And, and then you go back and Claude says, oh yes, I didn't catch that, or I should have told you that the number was— like, there is just more room for error. So nobody— yeah, so So that was the first chapter. People are using it. Nobody is exactly, you know, kicking up their feet and drinking martinis yet at 3 o'clock in the afternoon. In the second chapter, we got into, okay, where everyone believes, everyone on the council, there's nobody on the council that is saying stop the train, stop the AI train, jump off the train, put it back in the can, and let's hope it never comes out again. No, everyone knows that we're not putting the toothpaste back into the YouTube. The question is, how is shifting? So in Chapter 2, we looked at the financial modeling life cycle. We looked at the classic 6 stages of a financial modeling project. Um, not everyone goes through all 6 stages, but the Council was asked which stages are most suitable for AI usage and which ones are least suitable. Um, and in a nutshell, in that chapter the clear conclusion came out that the shift— there will be a shift, of course, from construction to judgment. So, there will still be need for work, but we're all hoping that it means that you don't have to be at your desk at midnight building manual formulas anymore like we used to. So, the build stage, the actual mechanical construction stage will be expedited, everybody hopes and expects, through AI. But the parts around scoping, around design, what's this purpose of this model?

Who's it for?

What do they want out of it and why? And how are we going to design it, structure it, and organize it? Those pieces, the strong feeling was that there is going to continue for a long time to be, um, a human lens needed to attach to that. And so that's Chapter 2.

So I mean, that's how I feel. I think that's like you said, almost everybody in the council does. That doesn't surprise me, is still needs to be a human lens. But I think we're all excited for when AI can help us be, be faster. Now, some more than others, some will want to do it 100% themselves because there's, there's some kind of pride in building it by yourself and that struggle and be like, I did all this model and being able to do formulas exactly is what you want. I mean, just like in any profession, there are some people that are very particular about how it's done. The more particular you are on, you know, very little things, I think the harder and harder it will be to give it up to AI. Bad financial models can lead to bad decisions or worse. So how do you minimize the risk of a bad model? You make sure the models you build are great. Financial Modeling Institute developed the Advanced Financial Modeler Accreditation Program to help modelers like you. The AFM program offers a step-by-step step approach to building world-class financial models. The program ensures that you know the best practices in model design and structure and will help you brush up on your Excel and accounting skills too. Be the one on your team to build great models. If you want to impress your boss and your clients, get AFM accredited. Podcast listeners save 15% on the AFM program. Just use code PODCAST at fm institute.com/podcast.

Yep. 100%. And part of it is through what I would call just the craftsmanship element, right? I mean, if you're, if you're an artist, like if you're an artist or a crafts— a craftsperson, right? Like, if you are a mason or, you know, or, or a woodworker, um, you're right. I mean, if you're a financial— I mean, I've said this, a financial model is no different than building a wood sculpture. Um, financial models are just a virtual representation of something that exists in the physical real world. If you happen to be a wood sculptor or a mason and you like working with brick, if the day arrives that a robot can show up and you can stand you know, behind it and yell instructions and it will do perfect work, you still might not like that very much, right? Because there's something about getting your hands dirty that you might like. Now, a finance professional will probably have to, um, let go of some of that, but they'll have to know how to check it and audit it and make sure that what comes out of the final end is, is the same thing as, as if they had built it on their own. And so there will be a piece of that. Um, you know, the next chapter we got into, got into trust and governance. And probably the strongest consensus in the entire survey was that zero, zero of the 63 members, zero said— I'm just looking at it and reading right now— not a single member agreed or strongly agreed that they would be confident relying on an AI-generated model for a high-stakes decision without independent human review. 0 people said that they would be confident trusting it without human review if the stakes are high. Like if there's reasonable stakes involved, an acquisition, a financing, major decisions being made. Sure, for a pitch or a preliminary high-level discussion. Yeah, great. But if it's based— if there is a significant decision to be made, Not one person said they'd be confident in the foreseeable future using an AI-generated model without meaningful human review, uh, and checking. And we thought that was pretty, um, not surprising, but, but, uh, you know, it's telling.

It's the reminder that we're not there yet. Whatever there is, we're not, we're not there in the sense of what LinkedIn tells us we can do.

Wait, You mean there's influencers on LinkedIn that say we can just get our work done in 5 minutes?

No, no, there's not. I've never seen one.

Well, this group of people, maybe they're just technologically behind the times.

We just need to take more courses.

They need more courses, this group of 63. I'm certainly in that group. But they're not confident at this point relying on it without human intervention.

100% agree.

We asked the group about governance. 48% of the GLC members, so call it 50, half, half, half of their, half of their member organizations have no formal policy governing AI usage. And, and that was telling. So they all feel like they're in the Wild West. They know they're using something new. Everyone feels that there is some element of governance required around it. Half the organizations have nothing. The organizations that do speak to governance, it's often very light. Or one funny quote that's in the document— well, it's funny but it's not funny— said, 'Our organization keeps working on a governance, a modeling, AI modeling governance policy, but the AI tools keep changing so fast we can't even get our first draft out because it keeps changing.' And so, you know, and that's really telling as well. This technology is moving so quickly. Everyone recognizes that there is an ethical need and a governance need, but they're having trouble keeping up.

Yeah, no question. I mean, we've talked about that previously on ModSquad episodes, and I think it's something everybody's dealing with, the AI fatigue, as we've called it, just trying to keep up. It's crazy how quick this moves.

It's very crazy. And nobody, as we've talked about in other episodes, nobody's using one. Nobody that's serious into AI is just using one AI tool. Right? You're using one for idea generation, you're using something else to generate documents or reports, using something else to check and double-check the first one or the second one. The, the AI fatigue is very real, and it's hard sometimes to keep track of all it. I mean, I've had that experience, you know, in working on documents as well, where one of the AI agents will, you know, we— I think we're almost done, and then somehow it looks a lot shorter than I was expecting, and it says, oh, I didn't tell you, I edited down 25% the words to keep it within a manageable page count. Well, I didn't ask for a manageable, right? I mean, and so it will do things right without again sharing. So there is a lot of some hesitation. You know, then the last two categories in the report. So if I told you that we had a unanimous view in the report that nobody would trust an AI-generated model without meaningful human intervention, the last two sections we were split. The council was completely split down the line, um, which was around, first of all, around ethical standards. So most people agree— this is a very nuanced chapter— 70% believe that some form of ethical standards is needed and appropriate, but wide range of debate within the group on what, what is appropriate. And the 30% that don't want ethical standards, it's not that they don't want them, they're unsure of whether that's the right way to go. Like, everyone's thinking about the right way to, you know, if you use AI, who do you tell? How do you report it? Who should know, um, that you've used AI in your— and there's a wide range of views on what's appropriate. Listen, I, uh, you know, I know, uh, you know, most people on the council, this is a very, very, you know, ethical, ethics-focused group. And so everyone's trying to do the right thing, but there's no consensus right now on how to get there.

I think a good example, if I can, here on the ethics— I remember when AI first came out, when I wrote articles and different things, I would make— I would source it that it was AI. And I remember one of people were like, why are you doing that? You don't need to do that. A lot of other content creators didn't. But now I don't even think about it, to be honest. Like, you know, I help it write an article, but it's usually taking a transcript and putting something together. I'm still wording it and changing it, but I'll like These 5 words were AI. So it's, it's interesting, you know, kind of like with modeling. Okay, so it wrote a formula. Do I need to disclose that?

Exactly. And so there within the council, there's debates. Well, do I tell my boss? My boss owns the model. Do I tell my boss if I use some AI? Do I explain exactly what I did and where? Okay, do I have to tell? And, and most people believe that that part is an important reporting line. Do we tell the client? Do we have to tell the client that we used AI? And there was great disagreement on that. Some said absolutely, and others are like, well, no. I mean, the owner of the model, right, the senior person at the bank or, or whoever's building it, they're not going to tell the client necessarily the profile. Well, the per— if it was a person, the person who built it is a first-year associate on our team, or a third-year associate, or they have no modeling experience. So they have a lot of— you don't report on the exact nature of the person who built the model as long as the owner signs off on it. That's all that was done historically. So there's debate. Do we tell the client? Do we not tell the client? And, and there's no agreement there, uh, right now, um, which is telling of how early we are in this, uh, part of the process. And then the last, uh, the last question, the last chapter where there's not much agreement is what is the future of the profession look like? Roughly half right now are seeing some downward pressure on the career as a modeler, um, and almost the sec— about 10 or 15% are sort of neutral, and about 40% see upward pressure. They see more models being built, opportunity for more models, models will become more democratized, a little less expensive, etc. So again, What is the future? And I'm not surprised because it's so unclear. Nobody can possibly know the answer. And that's, you know, comes out of— that's borne out in the thinking on the report.

That doesn't surprise me. Like, like you said, doesn't surprise you either that there would be a variance of opinions because none of us know where it's going. It's like when we build a model, we don't know what the exact right answer is. That's why we're building a model to try to estimate something. Thing and to get an approximate of what we think is going to happen. And it's no different with AI and trying to figure it out. We're all looking at it and saying, okay, what do I think is going to happen, right?

And, you know, back— exactly. And back on that, like, well, a couple things. How much, you know, is it, is it different in the old days when you had a junior person building versus a more senior person? Is it a different responsibility to report back if AI was involved in doing some of the research and generating the assumptions? Like, at So these are all important ethical questions. Um, what, uh, you know, this was not in the executive summary, but it is in, uh, one of the later chapters, is there was a very, very strong, um, almost near, um, it was almost unanimous, but a very strong consensus. Over 90% of council members felt strongly that having human financial modeling skills was still going to be very important, and knowing how to build a model yourself from scratch was still going to remain important, even though I think everyone hopes and expects that you won't have to be in the weeds as often anymore. Um, but the ability to do that— that many people are worried that it will be difficult for future financial modelers to check models, to audit models, to provide instructions to AI, to check AI, if you yourself don't know how to do it. And so having the skill set was something that most of the council members believed was still very important.

Again, not surprised to hear that. So any other kind of maybe key takeaways, things that surprised you, any other thoughts you want to share about the report?

No, not much. I mean, I think it was a fascinating— it's, to me, it's a fascinating report. It's, it was really impressive and amazing to see all 63 people devote so much time to populating the survey, providing optional comments, um, and sharing. It gave us such a rich— it's given us such an amazingly rich, um, uh, report and a view of this profession and where it might be headed. Some of the— some parts are— feel more, you know, cemented and comfortable, and others, uh, as I said, the views are across the board. But, uh, no, I'll let people take a look at it. It'll be available, and I hope that people find it really, uh, instructive and helpful. To think about where we're at as a profession.

Great. Well, when that's published, send us the link. We'll make sure it gets in there for this episode so people can go download that themselves. I'm going to have you go through rapid fire again one more time. You've done this in the past. Several questions have changed. You get to pick a side. At the end, you can elaborate a little bit because I recognize there's nuance. That's the reason we're asking these. There's not a right answer. So, we're going to hold the elaboration till the end, and we're going to run through these.

So, okay, I know you, you know how much I love this. You know how much I know how hard this is for you. Um, very hard in my, in my role at FMI, um, where we, you know, just to say at FMI All right, so let's see how this goes.

Circular references, yes or no?

I'll say no. VBA? No.

Lambdas in financial models?

No.

External workbook links?

Nope.

That was the easiest one for you so far.

Yeah, easiest one. That was easy. That was the only one that I actually truly in my heart believed Absolutely no.

Yeah. I think you'll believe in this next one as well. Should modelers primarily use keyboard shortcuts? Yes. Should models always be print ready?

Yes.

Is there ever a situation where merge cells are acceptable?

Yes.

All right. Should financial modelers learn Python in Excel?

No.

What about Power Query?

Nope. Not for modeling.

How about Power BI?

You're making me say yes or no. I'll say nope.

That's what I figured you were going to say. I get a mix on that one. Should every financial modeler be able to build a fully integrated three-statement model?

Yes.

Will Excel ever die?

Nope.

Have you used AI to help you build a model in Excel? I know the answer to that one, but I'll ask it.

Yes.

What financial statement is most important for modelers, if you had to pick one? Income statement, balance sheet, or cash flow?

That is truly putting me on the spot. Um, for anyone who understands the financial statements, they are, they are literally, uh, equally valuable. I mean, it's, it's— gosh, for a financial modeler, I'm going to— people want me to say a cash flow statement, I'm going to say the income statement.

Alrighty. I always love the different answers I get on that one. It's really interesting. All right. Do you have a favorite LLM that you like to use? Claude, Copilot, ChatGPT?

Right now I'm using Claude, so I guess that's my go-to for now.

All right, so I'm curious to see what you say this one. If you could pick only one for all your models, would you choose sensitivity analysis or scenario analysis?

Scenario analysis.

All righty, and then What is your lookup function of choice? What's your favorite lookup function?

I'll go CHOOSE.

I knew you were going to— I figured you'd pick CHOOSE. I was going to be surprised if you didn't. All right. Is there something you want to elaborate on there? You got through that pretty good. You did well.

Yeah. Thank you. Yeah. Yeah. As, as I'll tell you what, if people, if anyone's wondering the theme, the thread and the theme that, that is weaving. So of course what I wanted, As you know, what I wanted to answer every single question was with, it depends. Um, but, but largely, um, but, but the theme that weaves through all my answers is, right, so as you know, I've been a financial modeler, you know, and identify that way back my whole career. I, as I said, I didn't identify at the beginning of my career that way, but now, I mean, that has been my identity back your entire—

it's been central to your entire career.

From day one in my banking days, I was building financial models. Literally, the thread that flows through every single one of my responses has little to do with technology and techniques and everything to do with clarity, communication, presentation, um, delivery, and being able to make clean decisions. So, um, so I have often found— listen, I've used circular references. I don't have a problem with circularity if you know what you're doing and if you can properly explain it and use it to client. Um, the default should be avoid it unless you need it. I mean, that, that should be the case for many things. Avoid complexity unless you need it. So I don't want to add a circular reference unless there's, you know, there's no way around it, or there's— or we're all on the same page. Um, but even some of them that might be questionable, like print-ready, people say, really, print-ready? Well, yes, even if you're never going to print it, setting— thinking about print-ready forces your brain to think about the model from a clarity, from a communication standpoint as a present. It allows you to think about the delivery, the flow, and the way you're going to treat the model as a communication tool. Even if no one ever sees the pages, the fact that you've had to think about it that way means you're thinking about it as a delivery tool, a communication tool. So again, I don't want external references. I'd rather not have VBA. It's one other element of of creating, uh, of creating risk and confusion amongst clients. Uh, sure, of course I use— I've had VBA for, for printing and formatting, and there's nothing wrong with that. But I mean, if you're giving me yes or no, I'd keep it simple. Same thing with lookup functions. I love X— you know, I'm happy to use XLOOKUP. I've just seen people get— I've seen your executives that don't know Excel that well get awfully confused by an XLOOKUP within an XLOOKUP and the, all the— whereas I've seen numerous light bulbs go off and joy on people's faces when they look at a choose function and realize, 'I actually get it. I understand it. I know how it's working.' So for me, my all answers have nothing to do with technology and more to do with how do I bring this person or group of people from the beginning to the end of a process so that they feel good about the decision that they need to make. You know, I will err on keeping it simple.

Yeah, so one of my favorite quotes, then we'll wrap up here. Favorite thoughts. I remember someone on one of these episodes said, keep the model as simple as possible to start. Always keep it simple because your business partners, the people you're working with, they will make it more complex than you want by the time you're done. And so don't add that complexity to start with, or it's just going to kind of fail under its own weight. You make it as simple as possible. Let them force you to make it more complex to meet their needs, basically. And I really like that way of thinking about it.

I promise you, it is much, much easier to start a model smaller. You know, having a 5-year annual model with 5 columns and 300 rows and the cost schedule is 80 rows. It's much easier to start that way and then be in iterative meetings with clients and have them say, yeah, that's, you know what, that's really good. We like that. Or for them to say, no, that's not enough detail. Can you elaborate this? Can you elaborate on that? And over time, maybe it becomes, you know, a few hundred rows longer, or maybe it evolves in the periodicity of all, but that's still much easier to do than start with a monthly model for 5 years, which is suddenly 60 columns and 10,000 rows of detail, and then chop it back. That's much, much harder to do. So yes, I would agree. Now, the right answer is to scope it properly and make sure everyone agrees up front to know exactly what we need and what's the level of detail. But that doesn't always work that way. We all know that it's an iterative process, but it's still easier to show something to somebody that's a little simpler and have them want to add detail than to take it away.

And I agree, scope— you get the scoping right. But so we're up on time. Any last thoughts? Anything you want to share before we let you go here?

Listen, I continue to believe that financial modeling is an incredible skill within many professions. And it's an incredible profession, you know, if you choose to make it your profession. Now you have the option. You have the option of— but if you want to work in finance or accounting, I continue to believe it remains an incredible skill because it's never— a good modeler knows it's never been about or just about building functions in Excel. It's about thinking. And it's about a forced— I have become, you know, people don't know this about me. If anyone has ever seen me in a talk, I I often will tell them that I used to be the shyest person in the room. I used to be horrified at the idea of speaking publicly, about presenting, about communicating. And I can promise you that modeling is a discipline that allows people to elevate your accounting knowledge. I've had people tell me that they really understood accounting much better. They've understood finance much better after they became strong modelers. They became better communicators. They became better researchers. And so I highly encourage people to still get into this sport, this discipline, because I know I've seen it with me and with many, many others. It has the capacity and ability to really turbocharge and elevate many elements of your professional development and your career. So I will leave it at that.

Well, thank you so much, Ian. Appreciate you telling us about the survey, allowing yourself to be put on the seat for a minute and have to answer without it depends and a little bit of Career Corner. So thanks again for joining us. I really appreciate it.

Always great to be here, Paul. Thanks for having me in.

Thanks. Financial Modelers Corner was brought to you by the Financial Modeling Institute. This year I completed the Advanced Financial Modeler certification and it made me a better financial modeler. What are you waiting for? Visit FMI at www.fminstitute.com. Institute.com/podcast and use code podcast to save 15% when you enroll in one of the accreditations today.