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Financial modeling offers insight into a firm’s performance and potential future growth. There are many items to evaluate and several benefits if you have the knowledge on what to look for. In this episode we discuss all of that and more! Ian Schnoor, Executive Director at Financial Modeling Institute joins Cassidy Clement to discuss.
The following is a summary of a live audio recording and may contain errors in spelling or grammar. Although IBKR has edited for clarity no material changes have been made.
Welcome back to the Cents of Security Podcast. I’m Cassidy Clement, Senior Manager of SEO and Content at Interactive Brokers, and today I’m your host for the podcast. Our guest is Ian Schnoor, Executive Director at the Financial Modeling Institute. Financial modeling offers insight into a firm’s performance and potential growth. There are many items to evaluate and several benefits if you have the knowledge of what to look for. In this episode, we’re going to discuss all of that and more. Welcome to the program, Ian.
Thanks, Cassidy. It’s great to be here.
Yeah, of course. Since this is your first episode, why don’t you tell the listeners a little bit about yourself and your background in the industry?
For sure. Super thrilled to be here. And yeah, my entire career has been focused on finance and financial modeling. I had a finance major in university and I’m a CFA charterholder. I started my career as an investment banker for a number of years. This was quite a while ago, during the early days—the gold rush stage, if you will—when modeling was a bit of a wild west and people were figuring out how to use Excel. Most models were a disaster. So I, on deal teams, liked to build tools that were cleaner, easier to understand, easier to follow. When I left banking, I started a training company that teaches financial modeling and ran that for 20 years—built that up. I think I taught 20 or 30,000 people all over the world financial modeling. Then I sold that business to Training the Street a couple of years ago out of New York. Now, I head up—I’m the Executive Director and head of the Financial Modeling Institute, which is the world’s only financial modeling accreditation organization. Think of it like the CFA Institute or CPA, but for financial modeling. And yeah, so that’s been my trajectory.
That’s awesome. Today we’re gonna delve right into financial modeling—you sound like the perfect guest for that.
So, when we’re looking at all of these different charts and integrated pieces of data and all these other elements that are at the fingertips for most people who are retail investors nowadays—since it used to be mainly institutional who got to see these charts in action—what exactly is financial modeling? Are there certain types of models, or is it mainly something that the user dictates based on the data that they have?
Sure. I’ll give you the definition. Anyone can build a financial model. We’re really using an Excel spreadsheet—or any spreadsheet, but typically it’s Excel. Anyone can do it. Models are typically built in corporate finance roles, so people that work in private equity, venture capital, investment banking, large credit teams, and risk groups at banks and pension funds—asset managers—they’re the ones that, on the institutional side, tend to do more modeling. But retail investors are absolutely welcome. I know a lot of people that do that. I know a lot of people that evaluate their own investment portfolios and stocks by building models. So, let’s talk about what it means. There’s a high-level, big-picture—I call it a kind of a big umbrella definition—and then a smaller umbrella, which is what we typically use in industry.
The big umbrella definition of a model is really anything that you build in a piece of software—usually a spreadsheet—but anything that you ever build in a spreadsheet to calculate something is a model. If you build a tiny calculation to do your home budget or to evaluate the performance of your kids’ football team, that’s a model. That really is. But that’s not what we mean in the world of finance. In the world of finance, when you hear people talk about a financial model, what that typically means is using a spreadsheet to build a forecast of a company.
So imagine—take a public company, take Apple, take Tesla, it doesn’t matter. If I want to do some evaluation of that company, I need to build a financial forecast. Usually, forecasts are five to ten years into the future—sometimes longer, sometimes shorter. But fundamentally, when you hear the term “financial model,” it means someone has taken the historical financial statements that they downloaded, and they have built, in a spreadsheet, a forecast over the next X number of years to look at that business into the future.
So you had mentioned that there are many different uses here. We’re using some historical data to see what the patterns are and the trends, and then we can evaluate in several different ways—most commonly Excel. But are there other elements that are associated with financial modeling that many people are familiar with? I guess in today’s world of what most people have exposure to, I initially think of a lot of documents that are pertinent to a company’s financials or maybe a handful of ratios. What do you usually see as the common elements?
Sure. Let’s talk about that. There’s a lot of components to it. What I like to say is financial modeling is very much a multidisciplinary skillset, and that’s something people don’t always realize. It requires a lot of skills and a lot of capabilities to be a good modeler. It becomes a bit of a sleuth—an investigator, if you will. A detective. It is the best way to truly learn and understand a company: build a financial model.
First of all, I mentioned in my last moment that financial modeling simply means building a forecast of the company’s financial statements. Most listeners will know that when a company reports its financial statements, all companies report an income statement, a balance sheet, and a cash flow statement. Those are the fundamental financial statements. So what we’re doing is building a forecast of those financial statements into the future. The big question is—why do we do that? And this gets to what you talked about: financial models have become the most important decision-making tools in finance.
That is what every single finance professional—every money manager, every investment banker, private equity banker—uses: forecasts to make critical decisions about the company. It might be an investment decision. You might have someone working at Fidelity or a large asset manager trying to decide if they should invest another $10 million in Apple stock. To do that, they’re going to build a financial forecast. So people build models to make investment decisions, to make lending decisions, to make merger decisions. And so, to build a strong model, it’s not just—sometimes people think of modelers as people working in the basement on a spreadsheet all day long. That’s not it at all. Modeling requires understanding how to read historicals, getting a lot of good data, reading historicals, thinking about what the future could look like, doing a lot of research, talking to people, understanding:
Et cetera, et cetera. Asking lots of good questions, thinking about what the future could look like, and then using that future forecast to make some important decisions that you want to make about the company. So there’s a lot to it. And it starts, though—you’re right—it starts by finding the historical reported statements in the annual report, reading it, learning it really well, so that you’re in a position to think about what the future could look like.
You had mentioned several different points—specific skill sets, capabilities, and then, of course, documents. And that will help the user understand the company’s performance and then maybe the potential future performance of the company. But I have to ask, what technically makes a good model? Because like most people learn in Economics or Business Statistics 101: junk in, junk out. You have to have good data. There maybe could be various models that yield various answers. So what exactly would make a quote unquote good model here?
Love it. Great question. There are a lot of things that make a good model. First of all, we need to start with healthy, accurate, robust historical information. You’ve got to start with an accurate starting point. And we trust—especially for public companies—we trust in their reported accounting statements. When you download the historical financial statements of Tesla or Apple or any other company, we all make the assumption that they’re accurate, that they’re correct, that we’re not being misled. So that’s an important starting point—we trust the reported statements are true and accurate. Then we need to think about—if we have to start by reading and understanding what’s been presented, analyzing what’s been presented—what does that mean in terms of each of the different line items in terms of what could happen into the future? Now, a good modeler—as I said—first of all, has to have pretty good spreadsheet skills, good Excel skills, because that’s the tool we’re going to use. They have to know how to read an annual report, a quarterly report, a set of financial statements. Because it’s hard to know—like you said—it’s hard to know where a company is going to go until we first know where they’ve come from. What does the history look like? And by the way, history is not necessarily a predictor of the future. It’s very possible—many companies have had exceptional growth (Tesla, Apple—I’ll keep using those examples)—that doesn’t mean the future is going to look the same.
You might intelligently determine that they’re in for a rough few years and revenues are going to decline. That might be accurate. But we have to be able to do some really good diligence work—some sleuthing. What people don’t realize is what makes a good model? A good model has to have accurate historical data going in, reasonable, intelligent assumptions. It has to have a well-built structure in Excel that has accurate formulas. Many financial models are wrong because the formulas are wrong—because people make mistakes. People don’t understand the discipline of building a powerful spreadsheet-based forecast, so there are often errors, which causes a problem. And then last—and most importantly—a model has to be a powerful communication tool. The most important thing you can do with a spreadsheet forecast tool is use it to tell a story. Nobody makes decisions based on numbers. They make decisions based on stories and emotions. And so a model has to be able to capture everything you’ve learned and tell a strong story about why you believe a particular opportunity is the right one.
I think that’s a major point when it comes to most data analysis or quantitative analysis. You actually have to round it out with qualitative analysis because you have to turn it into actionable items and more digestible items.
You can have a spreadsheet or several sets of financial data and documents that say, “Okay, revenue’s up by 50%.”
Okay—why? Okay—how? Okay—potential? Okay—seasonality? There are so many areas there that—even if it’s a five-bullet-point roundup—it gives more context to what actually comes out of those numbers. And also, to your point, as the creator of the model, there’s a chance that you’re looking to have that model be in line with your goals—meaning, what is it telling you about your financial goals? Or what is it telling you about the company or the institutional goals that you’re trying to reach? But in a lot of ways, outside of that—meaning, “Here’s our target goal and here’s where we are in reaching it”—what are the other elements of importance when it comes to financial modeling or financial modeling skills? Because somebody may think, “It’s just to see how far along I am toward this goal or how close I am to achieving it.” But there actually are other additional pros to utilizing financial modeling and the skills that come with it.
Yeah, so you don’t hear this a lot from people that teach modeling, but the most important reason to build models—to be a good modeler—is it hones your analytical skills and it hones your thinking. You become a much better critical thinker when you can build a model. Building a model is about the journey and the destination. Anybody who builds a model of a company will become the smartest person in the room about that company. So I can look at—pick any given—if I decided I want to invest some money into a stock, I can look at the news reports and I can read a research report. But there is no better way to become really intelligent and very insightful about that particular company than by modeling it. Modeling forces you to reach inside yourself, ask good questions, and think. And you’ll come out of that process with an incredible level of detailed insight that you did not have previously. So it’s very enlightening that way when you do a good job with it.
Right now, in most data and computational spaces, there tend to be trends with more people gaining access to these abilities—or more access to even just the data and the data sets. Are there certain trends in the space that you look to that may impact the future of the financial modeling area or the strategies associated?
Yeah, sure. The biggest one, of course—the big elephant in the room right now—is AI. And how will AI… AI is already radically changing the data science space: the need for programmers, how programmers work. I know a lot of programmers these days that don’t do any programming—they use AI tools to ask. And they still have to have the programming tools because they have to be able to edit and change and understand it. But they’re using AI. And in financial modeling, that is not as well developed. But people are wondering: will there be a need for humans to build forecast models of companies if you can press a button and say, “Hey AI robot, build me a five-year forecast model of…”—pick any company you want? And so that’s the big question. My own personal belief is that the AI tools will—there are a couple; there’s not a lot. Most banks, to my knowledge—and I talk to people regularly—are not using AI tools religiously for their forecasts just yet. And I don’t believe that it is going to replace the need for human modelers because of what I just mentioned: modeling is not just about getting the answer, it’s about the thought process. It’s the journey of becoming extremely intelligent about an opportunity so you can present it to your manager, to your board of directors, to your executive team. You’re the one that needs the knowledge. So, we’re seeing people play with these tools, but they’re not quite ready for primetime yet, is what I’m seeing.
We recently did a podcast on semiconductors, and if I remember correctly, our guest was talking about something similar in the same vein, which is—you do have AI to help. As a tool for all of these elements—as somebody who is an analyst or somebody who is creating any type of model—they can be utilized as a tool to help guide you. But you, as the human within this scenario, it’s up to you to absorb all the other ancillary pieces to figure out how you tell that story in the end.
Because as many models as there can be created, you have to use the critical thinking skills to bring them all together to see where you’re at—especially if you have a specific goal in mind. When we’re looking at pieces like AI, big data, cloud computing, quicker financial decision-making—and more so, real-time decision-making—there’s sometimes the element of ESG associated with how much computing power is going into this. There’s a lot of places that you may not initially think that you need to start to understand a little bit deeper as a financial modeling user. So are there certain other elements—or maybe interesting, unknown, surprise elements—for financial modeling that our listeners may not initially think of when it comes to gaining these skills?
I know you mentioned a little bit about better or sharper financial analysis skills or accounting skills, but maybe leadership skills or better understanding company valuations—or better understanding, sometimes, the actual power that gets associated with larger and larger models, as it’s getting more expensive.
Because it’s not getting less expensive these days to utilize these models. So I think there’s a lot of elements there. What are some things that you’ve found that may be surprising or interesting?
Yeah, again, what surprises people is that having strong modeling skills—and again, I’m now using “modeling skills” to talk, as we said, not just about becoming good at Excel, but really evaluating and understanding the deep inner workings of a project, a company—
One of the most surprising takeaways for some people is that financial modeling is one of the greatest leadership development skills that you can have.
You can spend a lot of money and go to a business school or get an MBA—nothing wrong with that, and I’m supportive of education.
However, learning to build strong financial models is one of the all-time great—and hidden—secret leadership development tools.
Why? Because to build a strong model—to be a really effective person to analyze and evaluate a model and a company—you need to know how to do good research. You need to know how to ask good questions. You need to know about data design. You need to know how to properly design all the data in a way that makes logical, intuitive sense. You need to know how to present it and communicate it—and to deliver and to create confidence. And anyone who’s growing up in an organization—anyone who can take data, frame it, shape it, forecast it, and create confidence amongst their bosses—is going to be highly embraced and very quickly pulled up throughout an organization. It’s not easy to come by people that can do that all the time.
And so this gets you on that track.
There’s definitely an element from human capital management where it’s almost like optimizing your resources.
If you’re able to have someone who can accurately do these models, there’s definitely elements of strategy, elements of timing, elements of utilizing tools and cross-functional collaboration. There’s a lot that goes into this. We started off explaining more from the foundational aspect, which is: we have an Excel file, these are the areas that we look for, this is how we start to frame things so we get towards a goal. But then when you extrapolate it further—and you actually look at what the employee or the person is bringing in terms of value to either the company, or if it’s yourself, toward your financial goals—that’s where you really start to see these skills sharpen. And as you said, the leadership element, I think, is something that a lot of people don’t initially think of, because in most cases, you’re going to have to present your findings. So it would make sense to try to leverage making these skills sharper to maybe having an almost collateral benefit—or surprise benefit—of leadership skills bleeding through as well.
Totally. Totally. Yeah.
Yeah, so you brought up some great points today. Thanks for joining us, Ian.
You’re very welcome, Cassie. My pleasure. Happy to be here.
Yeah, so as always, listeners can learn more about an array of financial topics for free at interactivebrokers.com/campus. Follow us on your favorite podcast network, and feel free to leave us a rating or review. Thanks for listening, everyone.
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Excellent interview! I’ve been constructing various models myself. The interviewer did a good job of asking the right questions and then not interupting.