The FP&A Guy

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The Great Debate on AI, Excel, and the Future of Financial Modeling

Paul Barnhurst

In this special debate episode, host Paul Barnhurst aka The FP&A Guy is joined by an all-star panel of modeling experts to tackle some of the most contentious questions in the financial modeling world. This lively discussion promises insights, entertainment, and plenty of surprises as the panelists bring their expertise and humor to the table. Together, they bring decades of experience, fresh perspectives, and a shared passion for the art and science of financial modeling.

The powerhouse panel of financial modeling experts include: Derek Baker, FP&A professional and co-founder of the FP&A Hub; Lance Rubin, CEO of Model Citizen and Chief Excel Officer at Excel Cloud; Diarmuid "Dim" Early, founder of Early Days Consulting; Craig Hatmaker, retired founder of Beyond Excel and advocate for modern modeling techniques; Dr. David Brown, finance professor at the University of Arizona and founder of the Microsoft Excel Collegiate Challenge; Danielle Stein Fairhurst, Sydney-based financial modeling trainer, author, and Microsoft MVP; Ian Bennett, leader of PwC's global financial modeling practice and Master Financial Modeler; and Craig Thompson, former investment banker now innovating in software at Aleph.

Expect to Learn:

  • Why financial models are (or aren’t) the ultimate decision-making tool for businesses.

  • The role of Excel in the future: is it here to stay, or will it be replaced by emerging technologies?

  • Power BI, Power Query, and Python in financial modeling—are they worth learning?

  • Controversial techniques: the debate on circular references and dynamic arrays.

  • Whether AI will eventually replace human modelers—and how soon.


Here are a few quotes from the episode:

  • "Excel’s modern tools, like Power Query and lambdas, are setting the stage for AI to change how we build models." - Lance Rubin

  • "AI can process data, but it lacks the creativity and business acumen needed for financial modeling." - Danielle Stein Fairhurst

  • "Excel is the foundation of the financial system, and its adaptability ensures it will last for years to come." - Dr. David Brown


From the future of Excel to the role of AI, the importance of financial statements, and the tools that modelers should master, this episode explored the evolving landscape of financial modeling.

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In today’s episode:
[01:42] - Introduction to the Episode
[04:16] - The Debate Battle Starts
[07:12] - Should Financial Modelers Learn Python?
[11:15] - Dynamic Arrays vs. Traditional Models
[16:52] - Will Excel Ever Die?
[20:55] - Should Financial Modelers Learn Power BI?
[26:21] - Will AI Build Financial Models?
[32:09] - Circular References: Useful or Evil?
[39:27] - VBA in Financial Models
[44:41] - Number One Corporate Decision Making Tool
[52:58] - Which Financial Statement is Most Important?
[59:50] - Conclusion and Audience Poll


Full Show Transcript
[00:01:29] Host: Paul Barnhurst: We're going to go ahead and get started. We got a lot going today. So this is the great debate. We're going to discuss a number of important modeling issues. You know circular references VBA will excel ever die. All those fun things. We're going to settle them all once and for all or something like that. Like I said, my name is Paul Barnhurst. I'm the host of Financial Modelers Corner. We'll turn this into a podcast episode. Financial Modelers Corner is sponsored by Financial Modeling Institute. They have the most respected accreditations in modeling. I highly recommend them. And with that, we're going to do a quick round of introductions before we get to our first question. So I'm just going to go through and introduce everybody we have. And they could just kind of say a quick hi and where they're coming from. So I'll start at the top of my corner Derek Baker.


[00:02:19] Guest1: Derek Baker: Hi, my name is Derek Baker. I work in FP&A at a startup called Circle, and I also work with Paul on building an FP&A community called the FP&A Hub.


[00:02:29] Host: Paul Barnhurst: Thanks, Derek. Lance


[00:02:29] Guest2: Lance Rubin: Hi, I am Lance Devine, CEO and founder of Model Citizen and Chief Excel officer of Excel Cloud. I'm based in Melbourne, I love Excel, I love financial modeling, but I love tech as well. Great to be here. Thanks, Paul.


[00:02:41] Host: Paul Barnhurst: All right. Perfect, Dim.


[00:02:43] Guest3: Diarmuid Early: Hey, I'm Diarmuid Early, also known as Dim. Coming from New York, and I work at my own firm, Early days consulting.


[00:02:50] Host: Paul Barnhurst: And if you want you guys, when you're chanting for Dim, you can refer to him as LeBron James. I knew I'd get. Craig


[00:02:59] Guest4: Craig Hatmaker: I'm Craig Hatmaker, I'm retired, founder of Beyond Excel and I'm coming from Salem, Virginia, USA.


[00:03:05] Host: Paul Barnhurst: All right. Love it. Thank you. Professor or doctor David Brown.


[00:03:10] Guest5: Dr. David Brown: Yep. David Brown, associate professor of finance here at the University of Arizona in Tucson, Arizona, also the founder of the Microsoft Excel Collegiate challenge.


[00:03:20] Host: Paul Barnhurst: All right. Great. Thank you. Danielle.


[00:03:23] Guest6: Danielle Stein Fairhurst: Hello, I'm Danielle Stein Fairhurst, coming to you from Sydney, Australia. Financial modeling specialist, trainer, consultant, author. And I'm also a master financial modeler and with the FMI and a Microsoft MVP.


[00:03:37] Host: Paul Barnhurst: She has it all covered. Thank you Danielle. Ian. 


[00:03:40] Guest7: Ian Bennett: Hi everybody. Ian Bennett also coming from beautiful Sydney, on the land of the Gadigal people of the Eora nation. And I'm a professional financial modeler and have been for almost 25 years, and I'm lucky enough to lead PwC's global financial modeling practice and the amazing team we have here in Australia. And like Danielle, I'm also a master financial modeler with the FMI.


[00:04:04] Host: Paul Barnhurst: Love it. Thank you Ian. And you look way too young for 25 years. All right, so here's how the rules are going to work today. We have two people on opposite sides of the argument for the question. They each get a minute 45 to argue it. You guys can put your comments on who you thought will win. If they go more than five seconds over, I will mute them or do something. We'll figure that out, but I'll let them know they're done and you can tell us in the vote who you need, who you thought won. We'd love to get your input. Let us know what you think of the different questions. So what's going to happen is we're going to put everybody behind. But we have Derek and Lance for this first one. This is a little bit of a surprise question. So they weren't expecting this one. All right. Are you two ready?


[00:04:53] Guest2: Lance Rubin: Yeah for sure.


[00:04:55] Host: Paul Barnhurst: All right, we're gonna start. I think we'll start with Lance on this one. He'll argue. I'll tell him what side he's going to argue. The question is, should financial modeler be spelled with 1 or 2 L's? I think you get the two L's. Lance. Right?


[00:05:09] Guest2: Lance Rubin: Yes. That's right.


[00:05:10] Host: Paul Barnhurst: Yep. Derek, you get the other side of that for this one, you only get a minute. I don't think you need a minute 45 to argue this one. So we're going to give you a minute.


[00:05:19] Guest2: Lance Rubin: Who's going to go first?


[00:05:20] Host: Paul Barnhurst: All right. Are you ready? Yeah. All right. Go.


[00:05:24] Guest2: Lance Rubin: We speak the Queen's English. Most of the English language is built out of the Commonwealth. I live in the Commonwealth. Two is always better than one, you know, two people, two hands. You know, two is definitely the way to go. And if you're on your own and you're number one. It's a bit self-centered. I like to work in couples. Couples are great. You make great things as twos. And really, modelers work in twos, right? There's an income statement and balance sheet. There's actually three. We're going to talk about that later. But you know, looking at just one perspective, you've got to look at both perspectives. You know we've got to take both sides of the debate. Right. What would a debate be like with only one. Right. It wouldn't be a debate. It would be useless. So one model for 'L' is just not good enough. We've got to show that model is Double L's double fisted, and it's powerful. That's it.


[00:06:15] Host: Paul Barnhurst: Love it. Thank you. Thank you. Lance, double fisted and with five seconds left over. Right. Derek, are you ready to argue for one L.


[00:06:23] Guest1: Derek Baker: I guess so. Well, while Lance was talking, I asked ChatGPT and ChatGPT said one l because it's based in America. And so ChatGPT is now the authority of all truth, I think, in this new AI driven world. And so I think that's why I have to go with one l.


[00:06:42] Host: Paul Barnhurst: That's it. Come on. You can give us a little more.


[00:06:45] Guest1: Derek Baker: I have always spelled it with one l and the reason for that is because autocorrect also corrects me whenever I spell it with two L's.


[00:06:54] Host: Paul Barnhurst: There you go. We don't want to upset the computers. So you're going with AI, and the computer's let us know in the chat who you thought won that one? Well, we'll announce that later, but for now, we're going to get to some serious questions. We had a little fun with that one. Danielle was supporting you in the comments there, Lance. You thought Lance won or you thought Derek won? Let us know in the comments. But next we're going to bring on Derek. You get to stay for this one. You ended up being two at the beginning because we moved things around. So we're going to bring on Professor David Brown. There he is. All right. This will be a fun one. As many of you know, Python recently was launched in Excel. And there's a lot of different opinions on Python. And when I asked them, "Should financial modelers learn Python?” David Brown said yes. Our professor here. So we're going to give him a minute, 45 to explain why we should learn Python, and then Derek will get the opposite side of that.


[00:07:56] Guest5: Dr. David Brown: All right. The fundamental argument here is that we should always be learning new skills that make us better. Python is that new skill today. It's probably going to change in the future, but for now, Python is where so much of the programming is happening. So much of the technology is driving through Python. That's what the students know and they're coming up and getting trained on. And so knowing Python is going to give you capabilities that are outside of your normal tech stack, the ability to scrape data from websites very quickly and efficiently to take a graph, take that graph and put it into a numerical table where you can, you know, scrape that from many different websites, many different documents and assemble it all together. That's not something that Excel is going to be well handled to, or any of the other kind of traditional FP&A products. Fundamentally, financial analysts need to be able to solve problems, and often being able to solve a problem efficiently means you need to go get data. , you know, if you're in an environment where you're given the data and you just analyze it. That is very different. And maybe you don't need Python, but in order to be a flexible, useful financial modeler in this new ChatGPT driven world, you need to have the tools to be able to get the data. And Python is a great tool to do that, which is why you should all invest your time into learning Python.


[00:09:08] Host: Paul Barnhurst: All right. Thank you, Professor Brown. Derek.


[00:09:11] Guest1: Derek Baker: Yeah, I actually agree with a lot of David's points. And I also know Python. , as a financial modeler, I think I'll piece out this argument a little bit and say you shouldn't learn Python to use it in Excel. I think if you're learning Python because you want to use it in Excel, you're probably limiting yourself and what's possible with Python. And if you're good enough to learn a coding language like Python, you should probably just stick with an editor like VS code and actually build Python scripts and not build it within Excel. The reason for that is I think that, you know, Excel has some limitations. It's limited to, from what I understand, anacondas, libraries and things like that. And there are a lot more that you can do if you do, if you use Python within an editor like VS code. I also think that if you're just getting started in financial modeling, you should ignore Python because it's a distraction. All financial models start in Excel, and they can be enhanced a lot with Python by interacting with APIs and bringing external data into those financial models. But if you're just getting started and you're learning how to build Excel models, you should stick with Excel and not not get into Python because it can be a big distraction. There's a big learning curve, but ChatGPT is helping a lot with that these days.


[00:10:30] Host: Paul Barnhurst: All right. Thank you Derek. You both finished a little under. So I'm going to give you 15 seconds there Professor Brown to provide any counter thoughts.


[00:10:40] Guest5: Dr. David Brown: I think Derek picked some great examples of why you wouldn't want to use Python. I agree that you know, Python and Excel. I think it's a great place to learn Python if you've already learned some Excel. You can learn Python in there. But otherwise I agree with your points. I think it's a nuanced thing. I think it's generally great to have Python, but you don't want to start there by any means.


[00:11:01] Host: Paul Barnhurst: Totally agree. It definitely is nuanced for sure. Derek, any last second thoughts you want to say?


[00:11:07] Guest1: Derek Baker: No, but I can give a couple of examples how I do use Python in financial modeling. I use it a lot like what David said. It's a great way to go and get data, fetch data from API's, or automate some reporting that gets eventually put into Excel or into dashboards. So I'll just say that's how I, how I've used Python.


[00:11:24] Host: Paul Barnhurst: I appreciate it, always great to educate as we do this. So please let us know in the chat. Who do you think won that one? Feel free to vote for our next two guests on the stage. We're going to bring Craig Hatmaker and Dim Early onto the stage. All right. This is going to be a fun one. If anyone knows Craig, we know what he's passionate about. Starts with an L and ends with an A, so this is probably something around that type of thing and modeling a certain way. So the question is only dynamic array models in Excel. Or should we be building those. And we're going to give Craig the yes argument. We're going to let him go first because we like to let seniors go first. And then Dim will get the next part going to get myself in trouble by the end of this. It's on our podcast here.


[00:12:20] Guest4: Craig Hatmaker: Okay. Well, dynamic arrays, I want to preface what I'm about to say with dynamic arrays and financial models require Lambda. Yes, my favorite subject or 5G functions. That said, for many models, dynamic arrays have so many benefits they make model file size smaller, they make model performance faster, they make inconsistent formula errors impossible. They eliminate the copy to write step in every row. They make model templates adapt to any time period or interval they can accommodate changes in. Things like asset count. Automatically they can reduce formula cell count by more than 90%. They can solve circularity without VBA or enabling iterative calculations. They look identical to traditional models, and for what it's worth, they have smaller range references. As I said earlier, dynamic arrays and financial models require lambda. Lambda requires a higher skill set unless using 5G functions. My favorite subject 5G functions are pre-built pre-tested functions that anyone of any skill level can use in any model. So rather than writing our own functions, we can just import 5G equivalents and not know a thing about Lambda. 5g functions look and feel just like native Excel functions and include inline help. They are version controlled, fully tested and documented and easier to read and understand than the formulas they replace. This is because 5G functions internally name their arguments and formulas. They even include comments, so they explained themselves. They are the opposite of black boxes. Well, customers accept them. Some have 100% fully dynamic models with 5G. Functions are in use now by one of the world's largest accounting firms and several investment firms. Over to you, Dim. All right.


[00:14:04] Host: Paul Barnhurst: And with one second to spare. Well done. Dim, give me one second. I'm going to reset the timer here and we'll get to hear your counterargument. Go.


[00:14:15] Guest3: Diarmuid Early: All right. I have to caveat this by saying I agree with Craig on a lot of this stuff. I'm a fan of dynamic arrays. I'm a fan of lambdas. I also wasn't expecting to be fighting this one, especially against Greg, but I am happy to take up this side because Greg and I, while we agree on a lot of things, don't agree on fully dynamic models. A couple of reasons for that. Number one, it depends on the situation, right? Like it depends on your audience. It depends on their level of technical skill. Like Craig is right to say that if you have a perfectly tested 5G function, you can use it. You can treat it like a black box. Your users don't need to understand how it works, but if you hand over a model to a client, to an investor and say, I just, I just use this 5G function. Someone told me it's good. I don't actually understand how lambdas work. They're not going to have any faith in your model. So it does depend a lot on the sort of size of your circle of trust, so to speak. But the big thing for me in terms of fully dynamic models is the corkscrew limitation.


[00:15:15] Guest3: Diarmuid Early: So if you just naively build a financial model that involves a corkscrew, in other words, this period depends on the last period. Like anything, you know, depreciation schedule, a debt schedule, anything like that, it will not behave correctly like it will treat it as a circular reference. If you have this array refers to this array, and this array refers to this array and it's slow to calculate. Now you can get around that for any one schedule. And again you know Craig has lots of cool functions for that. They're great. But here's the big thing. If you introduce an additional circularity, a circularity that ties together different pieces of your model, sorry, circularity, an additional corkscrew that ties together different pieces of your model. Like if our revenue gets over a certain amount, then we'll invest more in this stuff. Then suddenly lots of different pieces of your model are tied together. The only way to make that work is to have a lambda that models the entire thing. And at that point, your complexity is alarming.


[00:16:07] Host: Paul Barnhurst: All right. Thank you. I think we got a great argument by both. Alright. Clearly gives the opposite of dim. Well done. I like that one. It took me a second, but we're going to see a couple comments here. Fully dynamic models are pretty difficult to build until every function is billable. Trying to make a model can make a very simple model complex, I would agree. Excellent, Craig. I'm trusting your responses, aren't AI? Good point Der. I like it, I think it means dim but immediate loss of credibility. So those are a few there. All right. We're going to go to the next one. But let us know who you thought won that one. Very well. Great arguments on both sides. Definitely brought the consultant side using a lot of it depends. You probably have some experience with that. Kate said great rebuttal Dim. All right. Next one we're going to bring on the stage. We're going to have professor David Brown will be joining me. All right. We're going to let him go first. This is the one that I'm sure we'll get lots of opinions on. Will Excel ever die? Professor Brown has said no, it is immortal. It will live forever. Tell us why.


[00:17:26] Guest5: Dr. David Brown: All right. So first I'm going to back off slightly on the forever because nothing's going to last truly forever. So maybe let's recast this in my lifetime. So I guess I got four reasons it's not going to die. Sorry. Three reasons. First, it's the foundation of the financial system, right? So much of what we do in businesses and, really the entire business world is predicated on Excel, maybe not today as much as it was in the past. But fundamentally, people want to get things into Excel so they can manipulate it themselves. So that's number one. Number two, Excel itself is doing an amazing job of modernizing. It is making itself with the last question with syllable arrays, dynamic formulas. All of that is making its capabilities much higher than it was in the past, so people can continue to use it as power users going forward. And then the third reason is, the one that's nearest and dearest to my heart is that it is a foundational program that you can educate people with the ability to bring people into a grid where you can see things laid out in numbers, and you can lay lay your thoughts out basically in a grid format that's not going away. If there's one thing I think is going to live forever, it's that humans are going to be using a grid to express themselves in their ideas. Is it Excel? Well, right now it looks like it's going to be Excel forever because Microsoft is in the leading position. You could argue sheets is making a big move, especially with the younger generations. But in general, I think Excel is making that innovational innovation step. Now they're pushing on copilot. They're going to make Excel what lasts forever.


[00:19:06] Host: Paul Barnhurst: All right. Thank you David. Appreciate it. I'll get to argue the other side here. And I'm arguing it for David Thompson. So I'll share some of my own thoughts. But he wrote his up. He had an emergency and couldn't make it. All right. So I'll give myself a timer here first thing he said, which is a great quote that I think applies. As John Maynard Keynes once said, in the long run, we're all dead. Right. You did preface it with lifetime. He did even actually say, it's going to die. I don't see it in my lifetime. Now, he also mentioned he's seen the systems change a lot over his time, you know, in his career. It went from punch cards to Fortran, COBOL, Visicalc, Lotus, Quattro Pro, Symphony and now Excel. Why are we to think Excel will be there forever? Agree. A grid sheet will be. A grid will always be there. We'll use some form of a grid in some way. There will also always be a tool to model, right? We're always going to need to build financial models. What part AI plays what we play. We'll see how that all works out. But I think to say anything is going to last forever. It just isn't the case. Now, if we argued next 20 years, good chance Excel is probably here. Good chances, maybe longer, but at some point it will die just like we all die.


[00:20:27] Host: Paul Barnhurst: That's just the way of the world. So I think in many ways we agree with the forever part that okay, it's hard to say forever. I think we would both agree in the short term. Excel's not going anywhere. I will agree with you. As you mentioned, they've done a ton of modernization. That being said, there are a lot of new tools, web based things that Excel struggles with being both desktop and web that they're going to have to make some changes. So it may even be that they go to a web version and Excel kind of replaces itself with something else Microsoft does. All right. Thank you, Professor Brown. We'll now move on to our next question. Give me one second here. I'm getting to wear two hats for that one. All right. Next we're going to bring up Craig Thompson and Ian Bennett. All right. Hope you're both ready. This question is should financial modelers learn power BI is the question. Let us know in the chat how you like the last ones. What you think on the Excel question while Well, we go through this one and we have Ian Bennett arguing, yes, we should learn power BI. We're going to have Craig Thompson arguing no. So we're going to give Ian the floor first here to get us started. So when you're ready go ahead.


[00:21:52] Guest7: Ian Bennett: Hi, Paul. Hi, everybody. So should we be learning power BI and the suite of tools? Absolutely. We should. As financial modelers, we should be embracing these tools. We are in the middle of a citizen tech revolution right now. For too long, the only option we've had to fill the gap between the systems of the world and what finance and business really needs is Excel. And we've heard that already from many of the speakers. But newer tools are coming in. And as Microsoft starts to talk about modern finance and the tools that support that being the power platform and fabric, we are going to see a whole new world opening up for all of us in terms of how we tackle these problems. And within that power platform, power BI, Power Query, Power Pivot and also Power Automate and Power apps are going to revolutionize, I think, how finance tackle these problems. So financial modelers are some of the greatest problem solvers in business. They are some of the most adapt to new technologies, and they are some of the most curious people in the world. They are by far the best placed group of individuals to embrace these new tools and to take them into business and solve problems that haven't been solved before. Even if you are only looking at transaction models where you might think that these tools are totally relevant today, I am certain that they will be increasingly relevant in the future and will become to rely on them. And so learning those tools now and embracing those, as we've done with our clients recently in producing new automations, saving time in the accounts payable department. These things are going to be necessary.


[00:23:38] Host: Paul Barnhurst: All right, you get it right at a minute. 45. Perfect. And great job, Craig. Let's hear your argument.


[00:23:45] Guest8: Craig Thompson: Perfect. And first, I didn't get my intro in the beginning, but it was. So my name is Craig Thompson, former investment banker now at a software company called Aleph. And I think, look, the way I approach these things is really trying to optimize for, for two things. When we're talking about anything in the Excel universe, I think one is correctness and how quickly you can build to correctness. I think the other is auditability and how easy someone else can be involved in figuring out what we're doing. And so as it relates to power BI, I think the big advantage of not using power BI is in a lot of cases, you can just use regular old Excel to to embrace a lot of this stuff. And I think the big advantage there is simplicity and ease of use for other folks on your team. I think the big disadvantage and drawback of using something like power BI is one it's not especially optimized for finance specifically. It's sort of a broader kind of data analysis tool. And as the one power BI power user in your organization, you're sort of the only one that can modify. And it's a little bit of a black box for other folks. And so I'm sort of in two camps, there's the world where just use regular old Excel can matter and can be impactful for a lot of cases and simplicity. But if you are looking for a tool like that, I do think there are other tools out there, some of which have already been mentioned earlier, that are a little bit more tailor made for finance teams that are easier to use without that black box feeling. And so it's not known to supplementing Excel. It's more for finance folks specifically. There are a couple other paths. And this is a little bit of an in-between for me.


[00:25:26] Host: Paul Barnhurst: All right. Thank you Craig. Appreciate that. Let us know what your thoughts are. I'm going to throw a few. We have just a minute. A few things that people said. We have a LinkedIn user. Power BI will help more tasks become automated without the need to know VBA. Interesting to see. I kind of think of Python and Excel and some of those things doing that, but time will tell. Lance, a big power BI guy I know that. So his: is the next evolution step for financial modelers. With two capital L's you can't spell. But that's okay. We won't hold it against them with fabric. You are really stepping up your game scaling large. I'm going to stick two L's in large as well. Large data is not possible with an Excel in for the win is what he has to say. Harry: excel for bespoke work. By repeated work, we'll do one more. Then we'll jump to the next question. Power BI for internal operating models. Straight Excel for banking and private equity. Thank you. There's people bringing nuance, as we recognize with all these questions, there is nuance. That's why we can all just say it depends and go home. But that wouldn't be much of an episode. All right, next up we have Danielle and fellow Aussie Lance arguing against each other. All right. Perfect. This will be a fun one. So the argument they're going to take is they're taking opposite sides of will AI eventually build the model for us. You know it's always nice ladies go first. So we're going to give Danielle the start here. And she's arguing no, that they will not. So you are on the clock whenever you're ready Danielle.


[00:27:11] Guest6: Danielle Stein Fairhurst: Okay. Let's do it. All right. Yeah. Will AI eventually build the models for us? I just cannot see it happening. I cannot see it. I just can't see it happening. Ever in the world of financial modeling, I think that AI can do. I mean, we get really excited about AI don't we, we're like, wow, yeah, AI can do everything. It can do so many things much better than a human can like. It can process large quantities of data much faster than we could. But could it build a model? I just don't think so. I can't see it happening. So think about the skills of being a good financial modeler. So things like design and layout and having business acumen, communication presentation, industry knowledge, adaptability, critical thinking, time management and teamwork. You know, all of those things that make being a good financial modeler, I just can't, I just don't think that AI has or ever possibly could have. So financial modeling is an art and it's also a science. So yes, AI can handle technical skills, but it can't do original thought. All AI does is it just copies what's there and then it makes things up. It's generative. So you can't just make up numbers for a financial model. So AI technologies like they can use predictive analytics and they might forecast the numbers and just you know put those numbers in there. But will those numbers be right. That's the question. And is it going to just make them up. And how are we going to validate and check those numbers that are in there. We don't build models anymore, remember. So we've lost our built in. So I cannot see it happening ever. We're not going to have AI building our models over to you lads.


[00:29:09] Host: Paul Barnhurst: All right. Never going to happen, says Danielle, Lance. Convince us why it's going to happen one day.


[00:29:14] Guest2: Lance Rubin: Never say never. Seven Reasons Foundations Excel is now Turing complete. It allows end-to-end coding modern Excel with its open source Power Query, dynamic arrays and lambdas. It provides all the necessary ingredients we have for AI modeling. Open source Lamp is a game changing demonstration that has shown us that already in the Financial Modeling World Cup. Modular spreadsheet technologies, old school and closed source. This is open source. Number two spreadsheet LLM research. Microsoft are putting a huge amount of effort to get natural language processing to work with a grid-like structure, like a spreadsheet that's going to be solved. Number three VBA resurgence with AI. People have embraced, non-coders have embraced VBA because of AI. AI is helping us be more coders and do things better. Number four, the accounting and finance industry still doesn't have enough modelers around, and there's a demand to have really competent models build good models. AI is going to help us. So the industry is pushing us to go there. The benefits are huge. Accuracy, speed, cost, efficiency, scalability. And of course you start to integrate that with other technologies like Microsoft Fabric and Power BI. It'll overwhelm and really improve efficiency. But human judgment. Yes, Danielle, I hear you, but let's be honest. Creativity. Things we didn't think I could do. It's now doing. Tell jokes. Write poetry. Even have relationships as scary as that might be. I'm going to do some amazing things that we don't even contemplate right now. Last one ethics and regulation. Yes, that might stop and slow us down to some degree. But look, right now we have so many LLMs: ChatGPT, Copilot., Grok, Gemini, meta copilot. It's not going to stop this machine. And this is absolutely going to help us build models. We can build components of it, we can scale that. And really it's going to change the way that we build models. It's still going to have human interaction, but the actual building is going to be done by AI. And I reckon in the next 3 to 5 years.


[00:31:06] Host: Paul Barnhurst: FP&A guy here, and as you know, I am very passionate about financial modeling and the Financial Modeling Institute's mission. I have been a huge fan of the FMI for years, and I was super excited when they decided to sponsor the Financial Modelers Corner. I recently completed the Advanced Financial Modeler certification and love the entire experience. It was top notch from start to finish. I am a better modeler today for having completed the certification. I strongly believe every modeler needs to demonstrate they are a qualified financial modeler, and one of the best ways to do that is through the FMI's program. Earning the accreditation will demonstrate to your current and future employers that you are serious about financial modeling. What are you waiting for? Visit www.fminstitute.com/podcast and use code Podcast to save 15% when you enroll in an accreditation today.


[00:32:12] Host: Paul Barnhurst: All right. Thanks. Love it, in the next 3 to 5. So he not only said it's going to happen, he threw down a timeline. We shall see. Let us know what you think you got, you know, a lot of comments coming in on this one. So thank you Lance and Danielle. We're going to go to our next question here. This is one that LeBron James or some call him Dim Early is passionate about. This is the one he wanted. So we'll bring him on stage and we'll bring on Craig Thompson. We're going to bring him back to argue on this one. We'll give Craig, I think last time he got to go last. So we'll let him go first on this one. This is a big one. I think everybody has an opinion on it. Circular references in financial models. Craig you argued: Yes. So you're on the clock to defend why.


[00:33:04] Guest8: Craig Thompson: Perfect. And I'll start in 45 seconds. I'll let him go. I'll hear the passion and then maybe I'll reserve 45. But I think for me it comes down to simplicity and it comes down to auditability. And I think that there are certainly workarounds to circular references. I think in like the classic lender model, you know, there's like a geometric reference formula that you can use. But good luck explaining why you put that geometric reference formula to anyone else on your team for how it looked. So when it comes to auditing how a model works and being able to actually see the trace of the circular reference actually see it as a benefit rather than a negative thing, that it makes it really easy to audit how it works. I think circular references have a whole host of other advantages, like in scenario analysis, other places where you're trying to.


[00:33:49] Host: Paul Barnhurst: All right, you did that in 45 seconds. And he's going to give you your time there. And we'll see what you have to say. So LeBron James go for it.


[00:34:00] Guest3: Diarmuid Early: All right. So let me just start with the technical stuff. There's all kinds of like circular references are very clever engineering. But number one they may not converge. And it will not be obvious if they don't converge. Because if it doesn't converge it won't throw an error. So you could have something that's like adding $100 to your net profit every time you recalculate the model, you would never realize they can have multiple equilibria. Which means again, just because your model does converge and stay at a fixed set of values doesn't mean that's the only solution for the model you've set up. This stuff is actually really complicated mathematically. And number three, again, back to the point that you don't know if it's calculated. If you run a data table to do a bunch of different scenario analysis, you won't know in any of those scenarios. Has your circular reference actually converged, or has it just spiraled off into some kind of doom scenario? I don't really agree that they're easy to audit. I actually think they're quite hard to audit. , because, you know, because there is a circularity. But also if you have an error, like if you have an error in your model, it propagates, you fix the source, the fix propagates. If you have an error in a circular reference, it dirties the whole model and then you clean it up. But that's still being dirtied by the circle back from the original thing. It's going to get you in trouble when your client breaks, the model hits undo, the model stays broken and they're like, what is going on here?


[00:35:17] Guest3: Diarmuid Early: That's the sort of technical side. The business side for me is it's just a false accuracy. Like if the go no go on a project depends on this kind of weird timing assumption of like interest on interest for half the period. Then you need a different model. Like you need maybe a monthly model instead of an annual model. Or you need something that's more granular about cash flow timing. If something is kind of insignificant in the big picture, interest is going to be what makes the decision. I'm good.


[00:35:44] Host: Paul Barnhurst: And how was it? What was the sound they make when they get with that? Was it, and a few swear words? Was that kind of how it was? I didn't really pick that up.


[00:35:52] Guest3: Diarmuid Early: I slightly self-censored.


[00:35:54] Host: Paul Barnhurst: That's all right. You can have fun with that. All right. Craig, you got a minute left?


[00:35:59] Guest8: Craig Thompson: Sure. So, first, as a former debt capital markets banker, those circular references absolutely matter. In fundraising conversations. It hundreds of thousands and millions of dollars on the line of doing that accurate calculation. So it definitely matters. Very easy to audit all MAA. You can trace the references in your circular reference, you can see the loop super easy to do. The formula logic is also very straightforward. So I think like across those two cases it's great to use. And then as I mentioned there are non-financial like non quantitative use cases of circular references where you're trying to pull different values in different situations. So for me, easy. Absolutely. Definitely want to be able to use circular references.


[00:36:41] Host: Paul Barnhurst: Alrighty. Well thank you. And with a few seconds left. So let's just see a few recent comments. All right. Lebron James thinks it's hard to edit. Will: as an Ex-big five. We would never have circular references in the model to pass the peer review. Deloitte has one. They ran one of our models to flag all the potential conflicts. All right let's see Eric. Well, Eric Duke wants more. Craig. Sorry, guys. What can I say? The robot has spoken. If good models are designed to be clear, simple, logical flows, then circularities are bad, says Harry, and Giles comes in with his strong opinion. There's no way circularity wins out. All right, well, let us keep running.


[00:37:35] Guest3: Diarmuid Early: The crowd is on my side.


[00:37:37] Host: Paul Barnhurst: Now, those are a few of our comments. We'll do one more. The trick with circular references is knowing exactly where they are. I prefer always to have a hard break somewhere. That's from Chris. All right, as you can see, lots of opinions on that. Dim and Craig, thank you. Up next, this is a surprise question we have Danielle Stein Fairhurst is going to join us for this one. And I will get to argue the other side. So we're going to be arguing. Should financial modelers corner be spelled apostrophe s or s apostrophe. Danielle will be arguing for the s apostrophe. You get one minute on this one. So when you're ready, you can go ahead.


[00:38:19] Guest6: Danielle Stein Fairhurst: I don't need a minute for this one. Obviously if you put apostrophe s, I mean beside the fact that you've spelt modelers incorrectly. Besides that, the fact that if you put apostrophe s, that means there's only one modeler. There's a modeler sitting in the corner. Is that what the podcast is about? I don't think so. It should be s apostrophe because that is multiple financial modelers. We're getting together and talking on a podcast. I rest my case.


[00:38:50] Host: Paul Barnhurst: Thank you. Here's the counterargument. At the end of the day, modelers need their own place. We're kind of like left out. A lot of times there's the accountant, there's the finance. So we set up a show where you can go on your own and listen to that show, go to your special corner and learn. It's called the Education Corner and that's Financial Modeler's Corner. So it definitely should have been apostrophe s. I mean, many of us are introverts by nature. We don't want all the modelers in the room with us learning together. Forget that we want to listen to the show on our own. So it's really all about apostrophe s. Thank you for humoring me on this one, Danielle.


[00:39:27] Guest6: Danielle Stein Fairhurst: I was not expecting that one.


[00:39:29] Host: Paul Barnhurst: I know you weren't, but I figured you'd get a kick out of it. Yeah, yeah, because you were the first one to let me know. You're like, you need to change the name on the show, so. But please let us know what you guys think on that. I can also change it to two hours. We can have a vote on that as well. All right, we'll go to the next one here. We're going to bring on Ian Bennett and Derek Baker for this one. All right. Perfect. So the question for both of you here, we're going to let Ian go first. So we're going to let seniors go first on this one Derek going to get myself in trouble there. Use of VBA in financial models. Ian is going to argue yes. Derek's going to argue no. So we're going to put you on the clock here Ian. Let me give me one second. When you're ready you can go ahead and go.


[00:40:22] Guest7: Ian Bennett: Hi everybody. So let's be clear. The question here is not whether or not we should be learning VBA, and it's not whether or not VBA is dying, VBA is dying, its end is in sight and it will be replaced and it will be replaced really soon. Paul, you mentioned that Excel will maybe turn to the cloud. It's already there. That is the future of Excel and VBA has no place there and will not function. It will be left behind. But right now we have no choice. Financial models are necessary for some of the world's most important and largest projects. They are making major, major decisions and bring trust to each one of those transactions. And frequently and often there are demands placed upon them by financiers of the individuals whose blood, sweat and tears have gone into that project, which is manifest in the model around how that model should look. It needs to be transparent. It needs to be easy to use. It needs to be in Excel. It needs to have a debt solver. And that debt solver needs to be in Visual Basic. And that is non-negotiable for anybody trying to do those transactions. So at that point it's absolutely necessary. Should they be suggesting something else? Maybe they should. But just by way of example, I ran a seminar recently for a group of Japanese banks, and I asked them what version of Excel they were on, and it was Excel 2016. That's eight years old. We cannot use newer features until the banks who are providing the money to these people whose life dream is in these projects and, we cannot use things that they can't use. So we're dependent on VBA for some time yet.


[00:42:07] Host: Paul Barnhurst: Five seconds. All right. Thank you. And, Derek, are you ready for your rebuttal? To counter his argument.


[00:42:14] Guest1: Derek Baker: I don't know what a debt solver is. I haven't worked on a project complex enough to need to do something like that, but I have used solver in VBA and the one time I used that was in my finance class to find the optimal portfolio of a few stocks, and I think that there are much better tools for doing something like that. And something that comes to mind is Python. And so I think a lot of the things that have historically been used in Excel VBA are now being used in Python and other technologies like that. I also think that VBA has a place right now currently in Excel for some automated reporting where you can easily click a button and all the reports get sent out to stakeholders from an Excel spreadsheet. But that doesn't really have anything to do with financial modeling. I haven't built, I've built operating models for a dozen companies now, and I've never needed to use VBA. I think one of the use cases of VBA is actually creating custom formulas, which may be helpful if you have a very complex formula. But now we have let and lambda, which it gets rid of that need for VBA to create any custom formulas. So it's possible that I just haven't worked on complex enough models to need to use VBA, but I can't think of any realistic use case where VBA needs to be used when you couldn't use dynamic arrays or Lambda and let instead.


[00:43:34] Host: Paul Barnhurst: All right, thank you. I pulled up some of the different comments we got. Lance likes the VBA, they're not for calculations, he said. We got another one, only to be used for automation. Apart from debt sculpting, VBA does so much that Office Scripts still does not. So there's someone saying we're not. Maybe it's not going to be dead here soon. It's being replaced by C sharp for development and web ads, web apps I think. And what happens now. So we shall see. I'm only going to learn VBA for micro Automations. So we got those are a few of our comments. All right. Thank you. And thank you Derek. Appreciate you joining us. We'll throw, I'm going to throw out a joke real quick and we'll go to the next question. So you know me being the FP&A guy, it has to be an FP&A joke. So does anyone know what the difference is between an accountant and an FP&A professional? The difference is when an accountant gets creative, they go to jail. When an FP&A professional gets created, they get promoted. So let your children. Don't let them be accountants. Let them go into FP&A. Eric Owens says VBA will never die. Never say never, Eric. All right, let's go to the next question. We're going to bring back in one more time to argue this one. And we're going to bring back LeBron James or Dim as some call him. He's going to get sick of me calling him LeBron James. Like come on. All right. Here we're going to argue our financial models. The number one corporate decision making tool. This time we're going to let them go first. Dim is arguing no. Ian is arguing yes. So you ready LeBron.


[00:45:37] Guest3: Diarmuid Early: I'm ready.


[00:45:39] Host: Paul Barnhurst: All right. Start whenever you want.


[00:45:42] Guest3: Diarmuid Early: All right. Well this one is, this one is definitely not as much of a, you know, subject of rage as the circular references. And I suspect it's going to be one of these of like, oh, we agree on most things here, blah, blah, blah. As you've been mocking us for already, Paul. But look, I think financial models are great. I think that used with intellectual honesty, they are very helpful decision making tools. But I think that if we as financial modelers are to be honest with ourselves, are they, in fact the number one corporate decision making tool, or are they much more often used to rationalize decisions that have already been taken for a variety of other reasons, whether that's, you know, someone's intuition about where the business ought to go or whether that's, you know, ego or corporate politics or whether it's, you know, factors that are rightly not taken into account of a model because, you know, it's I don't know if someone is forecasting what they should be doing with the role of AI in their business, like there's only so much that a, that a financial model on historical data can tell you.


[00:46:44] Guest3: Diarmuid Early: You know, it can certainly inform your debate about, well, you know, if the range of plausible assumptions for this to be a go is here. But the real debate is are those plausible assumptions? You know, is the future going to resemble the past? You know, I think a financial model is a great backdrop to those conversations. Again, I emphasize when used with intellectual integrity, because often it's a case of, well, the model has to say X, the model has to say that we're worth this much money because that's what we're trying to IPO for. The model has to say that this is within the range of fair prices, because that's what we're trying to sell ourselves for. And, you know, very often, it's if you torture the data enough, it will confess. And if you have a sufficiently wide range of assumptions considered credible, you can make your model say almost anything you want. I think that's more often how they are used than actually really driving the decision.


[00:47:38] Host: Paul Barnhurst: All right. Thank you. Thank you. Dim. Ian, let us know why they are the number one decision making tool.


[00:47:45] Guest7: Ian Bennett: So I think Dim's point, if I paraphrase, is that humans are the world's number one decision making tool, and I can't disagree with that. But if we're going to say more broadly about the tools that those humans rely on, undeniably Excel is the king here. Excel just turned 40 years, and for way more than half of those, it has been the world's number one decision making tool. And for many years there were questions about whether Excel will die. And perhaps it looked like it was in the wilderness. But right now, today, it is categorically holding that position. And my view is that it will again, more so in the future. , if you think about what Excel brings to us every day and you think about the number of people that love it, like genuinely, absolutely love it, with not a hint of irony. If you were to go and look at the kitchens of the world's accountants, you will find I love spreadsheet bugs in almost every single one of those kitchens. It is universally loved. Yes, with some little bit of concern around some of its niggles. But we love it for its transparency, for its flexibility, for its ease of access, for its ability to tell a story very quickly and in a bespoke way. For all these reasons, we will continue to embrace it going forward and rely on it. And yes, maybe it's justifying a decision we've already taken, but maybe it is telling us something we didn't already know. Either way, it is categorically the number one tool. And frankly, when you think about how Microsoft is now positioning it as the cockpit into modern finance tools, as a cockpit, into broader finance, it is not only a little toy that we can use to be, to support decision making. It is now the heart and foundation of finance.


[00:49:27] Host: Paul Barnhurst: All right. Thank you Dim. Thank you Ian. As I had one guest say on Financial Modeler's Corner and this is my favorite answer yet when I asked this question they said, no, it's politics. And I was like, see you both go. That's hard to argue with. I did the same. I'm like, that's probably one of the better answers I've received. But as far as an actual tool, I get the argument there. So thank you. Both of you loved it. All right. Next we're going to bring on Craig Hatmaker. And I guess I'll get to make up the other side of the argument. We lost our guest. Even though I don't agree with the side of the argument. We'll see if I can come up with a good counter in a minute here. So the question is, should financial modelers learn Power Query arguing yes, is our very own Craig Hatmaker. So I'm going to put you on the clock when you're ready. Go ahead.


[00:50:22] Guest4: Craig Hatmaker: Well, thank you for not having me argue against Dim again. So my response is based on my corporate career, I'm retired now, but for those starting out in their career, I recommend obtaining both financial modeling and Power Query skills to broaden their job market. Adding Power Query to our skill set makes us more attractive to the corporate market, where a wealth of financial data resides in financial systems, if we need actuals, we can import them directly into our models with Power Query, and if we need to update actuals, we can simply refresh our Power Query Power Query, combine financials to find underperforming business units, and to use historical data to model the business opportunity of remediating those business units and then the IRR of taking on those tasks. I attribute such activities to my career success. One project I found 4 million in annual recurring bottom line profit, and another project I was credited with realizing 8 million annual recurring revenue. Those projects predated Power Query before Power Query. We used VBA and SQL to extract information from our ERP that required a good deal of technical know how. Power query removes that technical requirement and transfers the task of financial data mining from IT to finance professionals where it belongs. Having Power Query skill sets in no way diminishes our ability to land financial modeling opportunities that do not need them. But as the saying goes, better to have it and not need it than to need it and not have it.


[00:51:49] Host: Paul Barnhurst: All right, well done Craig. I see. How do I argue this side? Google sheets doesn't have Power Query and it is growing. So, you know, as more and more people start using Google Sheets or equals or other tools. Equals has a low code. No code with SQL. They're going to be other options. So you need to learn how to pull data. Sure. But you have to learn Power Query. No. Is it beneficial? Yes. Does every financial modeler need to know how to access data? They do, but that doesn't mean you have to learn Power Query. There are lots of other options. Is it good to learn it? 100% agreed. I am a huge fan of Power Query, but I don't think it's necessary for a modeler to learn it. There are other ways Python now other things you can do to pull your data. I think you get a better investment being more well-rounded with something like SQL. So if you're using other tools outside of Excel, you're working for a shop. It's not a Microsoft office. You have that capability. So my view is it will be great. I don't have any disagreement that it's beneficial to learn, but I just don't think it's necessary. There's other ways you can do this.


[00:53:04] Host: Paul Barnhurst: So, you know, be real careful. Is that where you want to invest your time? All right. I'm done arguing that. I agree with Craig. That's my real position. All right. Thank you. Craig, we're going to move on to the next one here. This is our last question. And then we'll quickly bring everybody up on the stage and wrap up. So we have Lance, Danielle. And we'll just go to Lance and Danielle because we lost David. So we just have two sides to this. So it's which financial statement is most important if somebody wants to argue cash flow. Let me know I'll bring them in. But for right now we're going to start with Lance and Danielle. We're going to let Danielle go first. Danielle is going to be arguing for the PNL as the most important statement for a modeler to understand. Lance is going to be arguing for the balance sheet and Ian is going to come on and argue for the cash flow. So we're going to have an all Aussie argument here. All right. We're going to go Danielle. And Ian. I realized yes I get excited sometimes as I'm talking. All right. You're on the clock Danielle. Go ahead and go.


[00:54:15] Guest6: Danielle Stein Fairhurst: All right okay. Let's do it. So we know that a financial model contains a P and L cash flow balance sheet. But the most important one for the modeler to understand is the PNL. Of course. Obviously it's the PNL, because that is where all the action happens. I mean, who cares about balance sheets and cash flows? They're boring. It's about profitability. Profitability is what people care about. So yes, cash is important, but you need to be making a profit to have a business. So the PNL is where it's at because it's got that sort of linkage. You know, everything that matters goes through the PNL. So if it's important to the financial model, it's going to be on the PNL. So depreciation. We're going to see that come through onto the PNL. Anything that happens with fixed assets, debt, interest, all of the revenue, all of the expenses. So even items like retained earnings, accounts receivable, which drives working capital. And it all comes from the PNL. So you need to understand it as a modeler. So a lot of the measurements, like the outputs of a model, are metrics and ratios like EBITDA, just like your cap there, Paul. So thank you. Thank you for voting for me, Paul. All of these things profit, DCF investment decisions. They all come from the PNL. And lastly what about scenario analysis. Basically, the whole point of building a financial model in the first place is being able to do scenario analysis, and most scenario drivers are around the revenue inputs or the cost drivers which come from the P and L. So if you're saying the P and L isn't important, you'd be saying that it is not critical for a financial modeler to be able to understand scenario analysis. So I put to you the P and L is the most important financial statement for a modeler to understand.


[00:56:11] Host: Paul Barnhurst: All right. Thank you, Danielle, and thanks for throwing me into that argument with the hat. Well done. Lance, you're on the clock balance sheet.


[00:56:21] Guest2: Lance Rubin: Great. Six points quickly. Cash is king 100%. Cash represents value. And it's a critical balance sheet item, not cash flow balance sheet. If your model doesn't balance its balance sheet and cash, it's fundamentally flawed. Number two accuracy check the balance sheet ensures the accuracy of the other two. Your income statement and your cash flow depend on the balance sheet to keep them in check. It connects the three statements they effectively go through and show the position elements like working capital, interest on debt, cash balances, depreciation. Need the balance sheet like fixed assets to drive the PNL. It's the comprehensive record. All financials entries land up in the balance sheet. The profit and loss goes through to retained earnings. Cash flow goes to cash in bank. Number four, it's the company snapshot. The balance sheet shows exactly the current state and value of the company. It's critical for assessing solvency debt to equity and many many other key ratios. Number five it's the complete story. Income statement and cash flow is only a point only over certain periods. It's only periodic. It's critical for only assessing just that movement. The balance sheet has the full picture. It has the start. It has the moving movement and it has the end model accuracy. There's no better check than does my balance sheet balance. That is the fundamental balance sheet item in the cash flow models that we build. And three way is the best way to do it. And sorry Danielle, not everything goes through the PNL. There's lots of things that hit the cash flow and the balance sheet. They don't even go near the PNL to manage the most important thing. Cash profit is not cash, and therefore scenarios are more around the position and performance and the value of the company, not what's going through on a periodic basis, but where you end up, not where you start. Might be boring, but it's critical for people to know and understand and be really fundamental and sound in their model. Building balance sheet balances model is good.


[00:58:15] Host: Paul Barnhurst: All right. Thank you Lance. And as Danielle wanted to argue, it's boring. But we have someone else sharing on team cash. So Ian, you have someone voting for you there, team cash, tell us why. It's the cash flow statement.


[00:58:31] Guest7: Ian Bennett: So I'm incredibly grateful to be called in the last minute to defend the cash flow statement. And as per the comments, I've already won without speaking, so I feel like I'm at an advantage. And Lance nailed it. Cash is king, but not just how much you've got, but how you generated it. The cash flow tells the story of the most important part of your business, the lifeblood of your organization. It tells you if you're about to go bust, if you run out of cash. But it also tells you how much you're generating and, as Lance said, feeds directly into valuation. Like, I like what Danielle said about the business drivers, they are absolutely crucial. And the PNL tells that story. And it's useful to know how your business is made up at a certain point in time. But if I want to think about the future, I want to think about how I'm generating cash. When you think about due diligence activities, those people, they're amazing colleagues of mine. They spend an awful lot of time unpicking Danielle's PNL and turning that EBITDA number on Paul's hat into cash. If you think about the cash flow itself and it's a three way, all it's doing is taking EBITDA. It's taking Paul's hat and showing how Paul's hat turns into cash. The cash flow spends its life.


[00:59:45] Host: Paul Barnhurst: I wish it turned into cash. Oh wait. Keep going.


[00:59:49] Guest7: Ian Bennett: The cash rotate, spends its life on picking all these other odd ways of looking at a business and telling you the most important thing is, which is how is your cash generated?


[01:00:01] Host: Paul Barnhurst: Thank you Ian. Thank you everybody. We've had a ton of activity and comments. We're going to bring everybody back on stage now and wrap up. All right I think that's everyone who's left. Wait. There we go. Thank you. Derek brought himself back on. So I want to thank all of you so much for joining. I hope you had fun with that. I hope everybody enjoyed arguing. Here's the reality, right? With all of these. They're nuanced. I think everybody would agree with me. There is some nuance to every question we ask, some less than others for sure. Some. It's almost always the it depends. At the end of the day, you can see we had some world class modelers here who have differing opinions on things. Some think there's two L's, some think there's one. Some love circular references. Some think they're evil. Right? We have a little bit of everything. And so thank you so much for taking time to join us. And as far as the winner in my book, they're all winners. So I might have to think a little bit more because I get in giving me that look. Come on, I won. Give me that, give me that, I won. So we'll give a minute here before I go, let me know in the comments. Who do you think made the best arguments today? If you had to vote for one of these people, we're going to give us another minute or two here. Let me know who you would vote for. This is kind of like America's Got Talent. In the final rounds, the audience votes.


[01:01:35] Guest7: Ian Bennett: Paul. Surely the true winner is financial modeling here. So that is the winner of today.


[01:01:42] Host: Paul Barnhurst: Yes, that is true. So in that sense, we all win And we can all go to our corner.


[01:01:50] Guest2: Lance Rubin: Or at least the Aussies are punching above our weight and size compared to the rest of the globe. Yeah, small, small, 20 million population, you know. Really nothing.


[01:02:00] Host: Paul Barnhurst: Hey, you got Danielle. You got a fan there?


[01:02:03] Guest2: Lance Rubin: Wonder who that is.


[01:02:06] Host: Paul Barnhurst: We have lots of legends. 


[01:02:12] Guest4: Craig Hatmaker: We all win.


[01:02:13] Host: Paul Barnhurst: We all win with all the great information in loses. For the cheesy comment, you can take that up with Giles: LeBron James is our winner. You mean all the mods? Thank you. Warren. I like Warren, he's our winner. Peggy says Danielle, even though I disagree about P&L, will is voting for Ian. Robert says Lance and Craig. Alright. Let's see. And just for fun. Oh, it's great fun. Thank you all. Great debate. Some person named Tate is putting some eyes in there. Who knows what that's about? And Robert says the numbers count. Alright. Well thank you so much for joining me.


[01:03:07] Host: Paul Barnhurst: 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/podcast and use code Podcast to save 15% when you enroll in one of the accreditations today.