What's The Big Deal?
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From mega-mergers and hostile takeovers to complex private credit transactions, they break down the why, the how, and the who behind the numbers.
What's The Big Deal?
Will AI Replace Wall Street Investment Banking Jobs?
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Welcome to the fourth episode of the 'What's the Big Deal?' (WTBD) podcast powered by Wall Street Prep.
AI is advancing at an exponential pace. Tools like Claude, ChatGPT, CoPilot and Shortcut are fundamentally reshaping workflows and what it means to be an investment banking analyst.
But where are we right now? And where are we heading? In this special episode of the podcast Wall Street Prep Founder & CEO Matan Feldman and Graham Smith discuss the current state of play and if analyst jobs are really under threat.
SPOILER ALERT: The overwhelming takeaway is completely counterintuitive to the current prevailing narrative and that is potentially very exciting.
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Time Stamps:
Introduction: 00:00
The Current State of Play for AI Tools in Investment Banking 02:18
How Good Are These Tools Right Now 04:39
What Do These Tools Do Well 5:52
The Dangerous Errors These Tools Make 7:39
Are These Tools Good At Tricky or Advanced Analyst Work 11:42
The Impact Will These Tools Have on IB Recruiting Pathways And What You Need To Be Successful 14:47
The Potential Increased Demand for Investment Bankers 20:52
Are Investment Banks Replacing Analysts With Technology 23:38
What AI Tools Are Investment Banks Using (Claude, CoPilot, GPT) 26:35
What You Need To Do As A Future Investment Banker 27:21
Why You Still Need Fundamental Financial Knowledge As Well As AI Tools 30:03
The Dangerous Temptation Of AI Tools & The Wrong Way To Break Into The Industry 34:29
Which Divisions Are Adopting AI 36:26
What AI Doesn’t Do: 39:23
Are Roles Under Threat & How Do You Future Proof Yourself 42:42
Will Be An Investment Banker In The Future Become More Interesting 45:50
Advice for Analysts & Future Investment Bankers 47:33
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It feels like this is all moving so fast. Today that could materially change seven days from now. To your point, you never would have even expected that Claude or GPT could do all this stuff.
SPEAKER_01Tools like Claude and others like Shortcut and ChatGPT has come out with a really major improvement over capabilities in Excel.
SPEAKER_00How you think the analyst rule is going to change if if at all? AI is not good enough today to do anything. So a huge part of the work is. Hey everyone, welcome to this week's episode of What's the Big Deal? I'm Graham Smith, and today I'm here with our founder and CEO, Maton Feldman. Maton, how's it going? Good. Nice to see everybody. So today, this week, we're not talking necessarily about a deal in the market. We're talking about more of a market phenomenon right now. And we've kind of highlighted this and touched on it over the last couple episodes. But really on the note of we've been talking about this AI software scare trade. Today we want to talk a little bit more generally about AI and finance and what we think the impacts of AI might be on some analyst roles and some junior finance roles, how that's going to impact the market over the next coming months and coming years. It feels like this is all moving so fast. So I think you're pretty well, pretty well versed on the topic. And I'm excited to talk about this a little bit today. Likewise, happy to be here, excited to talk about it. So you have put out a bunch of content, some blog posts and videos recently, reviewing some of the AI tools. So why don't we kick off by talking about just where we think the market stands right now? Acknowledging this is this has moved on a lot even in the last couple years, right? Two years ago we had what, chat GPT, there was no kind of Excel add-in. It was fairly basic. Now it feels like we've got a lot more focused, bespoke tools that can really start to tackle the job of a of a junior professional. So where does this all stand right now?
The Current State of Play for AI Tools in Investment Banking 02:18
SPEAKER_01Yeah, um, it's a good framing because if you were to talk about this two and a half years ago, I remember talking to a friend and saying, you know, this will never hit Excel. Like, you know, the Excel is just too complicated. It might be able to get the coding, but like there's just too much going on. It's a visual thing along with coding. And um we're now at a place where the the progress is so fast that you know if you do an evaluation of where these tools are today, that could materially change seven days from now. Like that is the that is the sort of level and pace at which uh things are changing. So in terms of the current state, um you know, and and I'll focus on Excel and financial modeling in particular, it's a very important workflow um for our clients, and and and that's when we spend a lot of time looking at. Today, the tools that are out there, and there's been a real massive um uptake in sort of capabilities, really, since Opus 4.6 came out and cloud. Yeah, uh Cloud came out in that with that with that model. Today tools like Cloud and others like Shortcut and NDX, and now ChatGPT has come out with a really major improvement over um on its capabilities in Excel, really at the level um across a lot of variables of a poor, poor investment banking junior analyst. It's it's almost as good as a poor uh analyst. And we we know that because we actually ran all these tools through the gauntlet of assessments that we put our new higher uh trainees through. And, you know, there's a whole rubric of how you can evaluate those uh those analysts, and it's you know, it's kind of creeping up. It is almost as good as a poor analyst. It is still, though, almost as good as a poor analyst.
SPEAKER_00Right. Well, I guess you gotta be you got to be pretty good to be a bad analyst, even to get to have gotten the job. So that's a certain certain benchmark you're reaching already. So the fact that it's even at that point now is is kind of impressive, actually. Like, think about this a couple years ago, to your point, you never would have even expected that Claude or GPT could do all this stuff, and here we are.
How Good Are These Tools Right Now
SPEAKER_01It's it's beyond impressive. It's actually mind-blowing. And and again, the qualifications around all of that is that even a poor analyst is a super agent that these things are not. A poor analyst can go and have conversations and write emails and do a whole bunch of things that these tools are only now starting to have the capability of doing. Yeah, they're nowhere near that kind of capability yet. Um, but when you're looking at sort of specific workflows, um, it is mind-blowing that it can do um the work of a poor analyst. Because to your point, it is really, really hard to become an analyst. Even the worst ones have to go through a gauntlet of interviews and uh learn a lot. So it is it is quite impressive.
What Do These Tools Do Well
SPEAKER_00So what is the what is because I've I've played around a little bit with these tools, and admittedly I've got to do more because when we were just talking on the walkover here, so many clients are asking about AI training and integrating an element of AI into normal training programs. From your perspective, the work you've done so far, what's the what are the things that these tools do well versus still have some improving to do?
SPEAKER_01So good question. There's there's a lot that it does well, and there's a lot of work that still needs to be done to make them truly um truly hyper-productive. So in terms of what it does well, um they're much better at getting a um a model, for example, or an analysis done from scratch. So if you were to if you're in a scenario, and by the way, this isn't the most common use case in a vessel banking where you just sort of start with a clean slate and you have to yeah, you're usually using a template, right? Like you're usually using a template. Um, although I will qualify even that. It is good at starting things. So even if you feed it a template that's empty, or if you give it guidance around um some existing template, or you say, let's start something from scratch, it's really good at that first step.
unknownYeah.
The Dangerous Errors These Tools Make
SPEAKER_01It's really good. It just sort of it it is sort of not, it is not yet taxed by too many prompts, by too much overlapping context, and it just gets the job done. There's another qualifier to that, which is it is not incredibly good at grabbing data without very clear guidelines about where that data should come from. So, for example, it it'll try to do the job where if you ask it to build a model or repurpose it or restart a template and put in new data, you have you do have to upload source files. You do need to direct it. If you don't, you'll get some hallucinations that are actually kind of um that are actually a little like dangerous because the way it hallucinates is different from how a poor analyst hallucinates. Um extra zeros or well, it'll do, it's it's interesting, it'll do weird things where if if an analyst who you know, if an analyst makes a mistake in a model, a lot of times what that looks like is kind of predictable. You had a typo somewhere, and that changes the subtotals. Um there's maybe a conceptual error that's that, you know, again, we've kind of been habituated. Associates, VPs, MDs have been habituated to sort of notice where errors come from.
SPEAKER_02Yeah.
SPEAKER_01These errors are a lot more like, well, I'm gonna get the subtotal right, but I'm gonna sneak in a mistake to make the subtotal right. Okay. And it's just it's it's different, and it's gonna take a little bit of getting used to if you're auditing these kinds of things. But um, but broadly, that that's what it's good at. It's good at starting things.
SPEAKER_00Yeah, okay.
SPEAKER_01It's not so good at um finishing things, right? So when you start working with it and iterating, there's a whole bunch of issues that are still there that haven't been resolved. There's a certain point where you just say, okay, I've asked it, I've reprompted it 10 times to try to solve a whole bunch of things. It starts losing sight of the original context.
SPEAKER_00It starts Which I feel like it's like, I mean, I've I've experimented with plenty of just AI prompting in general, not just for Excel. And that that I feel like is a common feature of a lot of these tools, right? You say, Oh, what about the thing I told you six prompts ago? And then it says, Oh, yeah, good point. I forgot about that. Like, you're not, you're not supposed to forget your computer. That's right. So that's a big thing.
SPEAKER_01That's what sort of keeps this. This is by the way, an issue with code as well, and a whole bunch of other things that it does, that it's not that good yet at keeping track of all these things. It does. Claude, for example, if you're having conversations with it, will run out of um memory, for example, for its conversation. You've got to start a new one. And there's a whole bunch of the friction that's created in these in these tools that make it actually fairly unusable at a certain point if you ask too much of it. And by the way, it wants you to ask a ton. Like it pretends like it can do everything. It's not like, guys, this is too much. Please stop asking. Right, right.
SPEAKER_00Yeah. It's like, what do you want me to do next? And it's like, I want you to finish this correctly. So that's basically it.
SPEAKER_01That's it. And so it's quite tempting, I think, if you don't really understand where the boundaries are of its real capabilities, that you ask too much of it. Yeah. You then give up because it's failed you, and then you don't use it again. So there is a sort of a Goldilocks state where if you really know, and what's challenging about that is that these tools are changing all the time. So you have to know as of the moment, right? What are its like capabilities? If you sort of exist in that state and can prompt it and kind of start on your own, fork off on your own when the time is right, you can actually get a lot of productivity out of it. Um, if you ask too much, you will at some point kind of wipe your hands clean of it and say, you know, it's just much better for me to just do it myself.
SPEAKER_00No, I'm I'm just I'm thinking back to to my analyst. I mean, we were analysts, I guess, about the same time as in a long time ago, right? But even a long time ago, I feel like we had we had some tools that made things halfway productive. I'm thinking things like CapIQ and FacSet. And I remember, I remember building models when I was an analyst where you had a bunch of inputs that you could have cap IQ or facet refresh. You get your consensus EPS estimates, you know, your margin assumptions, the the main things, I mean, because there aren't necessarily that many assumptions that you need to build a functioning, say, three-statement model. So even 20 years ago, we had tools that would automate a lot of this process. I think from just thinking about the aspects of the job that are trickier and require a lot more thought, it's going through the the 10 Q's, the 10Ks, pulling out some exceptional items, like really going through and and sense checking, hey, can I use these these estimates that I'm pulling from fact set, or do I do I need to make some kind of adjustment to account for a one-off transaction, a business combination, whatever that case may be. Are these tools in any way, shape, or form okay at that kind of stuff?
SPEAKER_01They're okay at it.
SPEAKER_00Okay. Actually, yeah.
SPEAKER_01Okay, that that seems like a huge time saver. It is, yeah. So we we've been talking now about financial modeling and sort of that rote work, but you're you're right in sort of like elevating that there's there's actually a whole bunch of things in investment bank bankers do that's arguably more important and time consuming than the mechanical work. So I I think, and and that's just one example. Um so a huge part of the work is judgment um around what I need to pull out of documents, what's relevant, what's not. Um and actually these tools are pretty good at identifying that. And so um especially if you feed it, for example, documents and prompt and frame what you're looking for the right way, it'll it'll significantly increase if you're saying, hey, you know, I want to make sure that I've got, and I'll just give you a very simple example that should make sense to anyone that's sort of in in the finance world. I need to really figure out what is the company's um clean, normalized eBid dot. So look for any sort of adjustments in in this press release, look at this conference called transcript, and try to identify anything that might um might need to be pulled out. It'll be pretty good at that. It'll it'll find those things. And um, because it's not perfect, you still have this really important like function of the analyst to actually understand this really complicated um concept in in investment banking, which is like what is the core number around which these businesses are going to be valued on? Um and how do I find the cleanest EBITDA? And obviously, as those of um those of us who have been living and breathing some of this stuff, real EBITDA is always a moving target, and different constituencies have different motivations for that. So you need to really leverage, you can leverage these tools, um, but you need to understand the underlying concepts yourself because you're not good enough to just to do it on their own.
The Impact Will These Tools Have on IB Recruiting Pathways And What You Need To Be Successful
SPEAKER_00Well, and I think that that's probably a nice segue into the next topic, which is you know, kind of trying to think about how you think the analyst role is going to change, if if at all. So it feels to me like an important part of the analyst, the analyst skill set is you still have to know how to do all this stuff. You still have to know how to do it manually because ultimately you need to check all these figures, sign off on it. And as you're an analyst kind of moving up the up the org chart, you need to, you always need to know what the right, what the right methodology is for calculating all these for all these figures. So, but how how do you think this is changing both the analyst work today and also, you know, let's say, let's say you're a new grad coming out of school, you're thinking about a job in investment banking. What what impact do you think these tools are gonna have, if not today, in the next couple years, on your on your recruiting pathway, the skill set you need in order to be successful?
SPEAKER_01Yeah, that's the that's like the million-dollar question in this industry, and I suspect in every industry that um that is being that is being changed by AI. So so the way I would uh look at this and what I would what I would tell folks that are looking at at this industry is if there is no demand change, right? So in other words, if um if investment banks in 10 years did the exact same thing that they do now, in the sense it's the same number of deals that are out there, um the same kinds of opportunities, the same types of sort of capital raising opportunities that exist, then there is gonna be an encroachment of AI on the bottom of the pyramid because you're gonna have financial modeling work, um, you know, pitchbook work, email communication, all that sort of mechanical work is gonna get um much more productive by AI. That's almost inevitable in the next 10 years. That literally that's starting to happen. I I will caveat that by saying AI is not yet at a point, and none of these tools are yet at a point today, you know, as we said today's in March 2026. You cannot get rid of any analysts right now with AI and get um and actually get the same job done that you would have a month before. Yeah. There's the cautionary tales here, like you would have thought a year ago when um Klarna fired whatever 700 support folks and brought in AI and immediately rolled it back because they're like it's just not good enough. AI is not good enough today to do anything um that really replaces analyst. Now, so we're talking about the next 10 years. Yeah, and we don't know exactly when that lands, when it when it gets good enough to disrupt these workflows. I think if there was no change in demand, if it was all just we have the same static amount of demand of like what investment banks do, you will have basically a flattening of the pyramid, right? So the investment banking deal team structure is you have you know one MD, you have maybe a VP supporting it, maybe two, then you have three or four associates, and then you got a you know large armies of analysts that are supporting the deals with all the road work that has to get done. Inevitably, if we're if the demand side is bound, that will flatten. But that's a big if. My view is that the man the demand side of what investment banks do, you have to think about what who investment banks serve. Um I run a company. Wall Street Prep is now in the midst of two acquisitions. We have um we're switching over from um more let's call it startup y kinds of you know financial controls to an ERP system. And um, it's a real company. Um and we have a whole bunch of KPIs that we need to track in real time, and we have systems that we need to uh build up. Um AI, so this is the demand side. AI is going to improve all of that over the next 10 years, make it much simpler, make it much easier for a company like Wall Street Prep, it's been around for 22 years to have done that way earlier in its life cycle. Well, what does that do? Well, that makes a lot of companies much more transparent to capital. It makes companies much more capable of presenting themselves in a way that exposes them to capital markets in ways that um never existed before. Um on the demand side, there's a whole there's a whole world of product innovation that we haven't probably thought of yet, that exists but hasn't really scaled. And I think that is an inevitable sort of consequence of what's happening with AI. And so when you think about what your job is in investment banking and what's gonna happen, if you were thinking statically about, well, I've got one deal that I have to work on for the next several months, um, yeah, AI could probably reduce the number of analysts. But if you're thinking about I'm gonna serve eight deals and I'm going to have continuous advisory services to my clients because now that is available, I actually think we could see a complete sort of counterintuitive flip where we don't have enough analysts. Now, are those analysts going to be doing the same thing that an analyst in 2026 is doing? No. That role is gonna shift. You are gonna be doing much more associate-level work, judgment type work. Moving up the way, for example, a pilot has moved up where they're no longer making manual calculations about what's going on. They're looking at their controls. So I think the industry is gonna shift. I think this is gonna be a very healthy industry because I don't actually believe the demand side is not going to, I actually think it's gonna surpass the supply productivity for the next 10 years.
SPEAKER_00You know, it's interesting to think that. I mean, because I I was in the startup world for a little bit and I think about when when I was doing that, say, you know, five, five, six, seven years ago, none of these tools existed, right? So you are you're capital constrained, you're resource constrained, you can't, you can't do necessarily as much as you want to. Think about if you're if you're starting a new business today with all of the all the tools you have at your disposal to really, really help make your life easier. To your to your point, once you once you reach some scale, really reach that professionalization mark a little bit earlier. It's really interesting to think about how that that demands, that demand increase on potential investment banking services, just because you've got more companies reaching that threshold a little bit earlier, is actually gonna be a real a real game changer for this industry overall. Now, do we think, do we think, I mean, I guess we're this is more on the topic of what investment banking might become? Do we think a lot of the big banks are gonna start moving down market and servicing more mid-market clients just because this is this is gonna be a new a new source of deal flow? Do you think we're gonna have sort of new new startup mid-market, more lower mid-market investment banking shops pop up? Like, how do you think that overall landscape is gonna change?
SPEAKER_01Yeah, so now we're we're sort of getting into the, I mean, I guess we've been prognosticating for the last several minutes, but like uh I think so. I I think it's it is inevitable that banks, um, the banks get the build up the capability through these AI productivity enhancements to go down market. And and you know, it's just not profitable right now for a bulge bracket investment bank to go after uh$20 million EBITDA businesses. Yeah, it's not profitable for middle market investment banks to go after sub-20 million dollar EBITDA businesses. That all changes. I think it's inevitable that the minimum viable like deal size starts shrinking down. And if you look at talking about a pyramid, you've got you know massive amounts of companies representing massive amounts of uh revenue and deal fees. Um, and again, I'm just talking about advisory. There's also capital raising. There's there's debt and equity and all the securitization that can happen when you have so much more um transparency at that bottom that bottom rung of businesses that in in aggregate. Represent much more opportunity than the business is currently being served by capital.
Are Investment Banks Replacing Analysts With Technology
SPEAKER_00Yeah, it's actually it's I think it's really fascinating just to think about how how this market might get a little bit more exciting in the sense that you've got more companies having access to capital markets, more companies that can be represented by investment banking services. I think it's a in some ways, it's actually to think five, ten years down the line, it's kind of an interesting, exciting time that you can that you can kind of imagine. But I do think we're still gonna be in this in this world where if you look at the way investment banks are structured, we're probably gonna see shifts in terms of some analyst jobs being, you know, maybe being replaced with some technology. I only say this because I'm thinking about my experience. So I started at Lehman Brothers back in the day. And I remember I, so I started in LA, I moved to London, and at that point, I want to say in 2006, Lehman was building up an offshore analyst program, in essence. And they were looking, I didn't put my hand up because I just moved to London and I'm like, no, I want to stay here for a little bit. But they were looking for people to to move abroad and lead a team of offshore analysts to start, to start doing some of the work that was seen as some of the most basic in terms of the modeling. So pulling the data together, you know, all the stuff that, you know, in theory you can you can ship offshore. I can see that, I can see that kind of stuff being replaced with with AI or investment banks wanting to wanting to replace some of those roles with technology. It feels like it feels like that maybe has started to happen already. If not is soon, you probably have a better view, better view on this just knowing knowing more of the banks. So so it's interesting.
SPEAKER_01Around that same time, yeah, we we were also seeing it. You have like BPOs uh companies abroad like spreading comps and doing all kinds of work. Yeah. Um, because CapIQ made that much easier and and um and it is there's a lot of road work. Um I do think that that happens kind of at a at a at a low at a low simmer and has been happening at a low simmer for 20 years. The I do anticipate that AI will actually make that you know even even more pronounced. But I will say back in 2006 when they were doing, when they were really experimenting with that, a lot of businesses similar to the Klarna example, like kind of scale back. They're like, this isn't working. That's not to say that it never works. There are there there is work product that has been done really well by the BPOs and uh with the outsource model, but um but it hasn't worked as well as back in 2006, people were expecting it to work, which is an interesting um, which is an interesting point. I I would say that we you know the what's now a cliche that you hear over the last couple of years, which is AI won't take your job, but uh, you know, someone who knows how to use AI will take your job, is I think you originally asked the question of like what what advice or how do you how do you talk to future you know analysts or prospective analysts? I do think that in the in the near term, and the near term is the next several years, right? It's not it's not the next several months.
SPEAKER_00Yeah, well the the the time frames do seem to be compressing, right? Because we're talking about difference between 2006 and 2026 now. I don't think we can continue to look out another 20 years, right? I think you're right, not a few months, but a few years, things could look a little bit different or materially different even.
SPEAKER_01Yeah, I mean I think what's gonna be materially everything is gonna be materially different in terms of the work product, even as early as like a year from now, because I think again that the tools are good. But in terms of how how the work will be um the work product in investment banking, if I'm a if I'm a betting man, um does not look materially different in a year. Because um they're just not good enough yet. Even as good as they are, they're not good enough yet. I think they probably and and here's the other thing that that happens adoption at banks is actually fairly um is actually fairly challenging to um to build up. So Copilot, for example, has a massive advantage of banks. It may not be the best tool right now, arguably is actually the worst tool. But that's the one that banks have piloted first, that's the one they've deployed first, that's the one that can handle material and not public information, that could sort of create the guardrails that are needed.
What AI Tools Are Investment Banks Using (Claude, CoPilot, GPT)
SPEAKER_00Is that just because it's bundled with Microsoft Office and it's a it's a it's a well-understood product?
What You Need To Do As A Future Investment Banker
SPEAKER_01It's got a massive mode around it that none of these other tools have. So um, so there are time lags around like deployment of these tools, there are limitations on what the state of the art is. And and and while Copilot will catch up, I mean, since we did our evaluation of the modeling tools like ChatGPT caught up, you know, we had Claude significantly ahead of ChatGPT. We had other uh another tool called Shortcut, which is a smaller uh platform. But again, these tools are much more difficult to get into the banks. Um copilot's got a massive lead. So that these things take time. These things take time, and then people need training on how to use them. And so it goes back to the point of you know, if you are if you are really good at using these tools right now, that is the that's the that's the real capability that will set you apart. So if you're going into an interview um right now for investment banking, and you have demonstrated a real aptitude for and a real like interest and passion for these tools, that's actually really, really important. Because there is no tool today that gets the job done. It's actually the tools of tomorrow. And what most employers, and this isn't just investment banking, this is this is, I think, most employers across every industry that that has the the potential to be uh more productive from this, is you're looking for people who are really into it. And it's really hard to just keep up with everything. Yeah. Time consuming. It's actually crazy making to just keep keep you know, to keep track of what's happening. So the people that are doing that and really get into it, those people have significant advantages in the market now.
SPEAKER_00And I imagine you have to, you have to, I I would think you have to have both, right? You have to have an interest in all these tools. When I say both, the interest, but you also still really need to know how to fundamentally do the job, right? Because I uh who I don't remember who was saying this or if this is kind of a general, general theme kind of going around right now, but I if you've read about uh some research suggesting that this the young the young generation now, like kids being born today, is gonna be the first generation that, for lack of a better word, is dumber than their parents because they rely on AI for everything, right? You if you're going into a job in investment banking where being accurate, being right is paramount, you still need to know, you need to know what the tool itself is doing. Right. So you gotta have you got to have the interest, I think, in the tool, but you also need to make sure that what it's spitting out is right. Because I'm just thinking about, I mean, we we talked on a previous episode about Warner Bros. uh Warner Brothers, Netflix, Paramount Skydance, that whole that whole acquisition. You got some of these investment banks who put fairness opinions together, which is you can almost make an argument just kind of spreading comps, right? Just making sure do we have the right comp set? Are we doing this correctly? You're getting paid a ton of money. Like the fees going around were like$90 million for a fairness opinion, right? The most important thing in that is that you're right. And in order to be right, you gotta know, you gotta know what these tools are doing. Like, can you imagine a world in which that fairness opinion came out and it was Claude's Claude's Excel tool that had run the comps and everyone said, yeah, okay, like this is good. Like, like let's print it and go.
Why You Still Need Fundamental Financial Knowledge
SPEAKER_01Yeah, so I think that that's that is the point. That's the most profound point to make, which is as long as humans are in the picture, right? Yeah. As long as humans are in the picture, um, in terms of making the decision about whether we we want to sell our company or we want to buy a company or whether we want to raise capital or not, as long as those decisions are made by humans, that trickles down to the service providers and those that deliver that, those are the investment banks. Analysts now have a much taller task, which is they not only need to know how these tools work, but they they actually have to also keep track of, and in a way, it's actually harder to keep track of the underlying basic concepts. So, in the same way, I'll go back to the the pilot example. If you're a pilot today and you're just relying on your controls to fly the plane, um you actually have to stay sharper on how to fly a plane because that you don't you're not like flying it all the time.
SPEAKER_00Yeah, you're not you're not doing it all the time. Yeah, yeah.
SPEAKER_01And so and if you don't do that, um you're not going to be able to understand or work with just now going back to the AI example, you're not going to be able to get good work product out of it. So it in a way, it there's an analogy here, which is when I started Wall Street Prep, I thought I knew accounting and I thought I knew financial modeling. I'd spent you know four years at JP Morgan and and and I was doing it day and night working 100-hour weeks as you were. And we all we all know how difficult that is and how how smart you feel when you're done. I really know this stuff. Yeah, yeah. I'm the best. Well, well, then what I the the humility came when I had to deliver my first accounting training program at a bank, and I was like, I don't think I know it to the level that I thought I did. And that came with having to teach it. So teaching is actually a well-known way to learn and identify the gaps that you have in your knowledge. Um, the analogy here is that in order to spot and use AI really effectively, you actually have to really understand the underlying concepts. There's a massive risk of like atrophy or lack of development that you're alluding to. Um, and that's that is the message to people who are trying to break in. You know, if you want to work with AI and you want to get really good at it, you build a model from scratch. Let's just go back to the modeling example. Build that model from scratch, even though you're not gonna have to do that on the job all the time. The lessons there are massive. And then compare it to what AI have AI build that same model from scratch, right? That's a new learning framework. And then you're getting both the reps of how to do it from scratch, and then you're getting the reps of, okay, well, where is AI messing up? Where am I messing up? And you start cross-reference. That's a great way to think about this. So now you have to do two things, whereas before you have to do one. Yeah. Um, that is that is a huge part of the risk that we just get dumber and dumber. Um, we rely on these tools, and and that's you know, that's a huge part of what a training organization has to be on top of. Right. It's um, I think the clients we work with are hyper focused on that issue. That you are, you know, we are we have this great co-pilot, um, and I mean all those tools, not just Microsoft Copilot, now in our hands, but we are we cannot fall asleep literally at the at the at the switch because um this thing is not ready to work without us. Right.
The Dangerous Temptation Of AI Tools & The Wrong Way To Break Into The Industry
SPEAKER_00Yeah. No, I think it's it's great advice. I mean, and also I actually I think about a lot of the a lot of the training and teaching I do, you know, one of the things I like to do is I do a lot of LBO stuff, right? Because I I worked in in you know credit investing, but in particular backing LBOs for for basically a decade. And one of my favorite teaching tools to use there is a short form from scratch LBO model. It doesn't have all the bells and whistles. We kind of go through and we build it together, give the class assumptions and say, okay, here's like here are our sources and uses. Let's talk about where everything comes from, let's build a full cash flow debt schedule, all the stuff. But you're building it from scratch. So you know, you know how it gets pulled together. And I think that's a really useful exercise to go through anytime you're you're kind of looking to study for an interview, like learn, learn something new, like actually going through that basic exercise, way more valuable, I think, than taking a big template put that's put together and getting Claude or Chat GPT to help you fill it out. Like that's not really going to teach you the core, the core fundamental concept of what's actually going on. 100%.
SPEAKER_01And it's so tempting to do do it the uh the opposite way. It's so tempting to just have Claude to just kind of submit to to the tool. And um and it's and those That's what it wants you to do. That's what it wants you to do, and and it's not ready, it's not ready to take over yet, but it wants you to submit. And exactly, and it's not uh it's not the right way to to um to build a career right now. Um so that discipline, you know, for especially for younger people who are you know trying to break into the industry, it's it's this interesting dynamic where I your point, there's so many amazing things happening right now. There's so much career opportunity, um, but it's a it's a much more you you need a lot of discipline. It's it's almost equivalent to like, you know, you know, don't don't go on TikTok or Instagram and waste your brand. Spend the time um to do the the work that'll you know take your career to the next level. And that really is now the double the work. It's I gotta know the underlying concepts and I have to understand how these tools work.
Which Divisions Are Adopting AI
SPEAKER_00Yeah. No, so we've been we've been talking a lot about how, in some ways, actually, the analyst role is probably relatively protected to some extent, at least over the next few years, right? It's it's gonna change, you're gonna be using these tools, but we're still gonna need investment banking analysts. You still need to know how to model and do all the all the technical stuff. What about other areas of finance or other roles within banks? Like, do we think there are other other kinds of business units or business lines? I can even think about, you know, maybe some investing roles where you're investing just on purely market technicals and fundamentals, where you think, hey, actually, maybe, maybe Claude, you know, GPT, you know, whatever, it could could do a lot of that job pretty well. If not today, then then not too far from now. For sure.
SPEAKER_01So interesting. The what we're getting out of our clients now in terms of level of engagement, the investment banking divisions are actually getting the most adoption, the most engagement out of a lot of the other divisions. Um, that said, there's a whole sort of buy-side world and um an investing space where the same disruption is happening. So I was, you know, I was in investment banking in the MA group at JP Morgan for a couple years, and then I moved over to Cell Side Equity Research Group, and I covered food and drug. And you know, we covered 10 companies. And we didn't cover 10 companies because there were only 10 companies to cover. We covered only 10 companies because that's that's the most you could cover given how much time it takes to maintain the model and um have the conversations within with buy-side investors and to put out the notes every, you know, every time something material happens and ingest all this information. So it goes back to supply and demand, right? Same, it's the same, it's the same opportunity, challenge, disruption. Um, there's a whole world, there's a whole coverage universe of companies that exist today that could expand dramatically. Yeah. You could do a lot more than you could before with these AI tools. And again, when I say you could, I'm I'm speaking present tense, but in reality, it's actually, I suspect that you will be able to. You're you're already kind of able to do more, uh, but over the next several years, you'll certainly certainly be able to do more. And again, without being overly creative, you just have to think about the the existing limits on how much analysis you can do and realize, oh wow. Um, these tools can absolutely maintain and track um portfolios and and companies and ingest uh changes and improve the model, um, put out the notes and have you just take a look at it as an as an um as an overseer as opposed to as opposed to the the originator of the content. So it's the same thing uh to me. Yeah these are huge opportunities to improve the demand side of it as as well as take advantage of the supply. But you have to, again, to your to your point, if you as a as an investor, as an investment analyst, are unable to understand the underlying issues, uh these these tools don't really serve a purpose. You you can't do anything with them.
What AI Can't Do
SPEAKER_00No, if anything, it's quite it's quite the opposite, because you you will just at that point you'll take the output from whatever tool you're using, assume that is correct and run with it, and then a few days, months, years down the line, learn that there was some some mess up in there you didn't know about, and all of a sudden you've got a really big problem. Yeah, and I uh that's exactly right.
SPEAKER_01And I'll just use again my own experience on the cell side. Like you have, you know, if you cover CVS, CVS was a standalone, basically a pure drug retailer um back then when I was covering it. Right now it's a it's a giant business with a whole bunch of other healthcare businesses uh attached to it. But back then it was a pure drug retailer. Um if you look at that company, which is was a large company back then, even not as big as today, but was large, was covered by 15 investment banks. Right. Um and they all had different views on that. It's you know, the the there are some folks that thought it was a buy, some folks that thought it was a screaming sell, and those are all like valuable insights to to the buy side community. Yeah. AI doesn't just converge to one. I mean the the issue here is that even in that example, if you asked AI to tell you whether CVS is a buy or a sell, um it won't really converge it today, it won't really converge to an answer. Depending on your perspective on what's important, what's not important, um, you know, your AI will come to different conclusions. Um and I think the the benefit here is you're just gonna be able to do more of your own um, you know, what makes you as an analyst um unique and thoughtful, you'll just be able to scale that to a lot of different businesses.
SPEAKER_00Yeah, and you know, maybe maybe that means over time that there aren't as many roles or seats available in certain business lines because because people are more productive, right? Instead of covering 10 companies, you're covering 50, right? Just because you all you're at that point, you're you're reviewing the output, making sure it makes sense. Maybe you've even been the one to train the model and teach it your firm's specific perspective on on life. So can you can you get a lot more out of the same of the same analyst? Like quite quite possibly.
SPEAKER_01As long as that analyst knows what's going on. Right.
SPEAKER_00That's the key. So what from your perspective, if we think about the overall kind of finance, finance universe, what do you have a view on what jobs you think are gonna be safest? Say, let's say, let's say five years out, because I don't think anyone the the interesting thing about being in the world right now is if you're asked to make a prediction beyond five years, I think it's kind of I think it's kind of tricky just given the pace of change of all this stuff, right? So, I mean, big picture, you can probably say, okay, investment banks are gonna continue to be around. We'll have we'll have people at all the different levels, like all the all the big picture stuff might be relatively consistent. But with the next five years, what do you think are the the safest spots? And which ones do you think are potentially the most likely, not necessarily to go away, but the most likely to you know be be more consolidated and have instead of that 10, 10 companies per analyst be 50 companies per analyst? You just don't need as many people.
Are Roles Under Threat & How Do You Future Proof Yourself
SPEAKER_01So I think to your point, it's a really hard question to answer. I think the the easier so I'll take the easier question. I'll make up my own question and I'll answer it. What is the skill set that you're gonna need when you're looking for work? Um and how is that gonna change? And I think because these tools, I think for the next five years, are going to get really, really good at specific workflows, um they will be, I suspect they will still be limited by um the ability to uh solve problems end to end. They won't have they won't be as good of an integrator as um a human will be. And so what that elevates is judgment, the ability to see the big picture, the ability to sort of uh orchestrate all of these tools together. Um and so that spans across industries. So any task that today, any job function, and any role that is really rote and mechanical, obviously, is going to shift. I don't even think it's about you know, will that job go away? I think that job will evolve, right? So if an investment banking, again, just going back to our our audience, if an investment banking analyst today is spending most of their time you know building models, putting together pitch books, um I don't think that job's going away. I just think it's gonna be Different. I think that that person will be able to produce a lot more of that with these tools, but then they will their their main job will shift to what an associate essentially does today. Yeah. At a much higher volume. So I'm now looking at again 10 transactions. I'm looking at 10 different opportunities. I am making judgments. I am I'm telling you, I'm telling my AI tools what to do. And so that skill set is becomes the job. It's different. It's a lot of it's a lot of what you you end up focusing on through reps over the first two years currently of the analyst job. And that's going to have to just get really uh accelerated and honed in on earlier and earlier.
SPEAKER_00And you know, I think if I were if I were graduating now and thinking about becoming investment banking analyst again, there's a world in which I actually think it you can you can see AI making this job a bit more exciting and a bit more fun. Like think about how we used to spend a lot of our time in those hundred-plus hour work weeks. It's in PowerPoint, making sure everything is lined up perfectly, a lot of manual formatting on bar charts, making sure the the you know the waterfall chart is formatted perfectly. If you can just say, you know, hey Claude, can you make this page look pretty? Actually, I had a one of the one of the first things one of the I don't know VPs said at Lehman in LA was can you just alt MP this, like alt make pretty. And I think I think we're probably we're probably getting pretty close, maybe, with some of those tools, right? And that that does free up your time to do some of the more high-level interesting stuff. So actually, I actually think there's a world in which being an Alice today is probably a bit more fun than it was when we were doing it.
Will Work In The Future Become More Interesting
SPEAKER_01Without question. I think to your point, hundred-hour work weeks where you're you're two o'clock in the morning, you are lining up images and are like, you know, worried that there's gonna be a mistake, so you gotta reprint the books. Yep. Like there's those of us who have been there know there is nothing more soul crushing than that experience. Makes you question. What are you talking about?
SPEAKER_00I loved it. I loved it. We all loved it.
Advice for Analysts & Future Investment Bankers
SPEAKER_01We all loved it. But um, but that's exactly right. There's a there's a there's a world where, first of all, the work days are not a hundred, uh the work weeks are not a hundred hours, but they're 60 hours. Yeah, with the big difference. It's a big difference. Yeah. And the job is so much more interesting. Right right now, the model is you build expertise through just model construction and rote formatting and rote work, and you just sort of through osmosis and those reps eventually let things sink in. There's there's a world in which AI just just really accelerates the process through which you can now do really interesting things much more quickly. Like those, those like little moments where you're like, oh, I got invited to the pitch, and I'm listening to how the management team is thinking about this. And you, those are the best moments because you get to really experience that. Those can be a huge part of the job. Yeah. Yeah, absolutely. And so it it there is a world in which this is this is a renaissance for um junior finance roles as opposed to some doomsday nuclear you know catastrophe.
SPEAKER_00All right. Well, I think we're we're almost out of time. Any any final parting comments to anyone, again, anyone who is either in the analyst seat right now or is about to start looking. Exciting times.
SPEAKER_01Embrace the change. Um just live in these tools. Don't forget the the vegetables of actually how you know, eat your vegetables. Um do Wall Street prep modeling courses. Do Wall Street Prep modeling courses. Um But there are some really exciting, you know, it's what's the old what's the old saying? May you live in interesting times. We are certainly living in interesting times. They are indeed. Um more interesting than any in our lifetime. So if you're starting out, congratulations. You're in the most interesting times in a long time. Enjoy it, uh, embrace it, and I think anyone that does that will have an incredible career right now.
SPEAKER_00Yeah. Awesome. Well, look, I'm sure more to come on AI in the future. Obviously, this is a very quickly evolving topic. In a year, this could this whole conversation be, could be completely wildly out of date. So I'm sure we'll come back and we'll come back and refresh the thinking. But until then, everyone, good if you're if you're out looking for looking for a role, good luck in the in the hunt. Uh and yeah, do all your do all your Wall Street prep modeling and training courses to to get ready.
SPEAKER_02All right.
SPEAKER_00Awesome. Laton, thanks so much. It's been it's been great. And everyone, we'll see you for next week episode of What's the Big Deal? Until then, take care.