Build INSANE Financial Models With This AI Tool

What if I told you there's an AI tool specifically for corporate roles like consulting, banking, or private equity?

It's called Traide, and it can convert unforatted sheets to corporate style layouts in seconds. Build an entire discounted cash flow from scratch and so

much more. To test how well it works,

much more. To test how well it works, we'll go over five different levels of real world examples from easy to hard.

And thanks to Traceite for sponsoring this video. Let's get into it. First of

this video. Let's get into it. First of

all, to install Trace Light, it works as an addin in Excel. So, you can see I have it right here on the right hand side. You just need to head over to

side. You just need to head over to addins and in here under more addins, you want to look for Trace Light.

It's this one right here. And you can actually install it for free. Starting

with level one. And we're going to test how well it can format data. Over here,

you can see I have an Excel file with a discounted cash flow valuation, but it's got zero formatting. For the headers, we would maybe like them to be in a blue color. Then we go over to the numbers,

color. Then we go over to the numbers, and these two that are percentages should be in percentage format. These

bigger numbers over here should have a comma separator for the thousands. And

also get rid of those decimal places as they're not very useful. So I'm going to click on trace light and get started.

Under this paste area in here, I'm going to paste my instructions. So I'm saying to format this financial model with the following rules. For the percentages, I

following rules. For the percentages, I want it in percentage format with two decimal places. And bigger numbers, I

decimal places. And bigger numbers, I want zero decimals and a comma separator for the thousands for multiples. So down

below, like the EV over EBIDA, I'd like that to have an X in the end. And once

we're ready, we can just go ahead and send this. Awesome. You can see the

send this. Awesome. You can see the final results here. Up top, we have the headers for each of the sections. We've

also got the borders. We've got it in bold when it's a total. And when we look at the actual numbers, these are in percentages. These here have the comma

percentages. These here have the comma separators. And when we go lower down,

separators. And when we go lower down, you'll notice the multiple also has the X. So that's looking great. For a prompt

X. So that's looking great. For a prompt like this, you're actually likely to use it again in the future when you need to format a new sheet. And actually, you can save it as a template. Let me

quickly show you. You just need to press on this insert a workflow button and then go to create workflow. So here's

where you would type the name of it. And

down below you would add the prompt. As

you can see in this case, we have a sample for building an LBO model and just create it. So whenever you want to format the sheet, you already have that as a template. That's a promising start.

And now let's go over level two with a harder example on scenario analysis. As

you can see over here, I have some assumptions. I've got a best case, a

assumptions. I've got a best case, a base case, and a worst case. When we

look at the actual growth rates here, like the monthly recurring revenue, it's obviously much higher in the best case compared to the worst case. And lower

down under the cost, we have a similar concept where the cost of goods sold are much lower for the best than they are for the worst case. So, what I want to do is ask it to create three different

scenarios of an income statement under the best case, the base case, and the worst case. So, let me ask it over to

worst case. So, let me ask it over to the side. Here's the prompt for it. I'm

the side. Here's the prompt for it. I'm

asking to build a 12-month income statement under all three scenarios. And

as the requirements, I'm reiterating that first step. And I want to also have some kind of a drop-down or a way to dynamically switch between the different scenarios. I also want all of the parts

scenarios. I also want all of the parts of the P&L to update automatically whenever that drop-down or toggle is switched. And finally, I want it to be

switched. And finally, I want it to be nicely structured so it's clear what's what. Now, let's go ahead and send this.

what. Now, let's go ahead and send this.

Awesome. It looks like it's finished.

It's created a new sheet for it. And

let's see what it's done. First, it's

got a scenario selector up top. Then

down below, it's got some of the assumptions that we gave it. And if we scroll lower down, we have the actual income statement where we have the breakdown in terms of revenue. We've got

the gross profit, the IBIDA, and finally the net income at the end alongside with a summary of the key metrics. And this

is for a total of 12 months. That's

looking quite good. Let me close out of trace light and see if it works with different scenarios. So instead of a

different scenarios. So instead of a base case, let me change this to a best case. You'll notice that growth rate

case. You'll notice that growth rate just updated and all of our numbers should update accordingly. Let me check here. It's 12,700.

here. It's 12,700.

And if I go ahead and put like the worst case in here, you'll notice that net income figure updates, but it's not using that drop down. So to add that, we can just go over to data and look for

data validation. Within this we want to

data validation. Within this we want to select a list and that list should have three values. The best case, the base

three values. The best case, the base case and the worst case. Press on okay.

And now I have this dropdown. So I can choose the best case and you'll notice how the numbers update. Same thing with the base case. And finally with the worst case the net income figure should

be the lowest. Moving up to level three.

And here we have a cohort analysis which is very common to track consumer behavior. So typically it might be a

behavior. So typically it might be a company in e-commerce. It might be a venture capital fund trying to assess a business. So overall it is a very common

business. So overall it is a very common type of model and you can see I have some assumptions for it. We've got an initial number of customers of a,000.

We've got a customer growth this is on a month-to-month basis of 8%. The average

revenue by customer we're assuming is just 50. And the kak which stands for

just 50. And the kak which stands for the customer acquisition cost at $75.

And down below we have some assumptions over 12 months on the retention rate. So

we're saying in month zero obviously all our customers is when they purchase and then from there they might start to use this particular tool less and less hence why they'll unsubscribe. So we can now

open up trace light and simply ask it to build a cohort analysis based on these assumptions. We'll keep the prompt

assumptions. We'll keep the prompt fairly vague. So let's see how well it's

fairly vague. So let's see how well it's able to perform under that kind of prompt. Awesome. Here's what it's been

prompt. Awesome. Here's what it's been able to come up with. And you'll notice actually for the formatting, it's actually using the exact same format as the assumptions that I gave it. So,

that's a nice detail where it's able to read what's already in the model and base that on the answers. If we look at the actual figures, let me double click here to have a better look. You'll

notice it's using the round function.

So, that's definitely a best practice.

After all, we can't have half a customer, right? Then we go lower down

customer, right? Then we go lower down towards the revenue area. Let me double click on this figure right here. It's

using the dollar signs. In this case, it's for the average revenue by customer. That makes sense. You don't

customer. That makes sense. You don't

want that cell to be moving around. And

for the number of customers, that part isn't fixed. So, we can move it around.

isn't fixed. So, we can move it around.

So, it's definitely using the best practice. And if we keep going lower

practice. And if we keep going lower down, we have some of the important metrics like the lifetime value over customer acquisition cost ratio. And

this is up 5.4 times. That means that for every dollar you spend on customer acquisition, you get back 5.4. In terms

of personal preference, maybe the only thing is that I would like to add a border, not just on the numbers, but also on the actual column cell in this case for the total revenue. But again,

that's just personal preference.

Awesome. Now, moving up to level four.

And here we're going to test how well it imports data from the internet. In this

scenario, I have the 10K for Nike or annual report. And as you can see, it's

annual report. And as you can see, it's about 100 pages long. And from here, we're really only looking for the three main financial statements. So, the

income statement, balance sheet, and the cash flow statement. So, we wanted to ignore all of this other stuff and only take those. Let's hop to Excel. And here

take those. Let's hop to Excel. And here

under Trace Light, what I'm going to do is upload the file simply by attaching it. As you can see, I have the Nike 10K

it. As you can see, I have the Nike 10K PDF in here. And based on that, I'm just going to ask it for the three main financial statements. Let's send that.

financial statements. Let's send that.

and see how well it does. Awesome. So,

you can see it has the cash flow statement, it's got the balance sheet, and it's got the income statement. And

we'll check the data in a second. And

it's even asking me if I want to save this as a workflow in case I want to use this prompt in the future. Let me close out of that. And you can see it's formatted it nicely with the same blue

that I've been using for the rest of this Excel file for all three statements. It's also added some borders

statements. It's also added some borders for the totals, too. And to look at the numbers for the income statement, it's

3219 for 2025. And over here on Nike's 10K PDF file, it's 3219 for 2025. So

that's all looking correct. If I dig a bit deeper into the data, you'll see that it's actually using formulas. So

that's definitely a best practice for any kind of calculation that applies for anywhere where there's some kind of a total or a subtraction. Also, up top,

you'll notice that it's using Nike. It's

detected that this is the company that it's importing the data from. Now, every

AI tool does have some limitations and that's the case with Trace Light 2 and we're going to look at them in a second.

But first, let's go over our hardest example today, which is only discounted cash flow. Here you can see that I have

cash flow. Here you can see that I have a very large model that I have some data source. So basically where the data is

source. So basically where the data is originally coming from and then I have some calculations that I've made all the way to the unlevered free cash flow.

Based off of this I wanted to actually create a discounted cash flow to calculate not just the enterprise value but also the equity value and even the implied share price. So I'm going to

head over to trace light and as the prompt in here I'm going to say based on the information in this file create a DC valuation with the enterprise value equity value implied share price and

also do a sensitivity table with the walk and the growth rate and assume a perpetuity rate of 3%. Let's go ahead and send that and see what it's able to come up with. With this, we can test how

well it works at reading data, not just for one specific worksheet, but for multiple. Awesome. It looks like it's

multiple. Awesome. It looks like it's now complete. Let me close out of this

now complete. Let me close out of this part on the side. And if I scroll lower down, you'll notice we now have a whole DCS section. It formatted it like the

DCS section. It formatted it like the rest of the model. So, that's really nice. Maybe here it's just missed the

nice. Maybe here it's just missed the bottom border. And same thing over with

bottom border. And same thing over with the implied share price. That said, it is fairly minimal. And we've got the present value of the unlevered free cash flows. the present value of the terminal

flows. the present value of the terminal value and the bridge going from enterprise value to equity value. It's

also got the sensitivity table over on the side for the formatting here. Maybe

it's missed a little bit in terms of having the bottom border all the way across. One thing that I wanted to check

across. One thing that I wanted to check here is for this particular number under the income statement, you'll notice that it's divided by a,000 and that's the correct way to do it because if we have

a look here, the shares here are in thousands. That's what it says up top.

thousands. That's what it says up top.

shares in thousands, dollars in millions. So, it's gone ahead and

millions. So, it's gone ahead and detected that and been able to make the change to divide it by a th00and, which is definitely very impressive. Had it

not done that, you'll notice that the share price is extremely low, which would have been incorrect. All right, so what are the limitations of Trace Light?

Well, the first one is that when it comes to creating things like dashboards and very complex charts and visuals, that's probably not its strongest point, and there are better tools for that out

there. Secondly, and kind of relating to

there. Secondly, and kind of relating to the first point, this isn't a generalist tool. Instead, it's specifically focused

tool. Instead, it's specifically focused for corporate roles like those in consulting or finance. So, it is very good and very fast at that, but not when you give it more generalist tasks. In

this bonus section, I want to go over some other features that if you've been watching this video, you might have noticed exist. These are the audit and

noticed exist. These are the audit and the trace that we've got over on the side. So, for the audit, this is great

side. So, for the audit, this is great if you want to spot any errors in a financial model. So, for instance, let

financial model. So, for instance, let me go ahead in here. You'll notice that this figure or the selling general administrative is just multiplying the revenue by the SGNA percentage of

revenue. Let me actually delete that

revenue. Let me actually delete that second part and just put a 10% in here to see if it's able to detect that.

Obviously, this would be considered an error as it's using a linkage all the way till here except in this next cell is just using that 10%. So, I'm going to select it for this particular worksheet

and just ask to run it. And just like that, it's saying it's already noticed an error with a high severity and that's specifically the one that I just made on purpose. So that's looking very

purpose. So that's looking very promising. If we click on this trace

promising. If we click on this trace feature, it takes us to the next part we haven't seen yet. So I'm just going to go ahead and click on that. Basically,

this explains what the formula is, where it's linking to. And down below, we have a full written explanation of what it's actually doing. It doesn't just work on

actually doing. It doesn't just work on the formula that you have an error, though. You can go to any other cell and

though. You can go to any other cell and just get that explanation for it instead by refreshing. Given these results, it's

by refreshing. Given these results, it's not surprising Trace Light is already working with six of the top 10 largest consulting firms in the world. So, if

you want to try it out completely for free, head over to the link in the description below. To learn how to make

description below. To learn how to make more advanced charts and visuals in Excel, watch this video over here. Or

you can also take our AI for business and finance course over here. Hit the

like and the subscribe and I'll catch you in the next