Financial spreading involves translating a borrower's financial statements into a standardized format that banks and credit unions can easily analyze. This process helps in assessing a customer's financial health and making informed lending decisions.
Financial analysis is crucial for making informed credit decisions as it offers deep insights into a borrower's financial stability, risk level, and repayment capacity. It enables lenders to evaluate the potential risks and benefits associated with extending credit to individuals or businesses.
Banks can overcome these challenges by investing in robust financial analysis software that offers data traceability from the source to the final spread. They should also consider training staff on data management best practices, and staying informed about regulatory changes and industry trends.
Technology plays a pivotal role in financial data analysis by providing advanced tools for data collection, processing, and analysis. It enhances the efficiency, accuracy, and speed of financial analysis, enabling banks to make more informed decisions faster. Financial analysis software should trace data from the source to the final spread, allowing you to understand the decisions you've made and why you made them.
Effective financial analysis significantly impacts a bank’s lending decisions by providing a detailed assessment of risk and financial stability. It ensures that lending decisions are based on sound financial reasoning, thereby reducing the likelihood of default and enhancing loan performance.
Mitch: Welcome to today's episode of Lending Made Easy today. I'm joined once again by Bryan Peckinpaugh and David Catalano. We're going to talk about a topic. That's really the foundation of sound credit decisions, effective financial analysis. So Bryan, I'm thinking back even to our recent conversation, or we were having with a client talking about how so many institutions have really combined this idea of statement spreading with financial analysis, statement spreading.
Really just the starting point for conducting financial analysis. And it's almost like they've started to look at them at the same thing. You know, they're saying the spread could take six hours, but the reality is that spreads probably taking 15 minutes. And the financial analysis is taking the other five hours and 45 minutes, that six hour chunk.
So Bryan, David, I really wanted to talk today about this idea and unpack it a little bit more. Why is differentiating between spreading and financial analysis important for a commercial lender? So I'll toss that question up for whoever wants to take it.
Bryan: That client I know listens to this podcast, Mitch. So, Mike Geralds, if anybody out there ever wants to really get into a deep conversation about the five C's of credit and how a bank should operate as it thinks about sound credit decisions. He's a great one to reach out to in Montecito, California.
But yeah, Mitch, you're spot on. And a lot of this has just been evolution of how spreading has happened. Over the decades, even going back to when people did this with legitimately paper and pencil and you were, looking at , the financial statements and you're working out on a piece of paper, how you think about the numbers that you're seeing?
Like, what are these numbers telling me? And by nature in that arena, what was happening is you were quote, unquote, spreading. And analyzing the numbers at the same time. And you had to, because we weren't thinking about standardization of data. We weren't thinking about entering it into a system that can allow me to look at it year over year, right?
What we were doing is we were trying to come up with what those numbers tell me. What is this set of data? Illustrating about the health of the business that I'm looking at now as we started to bring in tools and shout out to Baker Hill in our 40th year here we were right there at the forefront creating this market and the first to launch digital spreading tools where the focus was on standardization was in getting it into the same types of buckets year over year so that not only could I think about what it, The data was telling me on the financial statement or the tax return that I was looking at.
But what is it telling me year over year? What are the trends? How is this business performing? Not just in the past year, but over the course of the last three to five years, depending on how long of a view of history I look at. And those then continue to evolve. And you start to bring in concepts of how do I leverage the relationship information Associated with a particular deal.
And what does all of that tell me when I want to look at global concepts, debt service, coverages, global cash flows, et cetera. And it's just been this natural evolution that continues to have me spreading and analyzing at the same time when that's not always what I should do, because the spread itself, if I'm thinking about just, I've got David Catalano incorporated financial statements for 2023, I should be thinking about spreading those just in relation to what the numbers on the page are telling me, I shouldn't be thinking about, well, how did last year's analyst spread the information, you know, , the goodwill that's in David's, , Financials, how did they spread that last year?
You should be thinking about how you spread it, right? You should be thinking about from a credit perspective, how our organization views the information on this financial statement, what bucket does it go into? And I should be focused on, standardization. from that perspective. Then I should think about analyzing the information and what it is telling me because now I have to get into the context of why is it that I'm looking at this in the first place.
I'm probably either A, doing a new loan or B, doing an annual review. And how I think about the data is then colored by all of that other information. So separating the two concepts, even if it's the same person doing it. So even if you have an underwriting team that spreads and analyzes, kind of clearly separating those duties of saying, Hey, we got a data input and standardization effort, that's what we would call legacy spreading.
And we have an analysis effort that really needs to factor in. All of the relationship information, all of the deal information, because maybe it's one loan, maybe it's multiple loans, maybe it's one new credit, but modifying existing, you know, that now you're getting into different contexts and thus the numbers might tell me something different in my view of what it is I'm trying to accomplish for that particular borrower.
So it's a critical exercise to go through and unfortunately today, a lot of it happens within the same construct that can lead to some confusion about the data that when I come back and look at it on an audit basis.
David: The other thing is if you think about global cashflow and looking at, you mentioned my corporation, which is fictitious by the way, but it's not unusual for someone like me to have multiple properties, multiple pieces of real estate. So when you're looking at global cashflow, are you understanding that one piece of real estate is generating 400 percent of my income and the other two are losing money and over this because I've lost tenants or they're in areas that are not conducive to a new tenant or a new tenant, the same rent.
Or new tenant with the same space requirements or requiring a massive build out to move the, property from this use to that use. So being able to analyze income property, basically like an object within your analysis, as opposed to looking at it all at once, it just would allow a better, more complete analysis and looking at the strengths and weaknesses of the overall global cashflow.
So that's just an example of a way in which, financial analysis needs to be done and you need a solution to do that. And it's good that you can have a solution like that with normalized data and all the data is inside, inside your solution where you're using that in your credit memo or the presentation of the credit to the various people that are making that decision or the various people that are looking with perfect hindsight at the decision you've already made.
So justs makes a heck of a lot more sense to have the data entered and then have it normalized and available to you to use, depending on the deal tech and train and uncovering what that analysis is. But that analysis is again, it's like you're saying, it's not in the spreads. It's in the financial analysis aspect of what you're trying to do and what you're trying to decide on
Mitch: What both of you are hitting on, right, is what's the context, what does my analysis really mean, but then also how do I trace that back to where did this data come from, but then also where is it going after I do the analysis, Bryan, to your point with an audit, how do I really show why I made the decision that I made?
I think , maybe I'm packing this a little bit more right over the last several years. We haven't had a whole lot of issues with credit quality, but now things are starting to change a little bit. How does this really position a financial institution to be more successful if they're able to separate this concept of statement spreading and financial analysis as we look at it?
Thank you. What could be coming? Who knows what's going to happen, right? But what could be coming, what people are saying could be coming with potential credit problems for commercial and small business borrowers when you start thinking about statement spreading versus true financial analysis.
Bryan: Yeah, I'll use an example of a loan for a strip mall and how that might need to be looked at differently now than how it was in the past. So used to be enough to get rent rolls. Used to be enough to do high level tenancy analysis. , In my 80 percent occupied, what have you now, given the CRE concerns that are out there, given how the regulators are thinking about the needs of proof of good credit. We're seeing more and more of a push into what are the actual businesses in that strip mall? What do you know about nail salons in Montecito, California? What do you know about the health of CPAs in Carmel, Indiana? How are you getting a level of comfort that tenancy will stay at the rates you need it to fully serviced the loan that you're looking at? Which means I've got to go way beyond traditional spreading concepts, traditional rent roll concepts. You need to start thinking about how do I analyze all of this information and how do I bring that to life as part of my decision process and also potentially retrain the staff that you have, who just don't think that way.
Now, how do I put tools in their hands to make them look at a loan? The aspects that I know need to be reviewed to again ensure a sound credit decision is made and that goes way beyond what spreading is a component of it. I have to spread your tax returns. I have to understand what you're reporting from an income perspective to the federal government, but I got to do a lot more to and I've got to have a tools to help me facilitate that bring consistency to the process and ensure I'm doing it every single time.
David: The transition, the real estate, just as many sectors of real estate is going through a transition, a use transition. And then cities like Carmel, Indiana, where we reside, Is going through a transition as well, where roads are changing and roundabouts are being installed and traffic patterns are different.
So relying on something that historically has worked, you know, it's not going to work. You have to understand more of where I think Bryan said this before. More of where the puck's going, as opposed to where it's been. You're more like an economist than an accountant at this point. And you really need to understand what are these trends?
What am I getting myself into? What's the future state of this building? And then what's my backstop in the event that this doesn't work out? So we've seen real estate transitions, at least in this area, become very successful. And we've seen others that have failed miserably. And now there's a Republic Airlines headquarters there.
And that's a wonderful building. And that switch was absolutely wonderful. But I suspect the initial owner didn't do too well in that deal. So, you know, who is that lender? So it's,just a matter of understanding the transition that's going on, the type of real estate you're dealing with and getting deeper into that analysis versus used to historically be done or could be done within solutions.
So we're always thinking about that because we own this space and we want to lead in this space. And that's essentially what we're having this conversation.
Mitch: Bryan, David, thanks so much for taking some time today to dive a little bit deeper into the topic of financial analysis. I think some great takeaways for anyone that's listening, especially understanding how to provide context to your data that's coming in through spreads through financial analysis, and then really being able to trace your data sources there.
Being so critical for managing risk appropriately and also just being able to make sound credit decisions. So, thank you guys for sharing your insights and thanks everyone out there for listening to today's episode of Lending Made Easy.