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Assumptions in a Loan or Deposit Pricing Model

July 18, 2017
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A growing number of our clients are using LoanEDGE and iPrice to evaluate the relative profitability of everything from existing consumer rate sheet products to commercial lending deals. But the results can be misinterpreted unless we remind ourselves that a profitability model that looks forward, like LoanEDGE does, is not a prediction of results. In fact, if we are using the model correctly it won’t predict the exact outcome of any particular loan correctly, other than by luck. This is because these models are based on average behaviors and try to explain the overall behavior of a pool of loans or deposits – not the exact behavior of any particular borrower or depositor. We often make the mistake of thinking that we are forecasting the specific outcome (such as net income) with a loan model in order to determine exactly how to price it.

An institution budget is a forecast. It is attempting to describe what the balance sheet and income statement will look like at some point in the future. A profit model is not a forecast; it is a framework for comparing options. It shouldn’t be used like a forecast, because to do so you would have to evaluate every single non-commercial borrower independently and these models aren’t built to do that, nor do you have the time. A loan model is really helping you evaluate the overall value of a group of loans of some type compared to loans of some other type (or compared to something other than a retail loan, such as a wholesale market investment).

So what good is a model, if it won’t tell me how much we are going to make? For starters, a loan model is good for making pricing decisions that are not based on antiquated practices, or simplified views of what a competitor might be doing with rates. For example, many institutions fail to consider putting longer term fixed rate loans in their portfolios because of the myth that they have more interest rate risk than you can manage. A pricing model will show you how much interest rate risk you are carrying relative to other options, and then show you how you can adjust for that in the rate or fees charged.

Clearly a pricing model has to make assumptions about the market, consumer behaviors, and costs. We have to make guesses about market rates in order to evaluate wholesale alternatives. We have to make guesses about credit losses and prepayment activity – which are consumer driven activities. And we also have to make guesses about our operating costs and other expenses.

One of the observations we’ve made over the years is that for loan and deposit pricing purposes, some of these assumptions are more important than others and, therefore, some deserve more attention than others. Let’s look at the categories.

Market Rates

We all know the folly in trying to predict markets and rates. It can’t be done with any degree of accuracy that gives you any advantage. So what we do in a modern pricing application is evaluate today’s decisions using today’s yield curves. That’s it. The yield curve shows us what we can earn right now at any given duration point. For example we know what we would pay today to buy duration insurance in the wholesale market – via something like an FHLB advance rate. We take advantage of the fact that the current market yield curves represent the market’s evaluation of interest rate risk compensation along with relative preferences among wholesale options. We use that information in a loan model to determine funding cost assumptions and investment alternatives. Some people feel that a loan pricing model should attempt to describe what happens with different future rate environments, much as you do with an asset liability model that takes a prospective institution business plan through different possible rate scenarios. We don’t do that in an individual loan model because the results aren’t useful. That kind of analysis makes the mistake of trying to forecast a specific outcome for a specific loan, rather than looking at the relative value of a group of loans. In order to make sense of future rate possibilities, we would have to compare all possible newly funded loans at the same time – which is what an asset liability model scenario does.

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Credit Loss

Credit loss assumptions are likely the most important assumption set in a loan pricing model. For starters, it is a true variable cost when comparing between different lending activities. We know for certain that you are taking on more credit risk when making sub-prime auto loans than you are making first purchase mortgages to existing customers. So the credit loss rate you assume will make a major difference in how that loan will perform (generate a profitable return) in a loan pricing model.

How to make those assumptions is a topic well beyond the scope of today’s article, and Farin has recently expanded its credit risk services capabilities in part because of their importance. If given a choice on where to spend time or resources on the different assumption sets, we recommend you start with credit loss analysis. It is a given that in order to do any kind of risk based lending (such as the tiering of auto loans by credit grade), you need a solid mechanism for predicting the credit loss rates.

Prepayment Rates and Option Risk

Prepayment rates for loans and decay rates for deposits are fairly important assumptions in a complete asset liability model, but they are much less important in a loan pricing model. The option risk assumption is really the important one. Why is that?
In a loan pricing model, the prepayment rate is used only to estimate the principal balances being supported over time – and therefore what it is going to cost to fund them. A higher prepayment rate assumption means we expect more balances to mature earlier, and so we will have a shorter duration and lower funding cost for that loan category. But unless you are looking at longer term fixed rate loans, the difference is very small and not worth too much effort on its precision.

The option risk assumption is more important than the prepayment assumption with any loan that has a prepayment option. The reason is that you are taking on a risk that the market is compensating others for, so you do not want to give that benefit away or you run the risk of underpricing loans.  See the article onOption Risk Values for a very detailed explanation of option risk.

The bottom line is that if you use our assumptions, you are probably better off than guessing on your own – so no extra effort is needed here.

Operating Expenses

Expense assumptions are very important, because they represent costs that you are incurring in supporting retail products that do not exist when you purchase wholesale alternatives. So when comparing the alternative of adding to your investment portfolio versus adding to your retail loan portfolio, the additional costs are clearly a large factor.

We see two specific issues with operating expenses; how to come up with them, and then how to apply them. By far the best way to come up with them is to have a cost study done. We think the best cost studies have a couple of characteristics – they separate origination activity from operating activity, and they separate marginal costs from overhead costs (they spare the overhead allocation from the activity costs). As an example, if you have a study that estimates what your marginal origination cost is for a typical consumer loan, you have an excellent starting point in making a cost assumption in a loan model. A cost value that estimates the average origination and operating cost per loan across the entire organization is much less useful, because it won’t let you determine where you might have the best opportunities to beat alternative loans or investments. Finally, we always suggest that cost assumptions for loan and deposit modeling be expressed in dollar values. When you use percentage values in operating cost assumptions, you are making the potential mistake of assuming that it always costs twice as much to originate or service a loan if it is simply has twice as large a principal balance. We know that is hardly ever true.

If you do not have a recent cost study, we do have some industry based numbers that we can share with you. But we are always cautious of using industry or peer numbers for anything other than getting started with a reasonable set of assumptions.

We think overhead allocations that are not directly related to a lending or deposit activity should always be left out of cost assumptions. Remember that the primary purpose of a pricing model is to help select among alternatives. When we choose among different potential lending activities, we certainly want to know of one of those activities is expected to have higher marginal costs. But you will be at a competitive disadvantage to the market if you load your costs assumptions with overhead, and overhead costs are not marginal costs. Those who argue for overhead cost inclusion point out that all revenue generating activities in an institution have to make a contribution to overhead; otherwise you will be losing money on the institution income statement. But that isn’t true – very often only some activities generate the majority of the true margin that is used to support the organization. A loan pricing model isn’t trying to make that determination. It is only trying to show you the marginal benefit, and marginal profitability of that activity.

*Some of the solutions or services mentioned in this post may no longer be offered. For information on alternatives, please go to visit Abrigo Advisory Services.

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