Last time we spoke of market forces and demographic tendencies that should be considered in contemplating jumping into or out of the mortgage servicing marketplace.

This time we will explore how mindsets can change how you approach the aggregation of servicing assets. One specific model we will examine is the Clustered Borrower Retention Model.

Traditionally, servicing valuation and marketing has been approached using what we will call a “Single Transaction Model”. Whether or not the bid is being placed on a single loan or portfolio of loans the price multiple(s) offered are based upon the cash flow expectations that those specific loans will produce.

This approach provides for a very wide discrepancy in the price offered for a single loan’s MSA (Mortgage Servicing Asset) or collection of loan MSAs. Any time there is a discrepancy, somebody is right and somebody is wrong.

Reasons for the difference range from assumption made to hedging capabilities to cost control capabilities. Still somebody is right and somebody is wrong.

As we are at a 40 year low on many credit market yields, one might ask can they go any lower? The potential MSA investor using a “Single Transaction Model” must ask this question each time a bid is posted.

An alternative way to approach the business is to not look at the loan, but at the borrower. Perhaps not at the borrower, but at a cluster of borrowers. Not to focus on the borrower at a single point in their life but consider the borrower from this point in their life forward.

The “Clustered Borrower Retention Model” takes this approach. The CBRM considers where the borrower is in their lifecycle. Based upon such determinants as the loan they are taking today what habitat path are they following profiles are established. The CBRM would then group borrowers with similar profiles and entry points into clusters.

Here’s an example of viewing a loan in this fashion. We have a borrower, age 25 who is taking down a $150,000 loan today. The expectation is that this person will own a residence until age 70. Notice we said “a” residence, not “this” residence. Next, we identify what longterm return we wish to achieve from our activities. In considering the long-term return we must consider inflation. Thus, we target a long-term spread over the rate of inflation rather
than a static yield level.

In our case, we assume a constant rate of inflation of 2.000%. We wish to return 8.000% over the rate of inflation. Thus, our initial target yield is 10.000%. If our borrower tends to relocate every seven years, we are looking at this borrower having at least seven mortgage transactions in their life. Now, if our borrower has the tendency to
refinance each time market rates are 5/8ths lower than their existing mortgage rate, we are set to have more potential transactions than seven.

If our borrower tends to trade up in value each time they change domiciles and inflation increases at 2.000% per annum we will be looking at a growing servicing asset rather than a diminishing servicing asset over time.
When this and a few other considerations are thrown into the mix the unit value of this specific MSA when divided by the average loan transaction booked ranges between 1.150 and 1.350. This value range exists after using a multitude of possible rate paths to stress test the value. Not very volatile, huh?

So how do you retain these clusters? To draw from ZZ Top it’s good to be “…Bad and Nationwide…

Greg Crosby manages the secondary marketing software and services product line having joined ASC in June 1997. Greg has been involved in the mortgage industry since 1981. His fields of experience include secondary marketing, financial and performance auditing, construction and design of financial conduits, software development, commodity and securities portfolio management, and design of risk assessment systems. He developed the Risk Manager and Servicing Shepherd™ software products. Greg has served as a chief financial officer, with both commercial banks and investment securities brokerage firms, and has served as an advisor and board member to companies ranging from service providers to financial conduits. Greg is considered an industry expert in the fields of secondary marketing and risk management has authored numerous articles, papers and a book titled The Theory and Practical Application of Improving Secondary Marketing Performance with Software Tools.