Point of View: The Servicing Impact.

Mr. Showalter is senior director of product management at LoanPerformance. This viewpoint is the second of two parts. The first part ran in the August edition of MSN.

The impact of borrower and product trends on mortgage servicing is becoming apparent. As the mix of borrowers and products becomes more diverse, the complexity of the mortgage servicing problem is growing exponentially. Besides loan volume increases, today's loan portfolios have a higher portion of service-intensive loans (e.g., ARM, option ARM, IO). Moreover, servicing a delinquent ARM is not the same kind of problem as servicing a delinquent IO, neg am or fixed-rate loan.

Furthermore, addressing the issues of a subprime borrower are far different from addressing the servicing issues of the alt-A or prime borrower. A subprime borrower is likely to be more economically unstable and, at times, ill-equipped to handle the rigors of monthly debt service, especially when compared to the more economically stable, experienced bill-paying alt-A or prime borrower.

Clearly, the complexity of servicing loans is on the rise. Unfortunately, only a portion of subprime mortgage servicers are successfully coping with this increased level of complexity. There is a growing gap (as measured by nominal loss rates) between "best" and "worst" servicers, when comparing the performance of servicers who are servicing subprime paper.

In this study we compared actual (nominal) loss rates by subprime servicers using a static pool with a two-year look-back period ending in October 2005. The variance in servicer performance exceeded 300 basis points when comparing the typical top quartile player and the typical bottom quartile player. A comparison of the "best" and "worst" servicers revealed a 600-plus basis point variance. These servicer comparisons were not balanced for product type or vintage, so they only serve as a rough estimate of loss rate performance differences across servicers. Nonetheless, the conclusion that there are substantial (and economically significant) loss rate performance differences across subprime servicers is entirely valid.

The risk-adjusted impact of servicer selection on loss rates escalates with increasing portfolio loss rates. When moving from an expected loss rate of 1% to one of 8%, the potential impact of servicer selection on portfolio losses increases from 100 basis points to over 800 basis points on a risk-adjusted basis. This means that when neutralizing the effect of collateral risk upon servicer performance, loss rate performance can vary as much as 800 basis points between "good" and "not so good" servicers if the overall subprime loss rate equals 8%.

Translating risk-adjusted index performance into value added (or subtracted) by a servicer is relatively easy. If a servicer is servicing a $1 billion portfolio that loses 1.5% ($15 million) and this servicer's loss rate performance generates an index score of 75%, then this servicer would have reduced losses by $3.75 million relative to the typical servicer in this market.