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Distressed Mortgage Portfolios: A Borrower-Specific Approach

Although mortgage portfolios are going for bargain-basement prices, investors are still shying away from them.

Notwithstanding a general sense that these portfolios may indeed represent bargains, without a way of valuing them with a high level of confidence, they will languish unsold.

The value of a debt security is in the cash flow it will produce over the life of the obligation. But what is the expected cash flow of a distressed mortgage? While in some ways this question is at the heart of the current credit crisis, it is of particular interest to the prospective investor.

As a secured obligation, it should have some value, even if only through an REO (real estate-owned). But not only is foreclosure rarely the best option for the lender, it does not even lead to a straightforward evaluation, as two identical properties with identical initial sale prices in different locations will each be subject to the vagaries of the local real estate market and macroeconomic climate.

In the current environment, a combination of declining housing prices, tight credit, and growing public concern combine to make foreclosure an even less attractive option, particularly in the case of primary residences.

But if REOs are difficult to value, workouts are even more so. The goal in any given workout, of course, is to find the modification that will maximize the cash flow while remaining manageable for the borrower. If the modification is inadequate, the borrower will end up in default once again - we only need to note the Comptroller of the Currency's recent 51% re-default rate to fully appreciate this; yet if the loan modification is too generous, the investor is leaving money on the table. And because each borrower is different, a one-size-fits-all approach to loan modifications invariably misses the "sweet spot," as the recent spate of re-defaults on modified mortgages has shown.

At the same time, to have an experienced loan officer evaluate each distressed loan and determine the appropriate modification is simply not an option for loan servicers these days, even less so for the prospective purchaser of a large portfolio.

The idea is the right one, though: if it were possible to establish the optimum workout for each distressed loan in the portfolio, one could calculate the real hold-to-maturity value of the entire portfolio and use that to make an informed decision about whether to purchase the portfolio, and at what price. Now it is possible to apply advanced modeling and optimization technology, such as has been successfully applied to pricing optimization, to perform such calculations on distressed loan portfolios.

For while all borrowers are different, they are different in a constrained number of ways, and this makes it possible to use payment history data to construct predictive models of borrower behavior based on certain categories, such as geographical location. For example, it will explore whether a homeowner in Boca Raton is more likely to default than a homeowner in Des Moines, and given a home with the same home value, the same balance remaining on the same kind of loan, and the same FICO score, what different workout and loan modification actions to take in each case.

By running the behavior model against the different types of possible responses to the distressed loan, the optimum workout for a particular borrower can be arrived at, and these can then be used to optimize the cash flow for the entire portfolio. Further, an Optimization approach can take into account regulations or investor covenants that constrain the possible options, as well as the investor's own time horizon for holding on to the portfolio. This tells only part of the story. Since each modification is tailored to the particular borrower, there is a much higher probability that the new terms will actually be met. The importance of this cannot be over-emphasized: in December, Comptroller of the Currency John Dugan revealed that well over half of the borrowers whose mortgages had been modified were once again delinquent.

Dugan said it was unclear why the re-default rates were so high after modifications made by the 14 banks that provided data to his office. He acknowledged that "we have to be careful as we look at this data." One explanation for the high re-default rate might be that banks were not significantly changing the terms of the loans they modified. ("Modified Loans Often Lead Homeowners Back to Trouble" New York Times, Dec. 8, 2008)

The problem of the standardized workout is that it expects the borrower to conform to some arithmetical average of how a generalized borrower should behave. By constructing a model based on an enormous amount of payment history, an Optimization approach is able to recommend loan modifications that conform to how the particular borrower is most likely to behave.

The investors now has innovative solutions available that will enable them to accurately value a mortgage portfolio based on its hold-to-maturity value, and provide direction to the servicer to handle the loans in order to maximize that value; optimization is technology that will allow them to find value in one of the most important undervalued assets now available.

As with numerous other banking crises that have occurred in the past, technology can help us move beyond our present impasse and cause the markets to start moving again.

The Optimization Approach to Distressed Portfolio Management:

* Takes in existing behavioral (servicing) data

* Analyzes data and creates behavioral models from it

* Enhances delinquent and default models

* Models and forecasts customer behavior and financial impact

* Predicts likelihood of borrower performance

* Recommends "optimized" workout strategies

* Assesses value of multiple loan workouts

* Forecasts (expected) NPV cash flows

* Adapts continuously to borrower behavior and market conditions

* Assesses "hold-to-maturity" values (not mark-to-market)

* Refreshes models more frequently as markets, customer behavior dictates

Brent Lippman can be reached at brent.lippman@responseanalytics.com

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