Loss mitigation doesn't quite seem the right term for mortgage loan portfolio problems these days. How about "women and children first"?
According to RealtyTrac, foreclosures went up 12 percent in September, and were up 27 percent from a year ago. One in 416 households had received a foreclosure notice during the month.
The level of distressed mortgage portfolios full of unaffordable ARMs and high LTVs is only expected to worsen in 2009 as housing prices decline and shaken consumers move perilously close to the economic cliff. Banks and mortgage insurers are in the quicksand, as well, grasping for any lifelines to stave off the suddenly realistic threat of institutional collapse. It's not an ideal environment for making long-term decisions on loan modifications but banks may have little choice in the face of increased foreclosures and bulging REO listings.
Several technology providers in the past year have rolled out various systems to help banks streamline workouts or get a head start on communicating potential defaults, but workouts may only help with a current crisis - and not solve long-term problems of keeping homeowners in houses and out of collections.
The smarter strategy, say some observers, is to broaden portfolio analytics to include more loan-level details and more predictive analytics around consumer behavior. It's predictive pricing, in a sense, that's been moved to collections strategy - what methods would likely engage more homeowners in a successful resolution, and preserve more overall value for investors?
"Banks and servicers need a way to deal with the current delinquent borrowers they have, and know which ones will be in that category in the future," says Gartner's Kristin Moyer, a lending services research director.
That path, she says, may be through predictive assessments, "with an eye on home retention," instead of simply easing current quarterly loss numbers.
One vendor entry in the field, Scottsdale, AZ-based Response Analytics, landed a deal recently with a default division of servicer First American Corp., with software and services that employ behavioral metrics to evaluate the division's distressed portfolio for potential value.
Response Analytics's technology focuses on metrics that measure how both borrowers behave and portfolios change with ongoing market and economic conditions, including home values and local unemployment rates.
Unlike the practice of securitizing these loans, in which individual homeowner risks were wrapped up and disguised within tranches of collateralized debt, the activity by Response Analytics dives down into those loan-level details to measure the likely success (or otherwise) of workout programs.
Instead of one-size-fits-all modification strategy, banks and servicers can delineate how alternatives might bring different results based on a homeowner's situation. "We try to understand how a borrower will behave over time, given different workout treatments," says Brent Lippman, CEO of Response Analytics.
For example, freezing or reducing an interest rate may not keep a borrower current over the long haul. But reducing the monthly payment by giving that borrower reduced principal could add an incentive by upping his stakes in the loan.
The incentives can work from the top down, as well. Mortgage insurers who can get a handle on different borrowers can offer certain programs to segments within portfolios, according to Lippman, a serial entrepreneur who previously ran Khimetrics before selling the price optimization company to SAP.
With more certainty around borrower behavior, the product can ascertain cashflow to calculate a "hold to maturity" price for investors in order to project what portfolios are likely to yield, according to Lippman. That not only encourages servicers to improve consumer workout programs, but may boost incentives by insurers behind those servicers. Lippman says these strategies can improve portfolio performance by 500 to 1,000 basis points.
Gartner's Moyer says that both loan-level and portfolio-level analytics have to be applied. "You need loan data, borrower data, projected home price index, unemployment data, interest rates, some existing analytics...that can give you an idea of where your overall portfolio is," says Moyer.
Land America's "Back in Black" program or CSC's EarlyResolution software also help banks and servicers perform workout scenarios and whether it makes sense to move a loan into modification, foreclosure or perhaps allow a short sale.
But black-box analytics have drawbacks and limitations. Much of the ultimate decisioning taking place is not automated, and doesn't alone tackle the volume crunch of workout requests at stressed institutions. And if the fire in the mortgage arena spreads to unprecedented levels, where do these behavioral models draw their guidance?
Lippmann says Response Analytics's models gain more intelligence over time as the results of its clients' decisions. Believe it or not, for many of these predictive tools, the answers also come from data derived from the much-tarnished ratings agencies, says Craig Focardi, a research director in consumer lending at TowerGroup.
"Standard & Poor's and other ratings agencies looked at high defaults in the 1980s in many oil patch states like Texas, Louisiana and Oklahoma, where default rates reached 20 to 30 percent of every mortgage outstanding in certain MSAs," says Focardi. "So we do have empirical data on what happens when home values go down that significantly and default rates increase that rapidly."
It remains to be seen whether troubled servicers and banks are willing to invest in such a fine-tuned approach to portfolio analysis when the problems are so sweeping.
"One of the questions now, since there's such a big flood of loans and some of the decisions are so sweeping, is: are their blunter decisions that need to be made that don't require as sharp a tool to get it done?" says Focardi.