LIKE A CRYSTAL BALL FOR THE SERVICING SPACE, PREDICTIVE
ANALYTICS QUARRIES DATA TO PATENTLY REVEAL
WHAT THE FUTURE HOLDS FOR HOMEOWNERS
by Adam Weinstein
In the past few years, lenders, investors, and servicers have seen it all: big, fat sales bubbles; explosions of defaults; and avalanches of paperwork filings and data. And while the broad strokes of the economy are plain enough for all to see, the billions of nitty-gritty details can—even for the most seasoned pro—be far from crystal clear.
If you’re reading the Wall Street Journal or the latest reports from Zillow and Realty-Trac, that’s a start—albeit a bare minimum nowadays for staying abreast of the economy and the pressures on your portfolio. But you can’t shake the sense that somewhere out there, in that flood of data, is the info you need to predict the outcomes of your financial risks—who will default, who can benefit from which loss mitigation measures, and what you need to do to anticipate every ebb and flow in borrower behavior. “Servicers and investors are faced with a whole lot of delinquent loans,” said Mark Milner, VP of solutions consulting at LPS Applied Analytics. “Who should we focus our resources on to try to limit losses?” The truth is out there. And it rests squarely on the number-crunching, stone-unturning supermen of predictive analytics. Keeping an eye on the industry’s numerical indicators—pricing and interest-rate trends, default rates, foreclosures, and the like—is nothing new, of course. And in volume retail businesses, predictive pricing has long kept firms ahead of the curve when it comes to optimizing their consumers’ activity. Essentially, analytics in the mortgage-servicing space
applies those pricing predictions to prepayment and collections risks.