A recent article in the Boston Globe talked about the lack of incentive for banks to perform wide-scale real estate loan modifications due to the lack of profitability for lenders in the current government-led program structure. The article cited a recent study by the Boston Federal Reserve that noted up to 45 percent of borrowers who receive loan modifications end up in arrears again afterwards. On the other hand, around 30 percent of borrowers cured without any external support from lenders – leading them to believe that the cost and effort required modifying delinquent loans is not a profitable or not required proposition.
Adding to this, one of the study’s authors was quoted as saying “a lot of people you give assistance to would default either way or won’t default either way.”
The problem that lenders face is that although they have the knowledge that certain borrowers are prone to re-default, or cure without much assistance – there has been little information available to distinguish these consumers from each other. Segmenting these customers is the key to creating a profitable process for loan modifications, since identification of the consumer in advance will allow lenders to treat each borrower in the most efficient and profitable manner.
In considering possible solutions, the opportunity exists to leverage the power of credit data, and credit attributes to create models that can profile the behaviors that lenders need to isolate. Although the rapid changes in the economy have left many lenders without a precedent behavior in which to model, the recent trend of consumers that re-default is beginning to provide lenders with correlated credit attributes to include in their models.
Credit attributes were used in a recent study on strategic defaulters by the Experian-Oliver Wyman Market Intelligence Reports, and these attributes created defined segments that can assist lenders with implementing profitable loan modification policies and decisioning strategies.
