Analyzing credit risk in the RMBS sector has increasingly become more granular post crisis, said participants in yesterday afternoon’s panel at the Information Management Network’s ABS East conference. The gathering is being held this week in Miami Beach.

The discussion centered around the changes in the way RMBS market players are examining mortgage collateral and borrower performance. These have been implemented to incorporate the lessons learned from the crisis, the changes in consumer behavior, and the shifting regulatory requirements.

Panelists said that collateral composition has become a key metric in determining the propensity to default.

Michael Yadov, a senior pricing analyst at Standard & Poor’s, said that S&P has increased the number of buckets to as many as 1200 from 150 when slicing and dicing mortgage collateral to predict defaults.

Jonah Green, a director in mortgage analytics at 1010data, said that around four to five years ago analyzing RMBS transactions mostly involved separating mortgage collateral into three buckets:: prime, Alt-A and subprime. Collateral analysis was also mostly done on a pool level, he said.

When the financial crisis happened, RMBS market participants started looking at home price appreciation as a factor in their analysis, specifically calculating the effects of negative equity. A more recent development, particularly at hedge funds, is the incorporation of consumer data into the analytical equation.

Tim Martin, group vice president in capital markets at TransUnion, said that RMBS market participants are going beyond merely analyzing how borrrowers are performing on their mortgage obligations. In other words, market players are increasingly looking at how  consumers are doing in terms of their other debt. This has become possible with the ability to link the security to the loan and to the borrower.

He mentioned that a study that TransUnion does on a regular basis of 27 million credit records found that many borrowers have shown improved performance in their non-mortgage debt. These include credit cards and autos, which are sectors where consumer deleveraging has become increasingly apparent. However, no U.S. state, on a year-over-year basis, has shown any improvement in borrowers’ performance in terms of paying their mortgages.

Martin added that there are also other factors that give dimensionality to existing credit scores. For instance, he mentioned DTI ratios and borrowers making inquiries about obtaining new credit, which could serve as a leading indictor of the probability to default. 

Regulatory changes have also resulted in shifts in data analysis. With the new capital requirements and the significant downgrades that happened in the triple-A RMBS sector, the ways to determine the risk weighting that has to be held against assets has also changed, according to Wenbo Zhu, a managing director at Sandler Oneill & Partners. Determining the risk weighting is now based on the intrinsic valuation of the security and not on its credit rating.

As a result, she said that many insurance companies have had to raise equity to satisfy risk-based requirements. She also mentioned that banks have had to utilize intensive data and technology to help them implement the capital rules.

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