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Since the end of the day quickly approaches, we happily present to you some dense academic work that points out a few new nuances on something you probably already intuitively knew about securitization. Alea picks up on an interesting paper that will take you there: a result, statistical default model fitted in a low securitization period breaks down in the high securitization period in a systematic manner: it underpredicts defaults for borrowers for whom soft information is more valuable (i.e., borrowers with low documentation, low FICO scores and high loan-to-value ratios). We rationalize these findings in a theoretical model that highlights a reduction in lenders' incentives to collect soft information as securitization becomes common, resulting in worse loans being issued to borrowers with similar hard information characteristics

The Failure of Models that Predict Failure: Distance, Incentives and Defaults [Alea]