Asymmetric information and the securitization of SME loans (with Margherita Bottero)

Abstract:
Based on granular data for the entire population of firms borrowing from Italian banks active in the securitization industry, we test for asymmetric information in this market. We borrow the methodology from the empirical literature on insurance, looking at the correlation between the degree of risk-transfer and the default (accident) probability. The methodology adopted also provides information on how loans are selected for securitization based on observable characteristics. In addition, the presence of multiple lending relationships is exploited to disentangle the adverse selection and the moral hazard components. We document the presence of asymmetric information, mainly in the form of adverse selection. Moral hazard is limited to credit exposures characterized by weak relationship ties between the borrower and the lender, indicating that a tight credit relation is a credible commitment to continue monitoring after securitization. Importantly, the selection of securitized loans based on observables is such that it largely compensates the effects of asymmetric information, rendering the unconditional quality of securitized loans significantly better than that of non-securitized ones. Thus, despite the presence of asymmetric information, our results are inconsistent with the view that credit-risk transfer lead to lax credit standards.