The Design of Credit Information Systems

We examine the performance of large credit markets subject to borrower moral hazard, when information on the past behavior of borrowers is subject to bounded memory constraints. Borrowers who default should be temporarily excluded in order to efficiently incentivize repayment. However, lenders have an incentive to lend to borrowers who are near the end of their exclusion period, undermining this punishment. With perfect information on past behavior, no lending can be sustained, independent of the length of memory. Coarse information about borrowers' histories improves outcomes, by mitigating lender moral hazard. By pooling recent defaulters with those who defaulted further in the past, coarse information induces borrower adverse selection. This disciplines lenders, who are now unable to target loans towards those defaulters who are least likely to offend again. Paradoxically, efficiency can be improved by non-monotonic information structures that pool non-defaulters and multiple offenders. Equilibria where defaulters get a loan with positive probability can also improve efficiency, by raising the proportion of likely re-offenders in the pool of recent defaulters.