On the Optimal Design of Operational Risk Data Consortia

Abstract

To manage operational risk banks increasingly use data coming from data consortia that are formed by peer institutions. Though existing data consortia seem to work appropriately, it is worth studying what makes banks to report properly (that is, thoroughly and truthfully), since in several countries where new data consortia are planned to be set up, there are fears that banks may choose to report untruthfully or hide information (what we call misreporting). We show that if misreporting cannot be detected, then even in an infi…nitely repeated setup the game has multiple equilibria, so proper reporting is not the unique outcome. Then, we study two types of sanctions. When the punishment is non-monetary (eg, exclusion from the consortium for a given number of periods), then for some parameter values even the harshest punishment cannot bring about proper reporting as the unique outcome. Nonetheless, a numerical example suggests that by designing adequately the data consortium, proper reporting can be advanced, without compromising anonymity overly. When a monetary fi…ne is imposed on misreporting banks, then a sufficiently large punishment attains proper reporting, even if anonymity is maintained in the limit.