Modeling Bayesian inspection game for non-performing loan problems

Abstract

This study compiled a Bayesian inspection game as a branch in game theory to deal with non-performing loans (NPLs). Three types of games are analyzed, which are false alarm (FA), non-detection (ND), and bull's eye (BE). A Bayesian Nash equilibrium calculation process took place to formulate the player's strategy proportion. The equilibrium solution indicates the causative factors and develops the strategies to anticipate NPLs. The identified factors causing NPLs include customers' utility and disutility, inspection error in the form of false alarm and non-detection, operational costs to conduct an inspection, and bank utility related to inspection. The results showed that some examinations of type I and II errors to the game model could provide more comprehensive and interesting insights in managing NPL problems.