Incomplete information model of credit default of micro and small enterprises

Tingqiang Chen and Suyang Wang

International Journal of Finance & Economics, 2023, vol. 28, issue 3, 2956-2974

Abstract: This research constructs a credit default estimation model for micro and small enterprises (MSEs) under the condition of changing information asymmetry. The model is established through the refinement, abstraction and portrayal of the core elements contained in the default trigger mechanism; this mechanism is based on the cash flow, the default boundary and the distribution of actual cash flow in the framework of the incomplete information model. By relaxing the assumption that the bank can fully observe the customer's initial information, this work constructs a theoretical model with practical application value that can effectively describe the default risk of MSEs. Numerical simulation shows that the model can accurately estimate the default probability of MSEs by quantitatively modelling the mechanism of default risk management and control which is applicable to the risk characteristics of MSEs. The model is also suitable for the continuous dynamic estimation and forecast of individual customer credit application and post‐lending risk.

Date: 2023
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