Credit risk: an agent-based model of post-credit decision actions and credit losses in banks

2012 ◽  
Vol 6 (4) ◽  
pp. 253-266 ◽  
Author(s):  
S Jonsson
Keyword(s):  
Credit Risk ◽  
Agent Based Model ◽  
Agent Based ◽  
Credit Losses

The effects of reward system on bank credit losses – an agent-based model

2015 ◽  
Vol 41 (9) ◽  
pp. 908-924
Author(s):  
Sara Jonsson
Keyword(s):  
Reward System ◽  
Bank Credit ◽  
Reward Systems ◽  
Risk Modeling ◽  
Agent Based Model ◽  
Credit Risk Management ◽  
Content Type ◽  
Agent Based ◽  
Loan Officer ◽  
Credit Losses

Purpose – The purpose of this paper is to investigate how the design of loan officer reward systems affects bank credit losses caused by commercial clients. Design/methodology/approach – This paper uses an agent-based model to investigate how the design of reward systems affects bank credit losses. Two different systems are compared: competitive and a cooperative. The model is designed according to the theoretically derived assumption that a cooperative reward system will make agents more likely to share knowledge with each other in the processes of granting and monitoring credit. Findings – The results show that a cooperative reward system have potential to reduce bank credit losses. The reduction of errors in evaluating company’s probability of default thus mitigates variations induced by variations in industry, region, and firm-specific returns. Practical implications – The findings imply that reward system design should be considered in credit risk management. Further, managerial issues (e.g. reward systems) should be considered in risk modeling. Originality/value – The results presented in this paper provide evidence to the value of considering the downside (e.g. loss) when designing reward systems in banks.

scholarly journals A Network Evolution Model of Credit Risk Contagion between Banks and Enterprises Based on Agent-Based Model

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Pei Mu ◽  
Tingqiang Chen ◽  
Kun Pan ◽  
Meng Liu
Keyword(s):  
Credit Risk ◽  
Learning Algorithm ◽  
Banking System ◽  
Network Evolution ◽  
Agent Based Model ◽  
Power Law Distribution ◽  
Agent Based ◽  
Behavioral Rules ◽  
Credit Risk Contagion ◽  
Asset Size

Credit risk contagion between banks and firms is one of the important triggers of financial crisis, and the credit linkage network is the way of systemic risk contagion triggered by external shocks. Considering the heterogeneity of behavioral rules, learning rules, and interaction rules, this paper constructs a bank-firm credit matching network model based on ABM (agent-based model) model and reinforcement learning algorithm to analyze the interaction behavior and credit risk network contagion mechanism. The results show that (1) macroeconomic cycles are the result of the interaction between banks and enterprises and the interaction of microentities under complex financial conditions; (2) enterprises are heterogeneous and the asset size follows a power-law distribution; (3) the greater the sensitivity of banks and enterprises to market performance, the lower the bank failure rate and enterprise default rate; and (4) shocks to the largest banks and enterprises in terms of assets and entry can all intensify the risk contagion between banks and enterprises. Therefore, the regulation of financial institutions that are “too big to fail” is not sufficient but should be a comprehensive regulation of the banking system.

Simulations of an Agent-Based Model that Consists of a Large Number of Agents Moving Stochastically in a Wide Bounded Domain

2001 ◽  
Author(s):  
Minoru Tabata ◽  
Akira Ide ◽  
Nobuoki Eshima ◽  
Kyushu Takagi ◽  
Yasuhiro Takei ◽  
...  
Keyword(s):  
Bounded Domain ◽  
Agent Based Model ◽  
Agent Based
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