Roles of artificial intelligence in bank-firm loan decisions: a game-theoretic analysis
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Abstract
Objectives: This study aims to develop a game-theoretic model to analyze the impacts of Artificial Intelligence (AI)-based credit risk assessment on the strategic decisions of banks and firms in the loan market.
Significance: Understanding these dynamics is crucial for enhancing financial inclusion, reducing credit access barriers for SMEs and improving lending outcomes for banks.
Methods: The study constructed a game-theoretic framework in which banks set loan terms while firms decide whether to accept these terms based on their expected returns, creditworthiness and alternative financing options. The theoretical model involves baseline analysis; then consider the impacts of AI-driven risk assessment and finally perform some comparative statics analysis.
Results: The analysis revealed that incorporating AI reduces uncertainty in default risk assessment, promotes financial inclusion for SMEs and enhances regulatory compliance.
Recommendations: The study recommends that regulators develop frameworks that incentivize banks to adopt AI in risk assessment.
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