Explainable AI Models for Credit Risk Assessment in Fin Tech Applications

Key Points

• The research aims to investigate how explainable AI models can improve credit risk analysis in FinTech applications.
• Analyses the limitations of conventional credit risk assessment practices
• Evaluates the effectiveness of explainable AI models compared to traditional statistical methods
• Explores the benefits of increased transparency and adaptability in credit risk assessments
• Findings highlight that explainable AI models offer greater transparency in decision-making processes
• Results indicate improved adaptability in credit risk assessments
• Demonstrates potential for higher accuracy in predictions compared to traditional methods