Explainable Machine Learning in Credit Risk Management

2020/09/25 by Niklas Bussmann, Paolo Giudici, Dimitri Marinelli +1 · 7 citations
Business, Management and Accounting · Economics, Econometrics and Finance · #Credit Risk and Financial Regulations #FinTech, Crowdfunding, Digital Finance #Financial Distress and Bankruptcy Prediction

paper · pdf · doi:10.1007/s10614-020-10042-0

openalex publication_date 2020/09/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Abstract The paper proposes an explainable Artificial Intelligence model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing peer to peer lending platforms. The model applies correlation networks to Shapley values so that Artificial Intelligence predictions are grouped according to the similarity in the underlying explanations. The empirical analysis of 15,000 small and medium companies asking for credit reveals that both risky and not risky borrowers can be grouped according to a set of similar financial characteristics, which can be employed to explain their credit score and, therefore, to predict their future behaviour.

Citations

• A Unified Approach to Interpreting Model Predictions
• From local explanations to global understanding with explainable AI for trees

Cited by

• CLMN: Concept based Language Models via Neural Symbolic Reasoning
• Interpretable Machine Learning for Predicting Startup Funding, Patenting, and Exits
• An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness
• Enhancing Credit Risk Prediction: A Meta-Learning Framework Integrating Baseline Models, LASSO, and ECOC for Superior Accuracy
• The Basic B*** Effect: The Use of LLM-based Agents Reduces the Distinctiveness and Diversity of People's Choices
• Exploring a biocentric LLM-based assistant in environmental decision-making with more-than-human representation of the Tagus Estuary
• SHAP Stability in Credit Risk Management: A Case Study in Credit Card Default Model

Related

• Explainable AI in Credit Risk Management
• Towards Explainable Deep Learning for Credit Lending: A Case Study
• Explainable Artificial Intelligence Credit Risk Assessment using Machine Learning
• Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts
• PSD2 Explainable AI Model for Credit Scoring