White Box Finance: Interpreting AI Decisions in Finance through Rules and Language Models

DeepLearningIndaba 2025 Workshop AIBF Submission10 Authors

Keywords: Explainability, AI in Finance, Finance, AI, XAI, White box

TL;DR: Methods for explaining a finance AI model.

Abstract:

Although loan defaults continue to cause substantial
financial losses, this study focuses on improving how AI
credit risk models are explained. Beyond developing a
predictive model based on the demographics of the borrower,
the attributes of the loan, and the credit history,
the core contribution lies in introducing and comparing
explanation methods. Specifically, we evaluated two
ways to provide explanations. One method is a module
that integrates SHAP values and GPT-4 to generate
human-friendly narratives, a second is a rule-based
logic explanation. This approach aims to enhance interpretability
and trust, offering a clearer understanding
of model predictions than traditional explanation techniques.

Submission Number: 10