Fair lending needs explainable models for responsible recommendation

TL;DR

This paper emphasizes the importance of developing explainable models in fair lending to address compliance and ethical challenges in credit decisioning, advocating for responsible use of AI in finance.

Contribution

It highlights the need for explainable AI models in fair lending, addressing industry-specific fairness and transparency challenges.

Findings

Explainability is crucial for compliance and ethics in credit decisions.

Current AI methods face challenges in financial fairness and transparency.

Responsible AI models can improve trust and fairness in lending.

Abstract

The financial services industry has unique explainability and fairness challenges arising from compliance and ethical considerations in credit decisioning. These challenges complicate the use of model machine learning and artificial intelligence methods in business decision processes.