Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models

arXiv:2310.00566v3 Announce Type: replace
Abstract: In the financial industry, credit scoring is a fundamental element, shaping access to credit and determining the terms of loans for individuals and businesses alike. Traditional credit scoring methods, however, often grapple with challenges such as narrow knowledge scope and isolated evaluation of credit tasks. Our work posits that Large Language Models (LLMs) have great potential for credit scoring tasks, with strong generalization ability across multiple tasks. To systematically explore LLMs for credit scoring, we …

abstract arxiv businesses challenges credit cs.ai cs.cl cs.cy cs.lg element evaluation financial financial industry industry knowledge language language models large language large language models loans narrow scoring terms through type