AI-Powered Credit Scoring Models: Transforming Financial Inclusion in Rural India

Abstract

This paper discusses the role of AI in enhancing financial inclusion in rural India by implementing AI-powered credit scoring models. Traditional credit scoring systems are often inaccessible to rural populations due to a lack of financial history. AI models, particularly machine learning algorithms such as Random Forest, Gradient Boosting, and Neural Networks, offer alternative methods to assess creditworthiness by analyzing non-traditional data sources such as mobile usage, social media activity, and transaction histories. The study examines the effectiveness of AI-driven credit scoring systems implemented by Indian fintech companies, focusing on their impact in improving access to credit for small-scale farmers and rural entrepreneurs. The paper also addresses the ethical implications, including privacy concerns, algorithmic bias, and the need for regulatory frameworks to govern AI-based credit scoring systems. By highlighting case studies from rural India, the paper demonstrates how AI can be a game changer in bridging the financial inclusion gap and contributing to India's economic growth.