AI in Credit Scoring and Risk Assessment: Enhancing Lending Practices and Financial Inclusion

Artificial intelligence (AI) has become crucial in transforming credit scoring and risk assessment systems within the rapidly evolving financial services sector. This study explores how AI methods are incorporated into lending processes to improve financial inclusion and decision-making in financing. Based on firms’ past financial records, conventional credit rating systems should be updated to account for the complexities in assessing the creditworthiness of people and small enterprises, particularly those without an established credit background. Artificial intelligence has transformed how data is utilized by incorporating machine learning and deep learning algorithms to analyze diverse data sources, including unorthodox and unstructured data. This study comprehensively examines different AI methods used in credit and financial scoring, ranging from decision trees and neural networks to sophisticated deep learning and natural language processing techniques. The text delves into the mathematical foundations and algorithms that support AI models of these technologies and offers a comparative examination of several performance metrics. The article provides an in-depth analysis of the problems, opportunities, and future trends in AI credit scoring applications, emphasizing its potential to enhance transparency in credit availability and foster a more inclusive financial system.