Author(s)

Zhang Delin

Corresponding Author

Zhang Delin

Abstract

This article examines the application and effectiveness of artificial intelligence in credit assessment. The article first describes the emergence of artificial intelligence in the financial sector and then examines the limitations of traditional credit scoring methods, including data limitations, human biases and accuracy issues. The importance of credit assessment is then highlighted. The application of artificial intelligence to credit assessment is then examined in detail, including machine learning, natural language processing and block-chain technology. The impact of AI on credit assessment is then analysed, including improved accuracy, reduced bias and increased efficiency. Next, the article describes the challenges and risks faced, including data privacy, interpretation issues and reputational risk. Finally, the article discusses future trends, including the proliferation of artificial intelligence tools, evolving regulatory frameworks and the application of deep learning. These trends will continue to shape the financial sector and create opportunities and challenges for the financial system and borrowers.

Keywords

artificial intelligence; credit assessment; applications