The Investigation of Credit Score Evaluation Based on Machine Learning Methods

DOI

10.2991/978-94-6463-512-6_73How to use a DOI?

Keywords

credit score; machine learning; deep learning

Abstract

With advancements in artificial intelligence and finance, numerous academics have delved into credit risk assessment using machine learning techniques. Credit scores are vital for the stability of financial institutions both in China and abroad. Traditional methods of identifying user defaults can no longer accommodate the diverse data types, large user volumes, and high accuracy needed for modern risk prediction. Many scholars have employed machine learning methods, yielding significant research results that demonstrate these techniques’ strong predictive and generalization capabilities. Consequently, conducting a literature review and researching development trends in this area is of great importance. This review can offer valuable insights into the evolving landscape of credit risk assessment and highlight the benefits and challenges associated with the integration of machine learning in this field. By understanding these developments, financial institutions can enhance their risk management strategies, ultimately contributing to a more stable and efficient financial system. The ongoing research in this domain underscores the potential of machine learning to revolutionize credit risk assessment and drive innovation in financial services.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yukun Qiao
PY  - 2024
DA  - 2024/09/23
TI  - The Investigation of Credit Score Evaluation Based on Machine Learning Methods
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
PB  - Atlantis Press
SP  - 699
EP  - 703
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-512-6_73
DO  - 10.2991/978-94-6463-512-6_73
ID  - Qiao2024
ER  -