Proceedings of the International Workshop on Navigating the Digital Business Frontier for Sustainable Financial Innovation (ICDEBA 2024)

<Previous Article In Volume
Next Article In Volume>

The Role of Alternative Data in Credit Risk Prediction

Authors
Zhaoyan Chen1, *
1School of Economics, Guangdong University of Technology, 510520, Guangzhou, China
*Corresponding author. Email: 3222008204@mail2.gdut.edu.cn
Corresponding Author
Zhaoyan Chen
Available Online 24 February 2025.
DOI
10.2991/978-94-6463-652-9_76How to use a DOI?
Keywords
Alternative data; Credit risk prediction; Big data
Abstract

With the fast development of FinTech and big data technology, alternative data is sweeping the world at a rapid pace and plays an important role in credit risk prediction. At present, many lending institutions can use alternative data, a non-traditional emerging data, to forecast credit risk. This paper aims to review the literature on the research topic ‘The role of alternative data in credit risk prediction’, finding the similarities and differences between these documents. The results show that personal psychological information, digital footprint and consumer credit information in alternative data can help banks and other lending institutions to predict credit risk, as well as greatly reduce and control the credit risk. However, the current research in this field has limited research data, small sample size, the interpretability and performance of the constructed models and algorithms need to be improved, and the factors of cost and profit are not considered. The purpose of this paper is to provide reference for the future research.

Copyright
© 2025 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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Workshop on Navigating the Digital Business Frontier for Sustainable Financial Innovation (ICDEBA 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
24 February 2025
ISBN
978-94-6463-652-9
ISSN
2352-5428
DOI
10.2991/978-94-6463-652-9_76How to use a DOI?
Copyright
© 2025 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.

Cite this article

risenwbib
TY  - CONF
AU  - Zhaoyan Chen
PY  - 2025
DA  - 2025/02/24
TI  - The Role of Alternative Data in Credit Risk Prediction
BT  - Proceedings of the International Workshop on Navigating the Digital Business Frontier for Sustainable Financial Innovation (ICDEBA 2024)
PB  - Atlantis Press
SP  - 725
EP  - 732
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-652-9_76
DO  - 10.2991/978-94-6463-652-9_76
ID  - Chen2025
ER  -