The Application of Alternative Data in Credit Scoring
- DOI
- 10.2991/978-94-6463-652-9_84How to use a DOI?
- Keywords
- Alternative data; Credit score; Digital footprint
- Abstract
This paper mainly combs the ideas and methods of various researches on the application of alternative data in credit scoring and classifies, summarizes and summarizes the research results, so as to provide more comprehensive information for the current researches on this subject and clearer research direction in the future. Using the literature review method, this paper mainly summarizes the relevant researches on the application of alternative data in credit scoring into three aspects: Application of digital footprint, Application of telecommunications data source, and Assessing credit through social networks data, and the important role and feasibility of alternative data in credit scoring. In addition, by sorting out relevant literature, the advantages and disadvantages of each study and the model itself are found, hoping to provide scholars with a more comprehensive understanding of this topic, and provide ideas and research directions for subsequent research by pointing out the shortcomings of current research and application.
- 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
TY - CONF AU - Xuanrui Zhang PY - 2025 DA - 2025/02/24 TI - The Application of Alternative Data in Credit Scoring BT - Proceedings of the International Workshop on Navigating the Digital Business Frontier for Sustainable Financial Innovation (ICDEBA 2024) PB - Atlantis Press SP - 789 EP - 794 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-652-9_84 DO - 10.2991/978-94-6463-652-9_84 ID - Zhang2025 ER -