Interpretation and Prospect of Personal Credit Evaluation Based on Big Data

In the current booming development of financial technology, in order to improve the quality of personal credit evaluation, enhance platform prediction efficiency, and improve the credit evaluation system, this article deeply explores effective methods for building a credit evaluation service platform. Compared with traditional financial data, these platforms fully leverage the significant characteristics of big data, such as large scale, rapid circulation, and diverse types. Through a comprehensive investigation of the current situation of personal credit evaluation in China and in-depth analysis of the key role played by big data in credit evaluation, important achievements have been made in the research. It not only lays a solid theoretical foundation for building a reliable and accurate AI driven evaluation system, but also provides valuable decision-making references for policy makers, helping them make scientific decisions in balancing technological innovation and data ethics, innovating data collection and usage methods, promoting cross platform data sharing, and effectively addressing opportunities and challenges in the field of credit evaluation.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-13
DOI
https://doi.org/10.1051/shsconf/202522503008/pdf
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
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article

Interpretation and Prospect of Personal Credit Evaluation Based on Big Data

Springer Link (Chiba Institute of Technology)
Financial Distress and Bankruptcy Prediction
article

Interpretation and Prospect of Personal Credit Evaluation Based on Big Data

article en

Abstract

In the current booming development of financial technology, in order to improve the quality of personal credit evaluation, enhance platform prediction efficiency, and improve the credit evaluation system, this article deeply explores effective methods for building a credit evaluation service platform. Compared with traditional financial data, these platforms fully leverage the significant characteristics of big data, such as large scale, rapid circulation, and diverse types. Through a comprehensive investigation of the current situation of personal credit evaluation in China and in-depth analysis of the key role played by big data in credit evaluation, important achievements have been made in the research. It not only lays a solid theoretical foundation for building a reliable and accurate AI driven evaluation system, but also provides valuable decision-making references for policy makers, helping them make scientific decisions in balancing technological innovation and data ethics, innovating data collection and usage methods, promoting cross platform data sharing, and effectively addressing opportunities and challenges in the field of credit evaluation.

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Financial Distress and Bankruptcy Prediction
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Interpretation and Prospect of Personal Credit Evaluation Based on Big Data · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS