Value of Big Data to Finance: Observations on an Internet Credit Service Company in China

Shaofeng Zhang; Wei Xiong; Wancheng Ni; Xin LI

doi:10.1186/s40854-015-0017-2

Value of Big Data to Finance : Observations on an Internet Credit Service Company in China

Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review

Overview

16 Scopus Citations

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Author(s)

Shaofeng Zhang
Wei Xiong
Wancheng Ni
Xin LI

Related Research Unit(s)

Department of Information Systems

Detail(s)

Original language	English
Article number	17
Journal / Publication	Financial Innovation
Volume	1
Online published	24 Dec 2015
Publication status	Published - 2015

Link(s)

DOI	DOI https://doi.org/10.1186/s40854-015-0017-2 Final Published version
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Attachment(s)	Documents Final Published Version Final Published version, 1.06 MB, PDF Publisher's Copyright Statement This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-85057968483&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(bc79a66d-bc09-47f8-9c23-4dff7e98827b).html

Abstract

Background:

his paper presents a case study on 100Credit, an Internet credit service provider in China. 100Credit began as an IT company specializing in e-commerce recommendation before getting into the credit rating business. The company makes use of Big Data on multiple aspects of individuals’ online activities to infer their potential credit risk.

Methods:

Based on 100Credit’s business practices, this paper summarizes four aspects related to the value of Big Data in Internet credit services.

Results:

1) value from large data volume that provides access to more borrowers; 2) value from prediction correctness in reducing lenders’ operational cost; 3) value from the variety of services catering to different needs of lenders; and 4) value from information protection to sustain credit service businesses.

Conclusion:

The paper also discusses the opportunities and challenges of Big Data-based credit risk analysis, which needs to be improved in future research and practice.