Value of big data to finance: observations on an internet credit Service Company in China

被引：19

作者：

Zhang S. ^{[1
]}

Xiong W. ^{[1
]}

Ni W. ^{[2
]}

Li X. ^{[3
]}

机构：

[1] 100Credit Financial Information Service Co., Ltd, Beijing

[2] Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun E Rd, Beijing

[3] Department of Information Systems, City University of Hong Kong, Kowloon Tong

来源：

Financial Innovation | / 1卷 / 1期

关键词：

Big data; Credit rating; Finance; Information economics; Value of information;

D O I：

10.1186/s40854-015-0017-2

中图分类号：

学科分类号：

摘要：

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. © 2015, Zhang et al.

引用

共 39 条

[1]

The Development of Chinese Internet Financial Industry in 2014, (2014)

[2]

Agarwal R., Dhar V., Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research, Inform Syst Res, 25, 3, pp. 443-448, (2014)

[3]

Agarwal S., Hauswald R., Distance and Private Information in Lending, Rev Financ Stud, 23, 7, pp. 2757-2788, (2010)

[4]

Akerlof G., The Market for Lemons, Quarterly Journal of Economics, 84, pp. 488-500, (1970)

[5]

Barron J.M., Staten M., The value of comprehensive credit reports: Lessons from the US experience, Credit Reporting Systems and the International Economy, pp. 273-310, (2003)

[6]

Belanger F., Crossler R.E., Privacy in the Digital Age: A Review of Information Privacy Research in Information Systems, Mis Quart, 35, 4, pp. 1017-1041, (2011)

[7]

Birchler U., Butler M., Information Economics, (2007)

[8]

Brown M., Zehnder C., Credit reporting, relationship banking, and loan repayment, J Money Credit Bank, 39, 8, pp. 1883-1918, (2007)

[9]

Brown M., Jappelli T., Pagano M., Information sharing and credit: Firm-level evidence from transition countries, J Financ Intermed, 18, 2, pp. 151-172, (2009)

[10]

Chandler G.G.R.W.J., The Benefit to Consumers From Generic Scoring Models Based on Credit Reports, IMA Journal of Mathematics Applied in Business and Industry, 4, pp. 61-72, (1992)

← 1 2 3 4 →