Abstract
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.
Highlights
Credit management is the basis of the financial industry (Lin et al 2015)
We focus on four aspects: data volume, prediction correctness, service variety, and information protection
As compared with customers attracted through online channels, 100Credit’s model leads to about 70 % Nonperforming Loan (NPL) ratio reduction, as shown in testing by one of the banks.) Testing on a leading P2P lending company shows that the NPL ratio reduction is about 50 % to 70 %
Summary
Credit management is the basis of the financial industry (Lin et al 2015). When lenders provide loans to individuals or companies, they need to assess the borrowers’ credit risk to reduce the possibility of bad debt and decide the amount of the loan. Many private credit service providers in China use data collected from the Internet and other data sources. Their practices provide a good example of using Big Data technology to serve the financial industry. From 2010 to 2013, P2P platforms in China grew to number about 600 with a monthly investment of about 11 billion RMB In this stage, the platforms showed certain characteristics of private lending where borrowers often set a high interest rate and there was a lack of careful credit assessment. As of October 2014, they collected registrations for 19.63 million enterprises and identity information for 0.85 billion individuals in China Most of such information is not associated with credit-related activities, such as historical bank loan transactions, which are necessary for traditional credit rating models. The use of Big Data is a unique characteristic of Internet credit services
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