The Challenges of Using Big Data in the Consumer Credit Sector

P. 221–231.

Romanyuk K.

Credit risk analysis is essential in banking, and it relies on data. Multiple novel types of data are getting more popular for credit risk analysis in the consumer lending sector. On the one hand, the application of big data can increase the predictive power of credit risk analysis and reduce information asymmetry in the consumer lending market. On the other hand, more data types require better cyber-security, a more specific legal system for protecting consumers’ privacy and promoting high standards of corporate ethics. This paper is focused on the challenges in the application of novel data in credit scoring. Concentrating big data including highly sensitive personal information in one place creates a high value target for hackers. For example, the credit bureau Equifax had a gigantic data breach in 2017, that exposed highly valuable information for more than half of adult US citizens. The data breach is described, including the potential value of private information that was compromised and the company’s actions in terms of cyber-security and ethics, prior to and after the breach.

Keywords: privacy, ethics, cyber security, кибербезопасность, credit bureau, кредитное бюро

Publication based on the results of: Model Risks in Financial Risk Estimation Problems (2021)

In book

Intelligent Computing: Proceedings of the 2021 Computing Conference

Vol. 2. , Springer, 2021.