Information collection for fraud detection in P2P financial market

TL;DR

This paper discusses a data collection framework tailored for fraud detection in the Chinese P2P financial market, highlighting unique challenges and solutions in web crawling for anti-fraud purposes.

Contribution

It introduces a specialized web data collection framework for P2P fintech fraud detection, addressing unique challenges in individual-based crawling requests.

Findings

Developed a full-fledged web crawler for anti-fraud data collection.

Outlined challenges and solutions in web data collection for fintech.

Enhanced data gathering capabilities for fraud detection in P2P markets.

Abstract

Fintech companies have been facing challenges from fraudulent behavior for a long time. Fraud rate in Chinese P2P financial market could go as high as 10%. It is crucial to collect sufficient information of the user as input to the anti-fraud process. Data collection framework for Fintech companies are different fro m conventional internet firms. With individual-based crawling request , we need to deal with new challenges negligible elsewhere . In this paper , we give an outline of how we collect data from the web to facilitate our anti-fraud process. We also overview the challenges and solutions to our problems. Our team at HC Financial Service Group is one of the few companies that are capable of developing full-fledged crawlers on our own.