InfDetect: a Large Scale Graph-based Fraud Detection System for E-Commerce Insurance

by   Cen Chen, et al.

The insurance industry has been creating innovative products around the emerging online shopping activities. Such e-commerce insurance is designed to protect buyers from potential risks such as impulse purchases and counterfeits. Fraudulent claims towards online insurance typically involve multiple parties such as buyers, sellers, and express companies, and they could lead to heavy financial losses. In order to uncover the relations behind organized fraudsters and detect fraudulent claims, we developed a large-scale insurance fraud detection system, i.e., InfDetect, which provides interfaces for commonly used graphs, standard data processing procedures, and a uniform graph learning platform. InfDetect is able to process big graphs containing up to 100 millions of nodes and billions of edges. In this paper, we investigate different graphs to facilitate fraudster mining, such as a device-sharing graph, a transaction graph, a friendship graph, and a buyer-seller graph. These graphs are fed to a uniform graph learning platform containing supervised and unsupervised graph learning algorithms. Cases on widely applied e-commerce insurance are described to demonstrate the usage and capability of our system. InfDetect has successfully detected thousands of fraudulent claims and saved over tens of thousands of dollars daily.


page 2

page 3

page 4

page 5

page 6

page 7

page 8

page 9


Uncovering Insurance Fraud Conspiracy with Network Learning

Fraudulent claim detection is one of the greatest challenges the insuran...

Correlating Medi- Claim Service by Deep Learning Neural Networks

Medical insurance claims are of organized crimes related to patients, ph...

Delator: Automatic Detection of Money Laundering Evidence on Transaction Graphs via Neural Networks

Money laundering is one of the most relevant criminal activities today, ...

Conceptualize and Infer User Needs in E-commerce

Understanding latent user needs beneath shopping behaviors is critical t...

Enhancing Product Safety in E-Commerce with NLP

Ensuring safety of the products offered to the customers is of paramount...

When Fashion Meets Big Data: Discriminative Mining of Best Selling Clothing Features

With the prevalence of e-commence websites and the ease of online shoppi...

ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases

Low-quality listings and bad actor behavior in online retail websites th...

Please sign up or login with your details

Forgot password? Click here to reset