Trigger telecom fraud risk control measures

Can a new Internet and telecommunication fraud crime risk factor extraction system solve more cases?

To better analyze the Internet and telecommunication fraud crime to help solve more cases, in this paper, we propose a new Internet and telecommunication fraud crime risk factor extraction system. After studying the existing related research, we propose a novel risk factor extraction technology based on BERT.

What is the difference between telecommunication fraud and risk factor extraction?

Second, the Internet and telecommunication fraud crime information is mostly recorded using natural language in a textual form, with huge volume and diverse forms, while the existing risk factor extraction capability can mostly only deal with single-factor type extraction or at most several types of factor extraction.

What is a comprehensive fraud management system in Telecom?

Comprehensive Fraud Management System in Telecom: Utilizing AI and machine learning for dynamic fraud detection and prevention. Customized Consumer Protection Measures: Developing bespoke solutions that align with consumer needs and industry standards for security.

Why is telecom fraud hard to track?

Telecom fraud is hard to track due to its frequency, layers of anonymity, and global nature. According to the Federal Trade Commission, telecom fraud continues to account for more fraud complaints each year, with the latest schemes being particularly difficult to investigate.

Do Telecom fraudsters disguise themselves?

However, telecom fraud detection is a challenging task as fraudsters tend to commit co-fraud and disguise themselves within the mass of benign ones. Previous approaches work by unearthing differences in calling sequential patterns between independent fraudsters, but they may ignore synergic fraud patterns and oversimplify fraudulent behaviors.

How can we extract risk factors from Internet fraud cases?

Based on the proposed technology, we can implement an automatic extraction system to extract risk factors from huge volume of Internet and telecommunication fraud cases, which can further help the analysis, prediction, and early warning of new types of Internet frauds. The contribution of this paper is as follows: