Applying Spatio-temporal Analysis in Telecom Fraud Investigation

Abstract

Recently telecom fraud has become a severe problem worldwide, resulting in billions of dollars each year. To prevent telecom fraud, Taiwan National Police Agency proposes an Anti-money Mule Project to detect and arrest mules responsible for withdrawing victims’ ATM cash from telecom fraud. This study used the Python program to integrate visual data for the following three significant phases: time series, spatial connection, and geographic map data. These phases can analyze 2,238 remittance accounts that were withdrawn transaction records by the money mules. Our research results have demonstrated that Spatio-temporal analysis could help investigators linkage transaction records by the same money mule, narrow down the scope of the investigation, and increase the possibility of finding out the suspect. The Spatio-temporal analysis is successfully applied as a systematic, proactive investigation technique in Taiwan’s telecom fraud investigation.