Graph-Based Intelligence for Fraud Detection and Payment Transparency
Abstract
Detection, prevention, and control of fraud remain critical and urgent challenges for society and businesses. Fraud is interpreted as an act of deception intended to produce unlawful gain that may affect third parties involved in the transaction, such as banks, customers, and governments. Successful fraud detection enables law enforcement agencies to identify the perpetrators of active frauds and take appropriate actions. Payment transparency, on the other hand, is defined as the extent to which the origin and destination of payments in a payment system are known to relevant parties. Payment transparency enables banks to comply with public regulations, such as the prohibitions of money laundering and terrorist financing, and to demonstrate their commitment to combat such matters.
Fields of Study & Subjects
Advanced Graph Neural Networks
Privacy-Preserving Technologies in Data
Cybercrime and Law Enforcement Studies
Publication details
- Publication date
- 18 February 2026
- Language
- EN
- Document type
- Book chapter