Graph-Based Intelligence for Fraud Detection and Payment Transparency

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Authors: Bindu Madhavi Mangalampalli
Cited by: 0
References: 1

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