Published Online:September 2026
Product Name:The IUP Journal of Information Technology
Product Type:Article
Product Code:IJIT040926
DOI:10.71329/IUPJIT/2026.22.3.60-91
Author Name:Abhishek Kumar
Availability:YES
Subject/Domain:Engineering
Download Format:PDF
Pages:60-91
The paper presents a systematic review of machine learning (ML) and data mining approaches for fraud detection with particular emphasis on the potential contribution of fraud triangle theory (FTT) to behavior-aware fraud analytics. The review synthesizes recent advances in supervised, unsupervised, deep learning (DL) , graph-based learning, explainable artificial intelligence (XAI), and privacy-preserving fraud detection, while examining how the behavioral dimensions of pressure, opportunity, and rationalization can complement computational intelligence techniques. Building on the insights obtained, the paper introduces the FTT-ML taxonomy and proposes the FTT-meta conceptual framework to establish structured relationships between behavioral fraud theory and contemporary ML methodologies. The framework is intended to support future development of interpretable, behavior-aware, and collaborative fraud detection systems capable of operating across heterogeneous digital environments. The review further identifies persistent research challenges, including the limited operationalization of behavioral theories, shortcomings in explainable fraud analytics, and the need for privacy preserving collaborative learning architectures. By integrating behavioral and computational perspectives, the proposed taxonomy and conceptual framework provide a theoretical foundation for future empirical investigations and contribute to the ongoing development of more transparent, adaptable, and human-centered fraud detection systems.
The widespread adoption of digital technologies has fundamentally transformed the way financial transactions, commercial activities, and social interactions are conducted. While this digital transformation has improved accessibility, efficiency, and connectivity, it has also expanded the opportunities available to fraudsters.