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All Journal Asia Pacific Fraud Journal
Alham, Lalu
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Economics, Econometrics & Finance Social Sciences

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Fraud Syndicates Within Digital Ecosystem: Graph Network and Transaction Analysis Approach Irawandi, Ferdi Hidayat; Yohanes, Kristy Natasha; Alham, Lalu
Asia Pacific Fraud Journal Vol. 10 No. 1: 1st Edition (January-June 2025)
Publisher : Association of Certified Fraud Examiners Indonesia Chapter

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21532/apfjournal.v10i1.381

Abstract

This paper aims to develop and test methods to detect organized crime, fraud syndicates, and Money Laundering schemes within an e-wallet ecosystem. Analytical An analyticalprocess framework combining Graph Analytics and Supervised Learning is developed and trained with sample spaces of fraud and non-fraud. The pipeline utilized Heterogeneous Graph Transformation (HGT), Graph Statistics (Centrality Measures and Community Detection), and a Gradient Boosting Model to produce models for the detection of fraud syndicate syndicatesand organized crime. Welch’s t-test is employed to infer variance differences between samples. Findings confirm the hypothesis that fraud networks are markedly different, exhibiting a more centralized and isolated network compared to the organic, interconnected behaviors of non-fraudulent users. Fraud networks are further characterized by multiple isolated clusters, indicating distinctive groups or behaviors. The proposed method can provide validated methods of fraud and money laundering detection, especially for financial decision-makers and policymakers, to enhance fraud detection systems by improving the protection, integrity, and security of customers and digital transactions.
Co-Authors Irawandi, Ferdi Hidayat Yohanes, Kristy Natasha