Overview on Untargeted Methods to Combat Food Frauds: A Focus on Fishery Products by Giuseppina M. Fiorino, Cristiano Garino, Marco Arlorio, Antonio F. Logrieco, Ilario Losito, Linda Monaci

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A Credit Card Fraud Detection Algorithm Based on SDT and Federated Learning by Yuxuan Tang, Zhanjun Liu

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A systematic review of AI-enhanced techniques in credit card fraud detection by Ibrahim Y. Hafez, Ahmed Y. Hafez, Ahmed Saleh, Amr A. Abd El-Mageed, Amr A. Abohany

Subjects: “…Fraud attacks…”
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The Effect of Anti-fraud Socialization, Whistleblowing System, and Social Sanction on Assets Misappropriation by Rahmat Aiman, Roekhudin Roekhudin, Imam Subekti

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A taxonomia de fraudes em relatórios financeiros no mercado acionário brasileiro by Noel Kentinus Olokodana, Rodrigo de Souza Gonçalves, Monize Ramos do Nascimento

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E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review by Abed Mutemi, Fernando Bacao

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IMPACT OF FORENSIC ACCOUNTING SERVICES ON PREVENTING AND DETECTING FRAUD IN NIGERIAN DEPOSIT MONEY BANKS by Abdul-Hakeem Shuaib, Salaudeen Ibrahim

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Research on the effectiveness evaluation of cyber security curriculum construction for combating telecom network fraud by Shengli ZHOU, Keyi JIANG, Bo XU, Rui XU, Xikang ZHANG, Quanzhe ZHAO, Yangdong XU

Subjects: “…telecom network fraud…”
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EVOLUSI TEORI FRAUD DAN RELEVANSINYA TERHADAP STRATEGI PENCEGAHAN KORUPSI DANA DESA by Satya Fauziah

Subjects: “…Teori Fraud…”
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FORENSIC ACCOUNTING AND PUBLIC PROCUREMENT FRAUD PREVENTION: EVIDENCE FROM OSUN STATE, NIGERIA by Aderemi Olalere ADEBAYO, Oluwatimileyin Esther ADENLE, Ayodele David OJELEYE, AYENI AYENI

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RELEVANCE OF FORENSIC ACCOUNTING PROFESSIONAL CERTIFICATIONS ON FRAUD REDUCTION IN NIGERIAN DEPOSIT MONEY BANKS by Kamaluddeen Funsho Adisa IBRAHIM

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Metaverse crimes in virtual (Un)reality: Fraud and sexual offences under English law by Andreas Karapatakis

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Fraud Detection in Cryptocurrency Networks—An Exploration Using Anomaly Detection and Heterogeneous Graph Transformers by Víctor Pérez-Cano, Francisco Jurado

“…This article will address the problem of identifying fraud cases among a large set of transactions extracted from the Bitcoin network. …”
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A stacked ensemble approach with resampling techniques for highly effective fraud detection in imbalanced datasets by Idongesit E. Eteng, Udeze L. Chinedu, Ayei E. Ibor

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Scientific discussions on conducting different types of examination during the investigation of fraud in the field of electronic payments by M. V. Lepei

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Efficient Handling of Data Imbalance in Health Insurance Fraud Detection Using Meta-Reinforcement Learning by Supriya Seshagiri, K. V. Prema

“…Data imbalance is one of the major challenges in health insurance fraud detection where the distribution of classes within the dataset is significantly skewed, leading statistical models to be biased toward the dominant class. …”
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Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data by Jian Liu, Xin Gu, Chao Shang

“…At present, there are more and more frauds in the financial field. The detection and prevention of financial frauds are of great significance for regulating and maintaining a reasonable financial order. …”
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Indonesian Governors’ Gender, Age, Education Level, Educational Background, Tenure and Their Tendency of Conducting Fraud by Sri Elviani, Ramadona Simbolon, Farida Khairani Lubis, Lusi Elviani Rangkuti, Ismail Nasution

“…The results of this study indicate that the governors with accounting background are more likely not to be involved in fraud, while tenure has no effect on fraud. An interesting finding was obtained that education level and age have a negative effect on fraud. …”
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Machine Learning Based Method for Insurance Fraud Detection on Class Imbalance Datasets With Missing Values by Ahmed A. Khalil, Zaiming Liu, Ahmed Fathalla, Ahmed Ali, Ahmad Salah

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Compras públicas no Brasil: Indícios de fraudes usando a lei de Newcomb-Benford by Adilson Sampaio, Paulo Figueiredo, Elisabeth Loiola

“…O estudo, pioneiro nesse tipo de análise na base de dados brasileira, visa a contribuir para a literatura focada na detecção de fraudes contábeis ou financeiras no setor público. …”
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