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A Memory-Enhanced Framework for Financial Fraud Detection
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018The rapid development of electronic financial services brings significant convenience to our daily life. However, it also offers criminals the opportunity to exploit financial systems to do fraudulent transactions. Previous studies on fraud detection only deal with single type transactions and cannot adapt well to evolving environment in reality.
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Towards Privacy Preserving Financial Fraud Detection
2023 International Conference on Machine Learning and Applications (ICMLA), 2023Stephanie Abanilla +2 more
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Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances
Expert Systems With Applications, 2022John Yawney +2 more
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Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019
Computer Science Review, 2021Pritheega Magalingam
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The Detection and Prediction of Financial Frauds
2022Xinzhu Wang, Yiran Li, Chenxing Liu
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Financial literacy and fraud detection——Evidence from China
International Review of Economics and Finance, 2021Weixing Wu, Ming Peng
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Financial Fraud Detection of Listed Companies in China: A Machine Learning Approach
Sustainability, 2023Chen Yasheng
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A user-centered explainable artificial intelligence approach for financial fraud detection
Finance Research Letters, 2023Xiao Zhi, Haoran Li
exaly
Detection Fraud of Financial Statement with Fraud Triangle
2013Manurung, Daniel T H, Hadian, Niki
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Big Data Analytics for Financial Frauds Detection.
2014Criminals and criminal organizations often make use of companies and other corporate entities to hide their identity, conceal illicit flows of money, launder funds, finance terrorist organizations, evade taxes, create and hide slash funds, commit bribery, corruption, accounting frauds and other financial crimes.
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