Financial Fraud Detection

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Overview

Financial fraud detection studies how to identify deceptive activity in payments, banking, insurance, markets, and digital assets, often when fraud is rare and its patterns change over time. Common approaches include gradient-boosted models and anomaly detection on transaction features, graph neural networks for relationships among accounts and transactions, and temporal or sequence models; synthetic data, federated learning, and language models are also used. Methods are evaluated on benchmarks such as credit-card transaction datasets, cryptocurrency graphs, and simulated anti-money-laundering networks, with attention to precision-recall and the number of alerts investigators can handle. A central challenge is whether reported gains hold under chronological, leakage-safe evaluation and real operational constraints, where delayed or incomplete labels, distribution shift, privacy, and false alarms all affect deployment.

Latest papers

CardsList

137 papers20 papers in the last four weeks, up 33% on the four weeks before. 0.1% of all new papers.

  1. TED: Related Party Transaction guided Tax Evasion Detection on Heterogeneous Graph

    May 26, 2026Yiming Xu, Bin Shi, Bo Dong +3Graph Attention NetworksHeterogeneous GNNs

    School of Computer Science and Technology, Xi’an Jiaotong University, Shaanxi, China. · School of Distance Education, Xi’an Jiaotong University, Shaanxi, China. · School of Computing and Augmented Intelligence, Arizona State University, Phoenix, USA.

  2. Innovations in Cardless Artificial Intelligence Banking: A Comprehensive Framework for Cyber Secure and Fraud Mitigation using Machine Learning Algorithms

    May 21, 2026Md IsrafeelFinancial ServicesFinancial Fraud Detection

    Dept. Electrical and Computer Engineering, University of Central Florida, Orlando, Florida, USA

  3. SilIF: Silhouette-Augmented Isolation Forest for Unsupervised Transaction Fraud Detection

    May 21, 2026Venkatakrishnan GopalakrishnanTabular Anomaly DetectionIsolation Forest

    Independent Researcher Redmond, WA, USA

  4. Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection

    May 20, 2026Adam Innan, Mansour El Alami, Nouhaila Innan +2Class-Imbalanced LearningSynthetic Data Augmentation

    Quantum Physics and Spintronics Team, LPMC, Faculty of Sciences Ben M’sick, Hassan II University of Casablanca, Morocco · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, UAE

  5. SCAFDS: Edge-Feature Graph Attention for Interbank Fraud Detection with Attribution-Grounded SAR Generation

    May 17, 2026Mohammad Nasir UddinGraph Attention NetworksFinancial Fraud Detection

    Taskimpetus Inc., Los Angeles, CA 90020, USA

  6. Graph-Driven Cross-Industry Real-Time Monitoring Framework for Anti-Money Laundering Detection in Converged Mobility-Energy Supply Chain Networks

    May 13, 2026Rong Liu, Xiaojun Xiao, Zhanqing SuTemporal GNNsHeterogeneous GNNs

    Sol Price School of Public Policy, University of Southern California, Los Angeles, USA · Boston University, Boston, USA · Johns Hopkins University, Washington, USA

  7. Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

    May 12, 2026Yunfei Nie, Jiawei Wang, Ruobing Yan +3Graph Neural NetworksGraph Representation Learning

    Brandeis University, Waltham, USA · University of California, Los Angeles, USA · Georgetown University, Washington, D.C., USA +2

  8. Rethinking LLMOps for Fraud and AML: Building a Compliance-Grade LLM Serving Stack

    May 11, 2026Prathamesh Vasudeo Naik, Naresh Dintakurthi, Yue WangLLM ServingFinancial Fraud Detection

  9. PumpSense: Real-Time Detection and Target Extraction of Crypto Pump-and-Dumps on Telegram

    May 10, 2026Ahmed Mahrous, Roberto Di PietroSocial Media AnalysisNamed Entity Recognition

    King Abdullah University of Science and Technology (KAUST) · Thuwal, Saudi Arabia

  10. ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

    May 9, 2026Wenbo Gao, Songbai Tan, Zhongan Wang +6Online Anomaly DetectionFinancial Fraud Detection

    Harbin Institute of Technology, Shenzhen · Shenzhen University · Zhejiang University +4

  11. FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

    May 9, 2026Xinyu Yan, Boyang Chen, Jiaming Zhang +12Image Forgery DetectionDigital Image Forensics

    College of Computing and Data Science, Nanyang Technological University · Alibaba-NTU Global e-Sustainability CorpLab (ANGEL) · Alibaba Group

  12. Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks

    Apr 27, 2026Lidia Losavio, Luca Persia, Madan Sathe +1Financial Fraud DetectionSpatiotemporal GNNs

    Faculty of Informatics, Universit`a della Svizzera italiana, Lugano, Switzerland · School of Management and Law, Zurich University of Applied Sciences, Zurich, Switzerland · Forensics and Financial Crime, Deloitte AG, Switzerland

  13. Do Transaction-Level and Actor-Level AML Queues Agree? An Empirical Evaluation of Granularity Effects on the Elliptic++ Graph

    Apr 26, 2026Ankur MalikFinancial Fraud DetectionAnti-Money Laundering

    Hudson Data, New York, NY, USA

  14. Scalable and Verifiable Federated Learning for Cross-Institution Financial Fraud Detection

    Apr 25, 2026Prajwal Panth, Nishant NigamFederated Learning AggregationCommunication-Efficient Distributed Training

    School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India · School of Electronics Engineering, KIIT Deemed to be University, Bhubaneswar, India

  15. Who Audits the Auditor? Tamper-Proof Fraud Detection with Blockchain-Anchored Explainable ML

    Apr 23, 2026Zhaohui WangData ProvenanceAlgorithmic Auditing

    Viterbi School of Engineering University of Southern California Los Angeles, CA, USA

  16. TRAVELFRAUDBENCH: A Configurable Evaluation Framework for GNN Fraud Ring Detection in Travel Networks

    Apr 22, 2026Bhavana SajjaHeterogeneous GNNsFinancial Fraud Detection

  17. Large Language Models Outperform Humans in Fraud Detection and Resistance to Motivated Investor Pressure

    Apr 22, 2026Nattavudh PowdthaveeFinancial Fraud DetectionLLM Decision-Making

    Nanyang Technological University

  18. When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift

    Apr 21, 2026Saket MagantiGraph Neural NetworksDistribution Shift

  19. TransXion: A High-Fidelity Graph Benchmark for Realistic Anti-Money Laundering

    Apr 19, 2026Keyang Chen, Mingxuan Jiang, Yongsheng Zhao +9Financial Fraud DetectionSynthetic Benchmark Generation

    Fudan University · Peking University

  20. Graph-Based Fraud Detection with Dual-Path Graph Filtering

    Apr 14, 2026Wei He, Wensheng Gan, Philip S. YuFinancial Fraud DetectionGraph Representation Learning

    School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China · Department of Computer Science, University of Illinois Chicago, Chicago 60607, USA

  21. Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation

    Apr 14, 2026Mohammad Nasir Uddin, Md Munna AzizFinancial Fraud DetectionEnsemble Learning

    Visual Data Analyst and Applied AI Researcher, Westcliff University, Irvine, CA, USA · Data Analyst and Applied AI Researcher, Westcliff University, Irvine, CA, USA

  22. A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

    Apr 14, 2026Mohammad Nasir UddinAI Regulatory ComplianceAI Governance

    Westcliff University, Irvine, California, USA

  23. Fraud Detection System for Banking Transactions

    Apr 9, 2026Ranya Batsyas, Ritesh YaduwanshiFinancial Fraud Detection

    Department of AI DS, IGDTUW, Delhi, India.

  24. Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation

    Apr 3, 2026Haseeb Tariq, Marwan HassaniAnti-Money Laundering DetectionAnti-Money Laundering

    ING Bank, Amsterdam, The Netherlands · Eindhoven University of Technology, Eindhoven, The Netherlands

  25. Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling

    Apr 1, 2026Haseeb Tariq, Alen Kaja, Marwan HassaniAnti-Money Laundering DetectionAnti-Money Laundering

    ING Bank Amsterdam, The Netherlands · Eindhoven University of Technology Eindhoven, The Netherlands · Identity & Risk Intelligence Adyen Amsterdam, The Netherlands +1

  26. Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding

    Mar 31, 2026Danny Butvinik, Yonit Marcus, Nitzan Tal +1Self-Supervised Time Series Representation LearningPredictive Representation Learning

    NICE Actimize

  27. LineMVGNN: Anti-Money Laundering with Line-Graph-Assisted Multi-View Graph Neural Networks

    Mar 24, 2026Chung-Hoo Poon, James Kwok, Calvin Chow +1Anti-Money Laundering DetectionFinancial Fraud Detection

    Logistics and Supply Chain MultiTech R&D Centre, Level 11, Cyberport 2, 100 Cyberport Road, Hong Kong · Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

  28. Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks

    Mar 22, 2026Dorothy Torres, Wei Cheng, Ke HuAnti-Money LaunderingAnti-Money Laundering Detection

    School of Science, Technology, Engineering and Mathematics 263 Academy Street, Room S204 Jersey City, NJ 07306 · School of Electrical Engineering and Computer Science, The Pennsylvania State University, 207 Electrical Engineering West, University Park, PA 16802, USA

  29. A Multi-Scale Graph Learning Framework with Temporal Consistency Constraints for Financial Fraud Detection in Transaction Networks under Non-Stationary Conditions

    Mar 15, 2026Yiming Lei, Qiannan Shen, Junhao SongFinancial Fraud DetectionSpatiotemporal GNNs

    Georgia Institute of Technology, Atlanta, GA, USA · Boston University, Boston, MA, USA · Imperial College London, London, UK

  30. DPxFin: Adaptive Differential Privacy for Anti-Money Laundering Detection via Reputation-Weighted Federated Learning

    Mar 14, 2026Renuga Kanagavelu, Manjil Nepal, Ning Peiyan +6Anti-Money Laundering DetectionDifferentially Private Federated Learning

    A*STAR IHPC Singapore · SRM University-AP Andhra Pradesh, India · EVYD Singapore