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Networked Markets, Fragmented Data: Adaptive Graph Learning for Customer Risk Analytics and Policy Design

https://doi.org/10.2139/ssrn.5991354
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User-Friendly Tail Bounds for Sums of Random Matrices
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Fighting Money Laundering With Statistics and Machine Learning
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Local Graph Partitioning using PageRank Vectors
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Exploring the Intersection of Machine Learning, Money Laundering, Data Privacy, and Law
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Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook
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Cluster Aware Graph Anomaly Detection
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Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction
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Black-Box Attack-Based Security Evaluation Framework for Credit Card Fraud Detection Models
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Microsoft Uses Machine Learning and Optimization to Reduce E-Commerce Fraud
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Could Good Intentions Backfire? An Empirical Analysis of the Bank Deposit Insurance
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Informal Lending in Emerging Markets
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Detecting Management Fraud in Public Companies
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Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
inferredcites →https://doi.org/10.1287/mnsc.2016.2489openalex-snapshot
GOTCHA! Network-Based Fraud Detection for Social Security Fraud
inferredcites →https://doi.org/10.1287/mnsc.2021.4248openalex-snapshot
Entrepreneurial Learning and Disincentives in Crowdfunding Markets
inferredcites →https://doi.org/10.1287/orsc.2014.0904openalex-snapshot
The Deterrence Effects of Vicarious Punishments on Corporate Financial Fraud
inferredcites →https://doi.org/10.1287/orsc.2021.1541openalex-snapshot
Hierarchical Inconsistency: A Monitoring Mechanism to Reduce Securities Fraud in Emerging Markets
inferredcites →https://doi.org/10.51594/farj.v7i1.1808openalex-snapshot
Exploring the role of Machine Learning and Deep Learning in Anti-Money Laundering (AML) strategies within U.S. Financial Industry: A systematic review of implementation, effectiveness, and challenges
inferredcites →https://doi.org/10.54254/2755-2721/2025.kl22287openalex-snapshot
Reinforcement Learning for Pattern Recognition in Cross-Border Financial Transaction Anomalies: A Behavioral Economics Approach to AML
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Explainable Machine Learning Pipelines for Customer Risk Scoring in Anti-Money Laundering: A Management and Governance Perspective
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