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AI-Powered Fraud Prevention in Digital Payment Ecosystems: Leveraging Machine Learning for Real-Time Anomaly Detection and Risk Mitigation

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Abstract

Digital payment ecosystems have expanded rapidly over the past decade, transforming how businesses and consumers transact online.For example, the share of adults using digital payments in developing countries jumped from 35% in 2014 to 57% in 2021 [1].This widespread adoption of e-commerce platforms, mobile wallets, and real-time payment systems brings enormous convenience and economic benefits.However, it has also been accompanied by a rising prevalence of fraudulent transactions.Cybercriminals employ increasingly sophisticated tactics to exploit system vulnerabilities, resulting in staggering financial losses that threaten consumer trust and the integrity of digital

Topics & Concepts

Anomaly detectionComputer sciencePaymentArtificial intelligenceRisk managementMachine learningRisk analysis (engineering)Risk assessmentRisk preventionComputer securityAnomaly (physics)Feature (linguistics)Blockchain Technology Applications and Security