Platform Risk and Payment Fraud Prevention in E Commerce Financial Ecosystems

Abstract

This article sets out an integrative decision framework for real time risk intervention in e commerce payments. Three linked problems motivate it: measurement that is fragmented across functions, uncertainty that is handled weakly, and a gap between commercial decision making and risk governance. A structured narrative synthesis assembles evidence from finance, analytics, technology, operations, governance, and sector-specific work. Six dimensions organize that evidence: identity assurance, transaction intelligence, merchant risk, network signals, adaptive controls, and customer friction. The focal decision criterion is fraud loss adjusted platform value, and the framework proposes an ordered sequence of data definition, baseline construction, causal or comparative estimation, risk adjustment, scenario testing, governance review, and post implementation learning. Isolated efficiency or revenue measures prove insufficient on their own, because they leave out implementation costs, tail losses, customer effects, and timing. What the article offers is a reusable architecture that ties economic evaluation to accountable execution, together with research propositions, measurement fields, validation tests, and reporting practices that empirical work can take up. No confidential company data are used, and no causal claim is made about any named employer. The central implication is that decision quality rises when value, risk, behavior, and control effectiveness are judged inside a single auditable model.