Intelligent Pay-by-Bank Architecture: Fraud-Aware Analytics and Risk Modeling for U.S. Account-to-Account Payment Systems

Abstract

Pay-by-bank is moving from a niche alternative to a strategically important layer in the U.S. payments landscape. Its appeal is clear: direct account-to-account (A2A) transfers can reduce merchant acceptance costs, accelerate funds availability,  support recurring and bill-payment use cases, and create a pathway for open-banking-enabled checkout experiences that do not depend on card rails.  At the same time, the same structural strengths that make pay-by-bank attractive—irrevocability, speed, richer data exchange, API connectivity, and multi-party orchestration—also create distinctive fraud, operational, and consumer-protection risks. Unlike card networks, many pay-by-bank implementations cannot rely on mature chargeback mechanisms as a primary safety valve, which makes ex ante risk scoring, identity assurance, behavioral analytics, and post-transaction monitoring more important. This paper develops a framework for an intelligent pay-by-bank architecture for the United States, integrating fraud-aware analytics, explainable machine learning, graph-based entity resolution, sanctions and AML screening, and rail-aware control design across ACH, Same Day ACH, RTP, and FedNow-enabled flows.  Using official U.S. sources and contemporary scholarly research, the paper synthesizes the structural drivers of A2A growth, maps the major fraud typologies that threaten consumer and merchant adoption, and proposes a layered analytic design that joins customer risk, payment context, device and channel telemetry, open-banking consent events, account validation, and network intelligence into a unified decision stack.  The paper also advances a practical governance model centered on explainability, model-risk management, fairness, vendor oversight, and escalation workflows aligned to high-stakes payment decisions. The discussion argues that successful U.S. pay-by-bank adoption depends not only on rail availability but on trusted orchestration: institutions must combine real-time controls, adaptive thresholds, human review for ambiguous cases, and continuous learning from returns, disputes, fraud reports, and customer complaints.  The manuscript concludes that intelligent pay-by-bank systems can materially improve the safety and efficiency of U.S. A2A payments when technical architecture, controls, and governance are designed together rather than sequentially.