Arun Palanisamy

Adaptive Hybrid Fraud Detection for Real Time Digital Payments

Abstract:

As global digital payment volumes exceed 1.5 trillion transactions annually in 2025, fraud losses surpassing $40 billion demand more intelligent and scalable detection approaches. Traditional rule based systems remain fast and transparent, yet they struggle against synthetic identities, account takeovers, and AI generated deepfakes. These limitations often result in 20 to 30 percent false positives, increasing operational costs and negatively affecting user experience.

This session presents an adaptive hybrid fraud detection framework that integrates rule based controls with behavioral analytics, geofencing, and machine learning driven optimization. By combining supervised and unsupervised models, the system continuously refines detection logic based on evolving transaction patterns while preserving decision transparency and real time performance.

Pilot implementations in leading banks demonstrate a 40 percent reduction in false positives and fraud detection accuracy above 95 percent, while maintaining decision times under 50 milliseconds. A comparative evaluation of rule based, machine learning, and hybrid architectures shows that hybrid models achieve up to 98 percent accuracy and reduce operational costs by 25 percent.

Use cases across banking, e commerce, and payment processing environments highlight scalability, regulatory alignment including PCI DSS and AML requirements, and measurable improvements in approval rates and customer trust. Attendees will gain a practical roadmap for deploying adaptive fraud detection systems within modern information technology and artificial intelligence ecosystems.

Profile:

Arun Palanisamy is a seasoned payment industry professional with over 16 years of expertise in payment processing systems, spanning retail, restaurant, AFD, and transit payment solutions. He is recognized as a subject matter expert in EMV, NFC, 3D-Secure, and wallet-based tokenization technologies, with extensive knowledge of payment network configurations for POS and ATM, as well as hands-on experience with Visa, Mastercard, American Express, Discover, FirstData-Fiserv, and WorldPay. Throughout his career, Arun has combined strong business and technical acumen to drive product development, testing and certification, compliance, and strategic delivery. He currently serves as a Subject Matter Expert and Payment Networks Support Specialist at InComm Payments, where he has led the implementation of innovative projects such as dateless EMV/NFC cards, advanced fraud detection engines, tokenization, and 3D-Secure systems. Previously, at Accenture US Technology Solutions for First Data USA, he specialized in production support and IT infrastructure planning, playing a key role in the development of Google Wallet and the Offerwise Redemption Platform. With deep expertise in ISO standards (8583, 20022, 14443, 7816), payment switching, fraud monitoring, reconciliation, and disputes management, Arun also brings strong program management and advisory experience. An active member and panelist in various payments forums, Arun continues to contribute to shaping the future of secure, innovative, and efficient digital payments.