Secure Complaint Intake Systems: Balancing Fraud Detection and Customer Experience

Abstract

Secure complaint intake systems have emerged as critical infrastructures in industries where customer trust, regulatory compliance, and operational transparency are paramount. While digital complaint channels such as online forms, mobile applications, and chatbots have increased accessibility, they have also created opportunities for fraudulent submissions, identity theft, and manipulative complaint practices. Organizations face the dual challenge of ensuring robust fraud detection without compromising customer experience, fairness, and responsiveness. This study explores the architectural frameworks, technological mechanisms, and governance models that underpin secure complaint intake systems. Drawing on multi-sectoral literature, the manuscript highlights the role of advanced analytics, artificial intelligence (AI)-powered fraud detection, and adaptive security controls in safeguarding intake processes. Simultaneously, it examines how human-centered design, trust-building communication, and complaint resolution efficiency contribute to maintaining positive customer experiences. The research underscores that balancing fraud prevention and customer satisfaction requires integrating regulatory compliance, user-centric design, and adaptive intelligence into complaint management platforms.