Input Profile Records for Authorized Fraud Detection

The system segments fraud detection into two distinct pathways: conventional fraud detection for unauthorized users and authorized fraud detection for legitimate users. This is achieved by creating separate detection mechanisms that analyze different feature sets - traditional authentication features versus behavioral biometric features captured through input profile records. The segmentation allows each pathway to be optimized independently, resolving the contradiction between maintaining high user identification accuracy while detecting authorized fraud.

The system introduces an intermediary layer - the input profile record (IPR) - that captures behavioral biometric data during normal user interactions. This intermediary structure serves as a mediator between the authorized user's legitimate actions and the fraud detection system. By analyzing subtle behavioral patterns in the IPR data, the system can detect authorized fraud without compromising the primary authentication mechanism, thus maintaining user identification accuracy while enabling new fraud detection capabilities.

The system implements self-service by capturing behavioral biometric data passively during normal user interactions without requiring additional user actions or specialized hardware. The input profile record automatically records keystroke dynamics, typing patterns, and other behavioral features as users naturally interact with the system. This self-service approach enables sophisticated fraud detection while minimizing system complexity, as the data collection infrastructure leverages existing user interfaces and interaction patterns.

The system changes the parameters being monitored from traditional authentication credentials to behavioral biometric parameters captured in input profile records. By shifting focus to temporal and behavioral characteristics of user interactions - such as keystroke timing, pressure patterns, and typing rhythm - the system achieves high fraud detection accuracy using data already generated during normal operations. This parameter change avoids the need for complex additional sensing infrastructure.