Adaptive Multi-Stage Fraud Detection System
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Solution Overview
Problem
Existing fraud detection systems in call centers are inadequate as they rely on pre-existing fraudster profiles, fail to detect fraud during initial call stages, are not flexible for diverse client requirements, and assume fraud manifests in specific ways, leading to inefficiencies and inaccuracies in identifying fraudulent calls.
Innovation Solution
A modular, multi-stage, hierarchical, and adaptive fraud detection system that dynamically loads and manages various fraud detection modules based on client-specific fraud risk profiles, employing different technologies at different stages of the call lifecycle to detect fraud proactively and accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fraudster database lookup approach is used, then the system can detect fraud when a match is found in the database, but the system cannot detect fraud from new fraudsters not present in the database
Solution Approach 1:
The system performs preliminary fraud detection actions during the IVR stage before the caller reaches a human agent. Voice print and phone print analysis are conducted in advance, creating baseline data that enables detection of both known and unknown fraudsters throughout the call lifecycle, not just when matching against existing database profiles
Solution Approach 2:
The system transitions from a static database lookup approach to a dynamic multi-stage detection process. Fraud detection capabilities are activated at different call stages (IVR, agent interaction, post-call) with varying technologies, allowing the system to adapt its detection strategy based on the evolving call context and fraud indicators
2Measurement precision
If voice print or phone print-based detection is used, then the system can identify known fraudsters, but the system is of little use to clients whose IVR applications are targeted by fraudsters using DTMF inputs
Solution Approach 1:
The fraud detection system is segmented into multiple independent modules that can be selectively activated. Voice print detection, phone print detection, and DTMF analysis are separate capabilities that can be applied based on the specific IVR scenario and fraud risk profile, allowing the system to serve diverse client requirements
Solution Approach 2:
The system creates a universal fraud detection platform that handles multiple fraud detection scenarios through a single integrated architecture. The same core system can apply different detection technologies (voice print, phone print, DTMF analysis) depending on the client's IVR application type and fraud risk profile
3Device complexity
If a single fraud detection approach is used, then the system is simpler to implement, but the system cannot be configured differently for different clients with different fraud detection accuracy requirements
Solution Approach 1:
The system applies local quality by allowing different fraud detection technologies and configuration parameters to be applied to different clients based on their specific requirements. Financial services clients can be configured with higher accuracy thresholds and multiple detection modalities, while other clients use simpler configurations, optimizing both accuracy and complexity for each local context
Data Source
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AI summary
A system and method for fraud detection and management are provided. The system includes a first communication device that receives a phone call from a second communication device, wherein a call flow of the phone call comprises one or more distinct phases. The system also includes a fraud detection and management system (FDMS) platform that determines whether the phone call exceeds a predetermined risk threshold at each distinct phase of the call flow.