Shift Technology

Shift Technology Architectural Analysis

Shift Technology operates as a vertical SaaS platform integrated into the insurance lifecycle, moving from traditional rule-based engines to a unified processing architecture driven by machine learning and computer vision 📑. The system architecture is designed to sit atop existing Core Systems (Policy Administration and Claims Management), acting as an intelligence layer rather than a replacement for record-keeping infrastructure 🧠.

Core Decision Intelligence Layer

The platform’s primary value proposition is its ability to synthesize unstructured and structured data to identify anomalies. This is achieved through several specialized modules:

• Automated Fraud Detection: Utilizes large-scale graph analysis to identify organized fraud networks across multiple claims and entities 📑. The specific graph database implementation remains a Managed Persistence Layer 🌑.
• Explainable AI (XAI) Framework: Generates human-readable justifications for every flagged indicator to satisfy regulatory audit requirements 📑. The logic for weighting conflicting indicators is proprietary 🌑.
• Agentic Orchestrator (2025): Designed to automate coordination with third-party service providers to facilitate straight-through processing ⌛.

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Operational Scenarios

• Fraud Ring Identification: Input: New claim data + historical cross-carrier records → Process: Graph analysis to identify shared phone numbers or addresses across unrelated entities → Output: Risk score + Explainable XAI report flagged for investigation 📑.
• Damage Assessment Automation: Input: Visual FNOL evidence (photos/video) → Process: Computer vision analysis for repair cost estimation and digital image tampering detection → Output: Automated repair estimate or referral to manual adjuster if anomalies are detected 📑.

Evaluation Guidance

Technical evaluators should verify the following architectural characteristics:

• FNOL API Latency: Benchmark the response time during First Notice of Loss ingestion to ensure real-time straight-through processing viability 🌑.
• Agentic Network Readiness: Verify the production status of autonomous coordination with repair networks versus manual workflow triggers ⌛.
• Data Isolation Protocols: Request documentation on the specific cryptographic or logical isolation protocols used when training cross-carrier fraud models 🌑.