Claims adjusters manually sift through narrative reports to detect fraud. This process is slow, inconsistent, and expensive.
Legacy fraud detection relies on keyword spotting and adjuster intuition. High false positive rates bury valid claims in unnecessary review queues.
Teams spend 70% of time reading narratives, not investigating. No deterministic pattern matching exists—each adjuster applies rules differently. Scaling requires headcount, not automation.
Senrok engineers deploy a hybrid system: rule-based NLP tokenizers extract structured entities (claimant statements, timeline gaps, witness inconsistencies). A decision graph then routes narratives to specialist adjusters or automated verification steps.
Every flag is explainable. No black-box LLM output. The system uses predefined thresholds (e.g., 'contradiction score > 0.85') and human-in-the-loop validation for edge cases. Audit trails record every decision path.
We apply configurable token mapping and fuzzy matching rules. Adjusters can add domain-specific synonyms without retraining. Edge cases are flagged for manual rule refinement.
Yes. Senrok deploys as a containerized microservice with REST APIs. We map to your existing data schemas and workflow triggers. No migration needed.
Our determinism prevents adversarial tricks. Every rule is transparent and testable. If a pattern evades detection, we write a new rule—no model drift, no black-box failure.
Engineering services
Claims Narrative Fraud Analysis is the kind of workflow we build as an AI agent system: deterministic checks, human checkpoints, and an audit trail operators can trust. We start from your real process boundaries and ship software that holds up in production.
We build production-ready, highly observable agentic systems engineered for enterprise scale. No black boxes, no magic—just systematized workflows with systemic safeguards.
We don't build fragile wrappers. Complex decisions and exceptions are automatically routed to your team for approval, ensuring zero unverified actions in production.
Every AI-generated output is validated against deterministic, programmatic rules before execution, guaranteeing structural integrity and compliance.
Our architecture records every state change, agent reasoning step, and user interaction, providing complete observability into your automated workflows.
Built for enterprise scale. We optimize for high-throughput, low-latency execution using edge infrastructure and efficient state management.
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