NIGO Requirement Analysis - Field
Detects and resolves field-level errors in FNOL submissions.
Description
Challenge:
Field-level intake errors—such as missing policy numbers, incorrect DOBs, invalid claimant IDs, or wrong date formats—create heavy downstream rework and delays. These errors increase rejection rates, extend adjudication timelines, and expose insurers to compliance risks. Without early detection, clerical teams spend significant time resolving incomplete submissions, causing frustration for claimants and unnecessary cost escalation.
How It Works:
The NIGO Requirement Analysis Agent activates at FNOL or intake. It extracts structured data via IDP, applies NLP to validate semantic intent, and cross-checks each mandatory field against PAS, CRM, and policy rulebooks. The agent flags missing, malformed, or inconsistent inputs, generates structured NIGO reports, and sends precise corrective instructions to claimants or agents. It tracks resubmissions, clears corrected cases automatically, and escalates unresolved discrepancies based on SLA or risk impact.
Benefits:
85–95% automated detection accuracy for field-level NIGO issues
Cuts intake-to-adjudication delays by 50–70%
30% reduction in claim rejections due to incorrect intake data
40% faster claimant response time for correction guidance
Stronger auditability and fraud detection through early field validation
Resources
Features
The NIGO Requirement Analysis Agent ensures all FNOL and intake forms are complete, consistent, and policy-aligned before entering downstream claims workflows. By combining IDP, NLP, rules engines, and GenAI messaging, it prevents invalid cases from slowing adjudication.
Features & Capabilities:
Automated Field Extraction: Captures intake fields via IDP with confidence scoring.
Mandatory Field Validation: Ensures required identifiers (policy no., DOB, claimant info) are present.
Cross-Reference Matching: Confirms identifiers with PAS/CRM records.
Timeline Checks: Validates service/incident dates against coverage periods and waiting times.
Semantic Validation: Uses NLP to interpret free-text inputs and detect inconsistencies.
Correction Guidance: Generates clear claimant/agent instructions with sample formats.
SLA Tracking: Escalates unresolved discrepancies after deadline expiry.
Audit Logging: Maintains full history of errors, corrections, and escalations.
Fraud Signal Detection: Surfaces early mismatches in identity and claim linkage.
Operating Blueprint
Knowledge Sources:
Policy & Product Rulebooks: Defines mandatory fields, formats, and waiting periods.
Claim Form Templates & UI Definitions: Reference intake field structures.
Regulatory Field Mandates: Compliance requirements for data capture.
CRM/PAS Records: Master datasets for identity and policy validation.
Historical NIGO Repository: Error-resolution patterns and SLA benchmarks.
KYC & Identity Guidelines: Standards for validating insured and claimant data.
Business Rules:
Mandatory Field Rule: All required identifiers must be present.
Format Validation Rule: Data must match expected formats (regex for ID, date).
Cross-Match Rule: Policy/claimant details must align with CRM/PAS.
Timeline Rule: Treatment/incident dates must be within valid coverage.
Confidence Threshold Rule: Low-confidence fields (<80%) flagged for manual review.
Duplicate/Conflict Rule: Conflicting submissions flagged for resolution.
Priority Escalation Rule: High-risk/high-value discrepancies fast-tracked.
Resubmission SLA Rule: Enforces correction deadlines, escalates unresolved cases.
Tool Workflow:
Intake submission received at FNOL.
IDP extracts fields and applies confidence scoring.
Validation engine checks presence, format, and cross-matches.
NLP interprets free-text fields for consistency.
Rules engine applies product and regulatory requirements.
Agent generates structured NIGO report with corrective instructions.
Claimant/agent notified via portal, SMS, or email.
Resubmissions tracked, validated, and cleared or escalated.
All actions logged for analytics and audits.
Badges
Classification
