Claims Triage Workflow
Last reviewed:
Quick Answer
The Claims Triage Workflow uses AI to evaluate incoming claims (FNOL), score complexity and risk, route to appropriate adjusters, and set initial reserves—all within seconds of claim submission. This workflow reduces manual triage time from hours to seconds while improving routing accuracy.
Definition
Key Points
- Processes FNOL data from multiple channels automatically
- Scores complexity on 1-10 scale considering multiple factors
- Flags fraud risk and routes to SIU when appropriate
- Identifies subrogation opportunities immediately
- Matches claims to adjusters based on expertise and capacity
- Sets initial reserves using historical comparable claims
- Creates complete audit trail for regulatory compliance
- Completes in seconds vs. hours for manual triage
How It Works
FNOL Data Intake
Receive claim from any channel (phone, web, mobile, API). AI extracts structured data from unstructured sources.
Data Validation & Enrichment
Validate data completeness, retrieve policy details, check duplicates, enrich with external data (weather, location).
Complexity Scoring
Analyze claim characteristics: injury severity, damage extent, policy limits, jurisdiction, parties, liability. Output 1-10 complexity score.
Fraud Risk Assessment
Evaluate fraud indicators: timing, history, documentation, circumstances. Output fraud risk score, flag for SIU if warranted.
Subrogation Potential
Identify third-party liability indicators, score subrogation potential, flag high-value recovery opportunities.
Adjuster Matching
Route based on complexity, expertise needed, adjuster capacity, geography. Simple claims auto-process; complex to senior staff.
Initial Reserve Setting
Estimate reserves from claim characteristics and historical comparables. Provide confidence interval for adjuster review.
Audit Trail Creation
Log all decisions, scores, routing logic, data sources. Create immutable audit trail for compliance and QA.
Decision Logic Model
Inputs: FNOL data (claim description, photos, reports, parties), policy details (coverages, limits, exclusions), claimant history, location data, weather conditions, historical claims database
Policy Rules: State-specific handling requirements, policy coverage verification, deductible application, statute of limitations timelines, reserved authority thresholds
Constraints: Adjuster capacity limits, expertise matching requirements, fraud threshold escalation, subrogation minimum value thresholds, reserve authority limits
Outputs: Complexity score (1-10), fraud risk score, subrogation potential score, adjuster assignment, initial reserve amount, audit trail documentation
Exception Categories & Handling
- Incomplete FNOL Data: AI identifies missing required fields, sends automated request to claimant, holds claim in queue until data received.
- Policy Not Found: Escalates to CSR to verify policy status, flags for potential coverage issue, prevents incorrect processing.
- Catastrophe Event: Detects CAT event correlation, applies CAT-specific triage rules, routes to CAT team, bypasses normal workflow.
- High Fraud Risk: Immediately routes to SIU, preserves evidence, alerts senior management, applies enhanced documentation requirements.
- No Available Adjuster: Queues claim with priority score, alerts management to capacity issue, suggests overflow routing options.
When to Escalate to Human
- •Complexity score > 8/10 (requires senior adjuster expertise)
- •Fraud risk score > 75/100 (requires SIU investigation)
- •Multiple parties with disputed liability (requires legal review)
- •Claim value exceeds adjuster reserved authority
- •Policy interpretation ambiguity (requires management decision)
- •Death, serious injury, or litigation potential (requires immediate senior review)