Case study — Claims
End-to-End Claims Lifecycle Automation
CLAIM IN PROGRESS
FNOL intake
LOSS TYPE
LOSS DATE
SEVERITY
NLP auto-classified
FNOL
Triage
Reserve
Pay
No inspection schedulingStraight-through
Cycle time
Manual21 days
AI-automated8 days
40% less reserving variance
60%
straight-through processing rate
21→8 days
average claim cycle time
40%
reduction in reserving variance

The Challenge

A national P&C insurer processing 500,000+ annual claims needed to reduce cycle time and operational costs while improving claimant experience. Their existing 21-day average close time was significantly above industry benchmarks.

First Notice of Loss (FNOL) was entirely manual, phone and web forms routed to human triagers.

Damage assessment required physical inspection scheduling, adding 5–7 days to every claim.

Reserve setting was inconsistent across adjusters, leading to leakage and reserving volatility.

Payment authorization required multi-level approval chains regardless of claim complexity.

The AidenAI Solution

AidenAI deployed a full-lifecycle agentic claims workbench that automated triage, AI damage assessment, reserve recommendations, and payment orchestration, while keeping adjusters in the loop for complex cases.

Intelligent FNOL intake with NLP-powered classification and automatic severity triage.

Computer vision damage assessment for auto and property claims, no inspection scheduling required for low-complexity claims.

AI reserve recommendation engine trained on 5 years of historical claims data, reducing reserving variance by 40%.

Automated straight-through payment for claims under $5,000 with no fraud flags.

Configurable adjuster workbench with full claim history, AI recommendations, and one-click approval.

Measurable Outcome

60%

Straight-through processing rate for low-complexity claims

21→8 days

Average claim cycle time reduction

40%

Reduction in reserving variance

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