Insurance
Faster Adjuster Review with Intelligent Claims Validation
< 10 min
Latency from daily export to usable data
100%
Legacy dependency removed from the ingestion path
Automated
Replay, validation, and monitoring capabilities added
Client: The client, a leading equipment protection and insurance service provider, needed a faster, more consistent way to validate equipment insurance claims before adjusters began review. Fulcrum Digital used FD RYZE® validation agents and DocIntel extraction to check labor reasonability, parts pricing, contract terms, and work order details while keeping final decisions with adjusters.
The Challenge
Manual Validation Added Friction Before Every Claims Decision
The client needed adjusters to review equipment claims faster, but too much of the validation work still depended on manual lookup, PDF review, and individual judgment before a claim could move forward.
Labor-hour reasonability lacked consistency
Adjusters had to assess whether claimed labor hours were reasonable, but there was no standardized framework to compare them against historical claim patterns before review.
Parts pricing required manual comparison
Submitted parts prices had to be checked against available pricing references, adding repetitive lookup work before adjusters could evaluate the claim.
Contract terms slowed validation
Coverage, deductibles, exclusions, and other contract conditions had to be checked manually against claim details, creating extra effort before a decision could be made.
Work order PDFs created review drag
Key fields from work order PDFs had to be read and interpreted before adjusters could complete validation, making the process slower when document formats varied.
The Solution
A Claims Validation Layer Built Before Adjuster Review
Fulcrum Digital used FD RYZE® to create a background validation workflow that prepares claims before adjusters open the file. The solution combined document extraction, rules-based checks, historical comparison, and advisory findings so adjusters could review claims with clearer evidence and stronger control.
DocIntel-powered work order extraction
FD RYZE® DocIntel extracted and normalized key fields from work order PDFs as claims arrived, making document data available for validation without manual extraction.
Background validation workflow
FD RYZE® validation agents ran claims checks before adjuster review, bringing labor reasonability, parts pricing, and Nexus RAG-supported contract-term validation into one pre-review process informed by 2+ years of historical claim patterns.
Unified advisory adjuster view
Findings surfaced in a single adjuster view with reasoning chains, confidence signals, and accept/override controls, keeping the workflow advisory-only.
Audit-ready validation record
Validation outputs were stored in SQL Server with links to the claim, work order, and validation rule, creating a traceable record for review and audit needs.
Outcomes and Results
Clearer Claims Review Before the Adjuster Decides
| Validation Layer | What It Helps Adjusters See |
|---|---|
| Labor-hour reasonability | Whether claimed labor hours align with historical job patterns before review begins. |
| Parts pricing validation | Whether submitted parts prices fall within expected pricing ranges or need closer review. |
| Contract-term compliance | Whether coverage, deductible, and exclusion details align with the claim attributes. |
| Work order PDF extraction | Whether key work order fields are available in a structured format before review. |
| Advisory adjuster view | Whether to accept, override, or escalate an AI finding while retaining final decision authority. |
| Audit-ready validation record | How each finding connects back to the claim, work order, and validation rule. |
Why Fulcrum
What Made This Work
Claims logic translated into AI validation
Fulcrum brought the claims review logic into the AI workflow without reducing it to simple field matching. The approach reflected how adjusters actually assess reasonability, pricing, contract fit, and supporting documentation.
Evidence-led AI design
The goal was not to make the system look autonomous. Fulcrum focused on surfacing findings that adjusters could understand, challenge, and act on with clear reasoning behind each recommendation.
Control built for insurance decisions
Fulcrum kept human judgment at the center of the workflow. The system helped prepare the claim for review, but the adjuster still had the authority to accept, override, or escalate.
Traceability as a delivery requirement
Fulcrum treated auditability as part of the core build, not a final reporting layer. Each validation output needed to connect back to the claim, work order, and rule behind it.
FAQ
Frequently Asked Questions
Answers to the most common questions about the engagement, implementation approach, and business impact.
How can AI improve insurance claims validation?
AI can improve claims validation by checking labor reasonability, parts pricing, contract terms, and supporting documents before adjuster review, helping teams reduce manual lookup and review claims faster.
What is labor-hour reasonability in claims review?
Labor-hour reasonability checks whether the hours claimed for a repair align with expected patterns, historical claim data, or comparable job references before the adjuster makes a decision.
Why is human review important in AI-assisted claims validation?
Human review keeps claims decisions controlled and accountable. AI can surface findings, confidence signals, and supporting reasoning, but adjusters should retain authority to accept, override, or escalate.
How does FD RYZE® support intelligent claims validation?
FD RYZE® supports intelligent claims validation through background validation agents, DocIntel extraction, Nexus RAG-supported contract checks, advisory adjuster views, and traceable validation records.