Claims Processing Experiment
AI-powered document extraction and intelligent routing can reduce claims cycle time by at least 40% and eliminate manual EOI review for straightforward applications.
60%
Cycle Time Reduction
45 days → 18 days
90%
Touchless EOI Rate
From 12% baseline
6
Weeks to Production
Vs 6-month estimate
$4.2M
Annual Savings
Validated at scale
Legacy Systems Creating Operational Bottlenecks
One of America's largest insurance providers was struggling with a fragmented technology landscape. Their claims processing relied on manual data entry across 12 different systems, leading to average cycle times of 45 days for complex claims.
Evidence of Insurability requests were particularly problematic. Each application required manual review, with adjusters spending 40+ minutes per case copying data between systems. Only 12% of EOI applications were processed without human intervention.
The operational inefficiency was impacting customer satisfaction. NPS scores had declined for three consecutive quarters, and the company was losing market share to more agile competitors.
Phased Rollout Across Regional Offices
We designed a phased experiment starting with 3 regional offices (representing 15% of total claims volume) before expanding to all 12 locations.
The experiment measured end-to-end cycle time, touchless processing rate, error rates, adjuster satisfaction, and customer NPS. We established 90-day baselines before deployment and tracked metrics weekly.
To ensure statistical validity, we used matched-pair analysis comparing similar claim types and complexity levels between treatment and control groups.
Measured Variables
AI-Powered Integration Platform
We deployed Phoenix AI Platform to create an intelligent integration layer connecting all 12 legacy systems. Rather than a costly rip-and-replace approach, we built AI agents that could navigate existing interfaces.
For claims processing, we implemented intelligent document extraction that automatically identifies claim types, extracts relevant data with 98.5% accuracy, and routes cases to appropriate adjusters.
The EOI automation solution uses machine learning to assess applications against underwriting guidelines, automatically approving straightforward cases and flagging edge cases for human review.
Results Exceeded Hypothesis Targets
Within six weeks, the platform was processing 80% of claims without manual intervention—double our initial target. The remaining 20% arrived at adjusters with complete context, reducing their handling time by 65%.
EOI automation exceeded expectations, with 90% of applications receiving instant decisions. The 10% requiring human review came with AI-generated recommendations that adjusters approved 94% of the time.
Customer satisfaction rebounded dramatically, with NPS scores improving by 23 points in the first quarter post-implementation.
“The Phoenix platform didn't just improve our operations—it transformed how our team thinks about work. Our adjusters are now focused on complex cases that genuinely need human judgment, while AI handles the routine.”
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