VP of Claims
Subrogation & Recovery
What You Do Today
Maximize recovery on claims — subrogation against third parties, salvage, and deductible recovery. Every dollar recovered improves the loss ratio, and the potential is often larger than companies realize.
AI That Applies
AI that identifies subrogation potential at FNOL by analyzing claim circumstances against subrogation success patterns. Automated recovery workflow management.
Technologies
How It Works
For subrogation & recovery, the system identifies subrogation potential at fnol by analyzing claim circumstanc. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The pursuit and negotiation.
What Changes
Subrogation potential identifies at first notice of loss instead of after settlement. The AI flags claims with high recovery probability based on loss circumstances, third-party identification, and historical recovery rates.
What Stays
The pursuit and negotiation. Recovering from a third party requires evidence gathering, legal judgment, and negotiation skill that goes beyond identification.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for subrogation & recovery, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long subrogation & recovery takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your board chair or lead independent director
“What data do we already have that could improve how we handle subrogation & recovery?”
They shape expectations for how AI appears in governance
your CTO or CIO
“Who on our team has the deepest experience with subrogation & recovery, and what tools are they already using?”
They own the technology infrastructure that enables AI adoption
a peer executive at a company further along on AI adoption
“If we brought in AI tools for subrogation & recovery, what would we measure before and after to know it actually helped?”
Their lessons learned are worth more than any consultant's framework
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.