Claims Adjuster
Recorded Statements & Interviews
What You Do Today
Take recorded statements from the insured, claimant, and witnesses. Ask the right questions to establish facts, timeline, and liability. You're listening for inconsistencies, evasions, and details that don't match the physical evidence. A good recorded statement can make or break a disputed claim.
AI That Applies
AI transcription and summarization of recorded statements. NLP analysis that flags inconsistencies between statements, highlights key admissions, and compares the narrative to the physical evidence (damage photos, police report).
Technologies
How It Works
For recorded statements & interviews, the system compares the narrative to the physical evidence (damage photos. 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 interview itself.
What Changes
Transcription is instant instead of manual. The AI highlights 'the claimant said they were going 25mph but the damage pattern suggests 45+' — inconsistencies you might catch on re-read but the AI catches in real-time.
What Stays
The interview itself. The way you ask follow-up questions, the rapport you build, the instinct that tells you someone is hiding something from the way they pause. That's not automatable.
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 recorded statements & interviews, 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 recorded statements & interviews 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 claims director or VP Claims
“What data do we already have that could improve how we handle recorded statements & interviews?”
They're setting the automation strategy for your unit
your SIU lead
“Who on our team has the deepest experience with recorded statements & interviews, and what tools are they already using?”
AI fraud detection changes how investigations are triggered and prioritized
a claims adjuster with 15+ years experience
“If we brought in AI tools for recorded statements & interviews, what would we measure before and after to know it actually helped?”
Their judgment sets the benchmark that AI tools are measured against
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.