Loss Control Engineer
Perform catastrophe risk evaluations
What You Do Today
You assess properties for earthquake, wind, flood, and wildfire exposure, evaluating construction quality, secondary hazards, and business continuity preparedness.
AI That Applies
AI integrates satellite imagery, climate models, and catastrophe modeling outputs to provide detailed exposure assessments for individual properties and portfolios.
Technologies
How It Works
The system pulls operational data and maps it against risk frameworks, control requirements, and historical incident patterns. Computer vision models analyze the visual input by detecting objects, measuring spatial relationships, and comparing against trained reference patterns to identify matches or anomalies. The output — detailed exposure assessments for individual properties and portfolios — surfaces in the existing workflow where the practitioner can review and act on it.
What Changes
CAT exposure assessments become more granular when AI layers climate projections, building characteristics, and historical event data.
What Stays
Your on-the-ground assessment of whether this specific building will actually survive a Category 3 hurricane — models give probabilities, you give engineering reality.
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 perform catastrophe risk evaluations, 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 perform catastrophe risk evaluations 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 would have to be true about our data quality for AI to work reliably in perform catastrophe risk evaluations?”
They're setting the automation strategy for your unit
your SIU lead
“What would a pilot look like for AI in perform catastrophe risk evaluations — smallest possible test that would tell us something?”
AI fraud detection changes how investigations are triggered and prioritized
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.