Catastrophe Loss Reserve Estimation Support
When a catastrophe event hits — a hurricane, a wildfire, a major flood — the carrier needs a reasonable reserve estimate for the overall event exposure well before individual claims have actually been filed and adjusted, because financial reporting, reinsurance notification, and capital management decisions can't wait for claim-by-claim reserving to catch up over the following weeks. Building that early bulk estimate manually means pulling policy exposure data for the affected geography, overlaying it against the event's actual footprint and severity, and applying loss-development assumptions by hand under real time pressure, and the resulting estimate quality depends heavily on how fast and how carefully that manual analysis gets done in the days right after the event.
STARTING PRICE
From €799
Complex tier · Multi-system orchestration, custom logic, and higher-volume or higher-risk processing.
Get a quote →Saves roughly 10-20 hrs in the first week after a catastrophe event, versus fully manual bulk estimation.
How the automation works
We generate an early bulk reserve estimate by overlaying in-force policy exposure data for the affected geography against the catastrophe event's footprint and severity data as it becomes available, applying loss-development curves and exposure-based severity assumptions appropriate to the peril and region. The estimate updates as better event data arrives — more precise storm track or flood extent data, early field-adjuster reports from the highest-severity areas — refining the bulk figure without waiting for full claim-level detail. Every estimate is presented with its underlying assumptions and confidence range explicit, not as a single definitive number, and the actuarial and finance teams review and sign off on the estimate actually used for reporting or reinsurance notification — this tool accelerates getting a defensible early estimate together, it doesn't replace the actuarial judgment involved in finalizing a cat reserve figure that the business will actually act on.
Process flow
- 01
Catastrophe event identified trigger
A catastrophe event is flagged, either from external event-tracking data or internal claims intake volume spiking in a specific geography, triggering early bulk exposure analysis.
- 02
Overlay exposure against event footprint integration
In-force policy exposure data for the affected geography is overlaid against the event's footprint and severity data — storm track, flood extent, wildfire perimeter — as that data becomes available.
- 03
Apply severity and development assumptions ai
A bulk reserve estimate is calculated applying peril- and region-appropriate loss severity and development assumptions to the overlaid exposure, producing an estimate with an explicit range, not a single point figure.
- 04
Refine as better event data arrives ai
As more precise event data and early field-adjuster reports come in from the highest-severity areas, the estimate is refined and updated, tracked as a version history rather than silently overwritten.
- 05
Route to actuarial/finance for sign-off output
Every estimate, with its assumptions and confidence range attached, routes to the actuarial and finance teams for review and sign-off before it's used for financial reporting or reinsurance notification.
Inputs
- In-force policy exposure data by geography
- Catastrophe event footprint and severity data (storm track, flood extent, etc.)
- Peril-specific loss severity and development assumptions
- Early field-adjuster and claims intake volume data
Outputs
- Early bulk reserve estimate with confidence range
- Estimate version history as event data refines
- Assumptions and methodology documentation per estimate
- Actuarial/finance sign-off record
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- An early bulk estimate is only as good as the event footprint and severity data available at the time it's generated, and presenting an early-stage estimate with the same apparent confidence as a mature one, once more claims data exists, risks the business making decisions on a number that hasn't yet incorporated the uncertainty it actually carries — the confidence range needs to genuinely widen for earlier, less-informed estimates, not stay static.
- Loss severity and development assumptions calibrated against a prior catastrophe event of a similar type don't automatically transfer cleanly to a new event with different characteristics — building density, local construction standards, and even the specific peril's behavior (storm surge versus wind damage in a hurricane, for instance) can shift actual severity meaningfully from what a prior-event-calibrated assumption would predict.
- This estimate is meant to accelerate getting a defensible early figure together for actuarial and finance review — it is not a substitute for the actuarial judgment involved in the reserve figure the business actually reports or notifies reinsurers with, and treating an unsigned-off automated estimate as final would remove exactly the professional review this kind of high-stakes, high-uncertainty figure needs.
- In-force exposure data itself can be stale or incomplete for the affected geography — a policy recently bound or endorsed that hasn't fully synced to the exposure dataset used for the overlay will be missed or misrepresented, and given how directly exposure completeness drives the estimate's accuracy, exposure data freshness needs active verification during an active cat event, not assumed.
Frequently asked questions
Does this replace individual claim-level reserving once claims start coming in?
No — this specifically supports the early bulk estimate needed before claim-level detail exists. As individual claims are filed and adjusted, standard claim-level reserving takes over and the bulk estimate is refined or superseded accordingly.
Is the estimate treated as final for financial reporting?
No — every estimate is presented with its assumptions and confidence range, and actuarial and finance teams review and sign off before it's used for reporting or reinsurance notification. It's a supporting tool for that judgment, not a replacement for it.
How does the estimate improve as more information comes in after the event?
It refines as more precise event footprint data and early field-adjuster reports arrive from the highest-severity areas, with each version tracked so the progression from early to more-informed estimate is visible.
Does it work the same way for different catastrophe types, like hurricanes versus wildfires?
The underlying approach — overlaying exposure against event footprint and applying peril-appropriate severity assumptions — applies across catastrophe types, but the specific severity and development assumptions used are calibrated per peril, since different catastrophe types behave differently.