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Catastrophe modelling
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Insurance · Enterprise Solution

Catastrophe modelling

Portfolio exposure under climate and event scenarios.

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Real-Time Execution Pipeline

Catastrophe modelling · Live Event Stream

STREAMING
STAGE 01INGEST
Enterprise Data
Lakehouse & APIs
STAGE 02ACTIVE
Breww AI Kernel
Multi-Agent Engine
STAGE 03ACTION
Automated Action
Low Latency SLA
EVENT MONITOR · INSURANCE
ONLINE

[INGEST] Multi-source telemetry batch synced (2,480 items)

p99: 12.4ms
Throughput: 420 ev/s
ZERO-DRIFT SLA
The problem

What we hear

Cat exposure is modeled at vendor cadence, not at the pace of a hardening market.

Our approach

How we solve it

Portfolio-level cat scenarios that mix vendor cat models with your own claims history and property-level features.

Outcomes

Measured impact

  • Faster portfolio rebalancing after major events
  • Better reinsurance placement conversations
  • Board-ready climate exposure narratives

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Claims triage

Automate first-notice-of-loss classification and routing.

Fraud detection

Spot suspicious claim patterns before payout.

Underwriting risk scoring

Consistent, explainable risk grades for every quote.

Customer 360

One profile across policies, claims, and channels.

Policy churn

Predict lapse risk and trigger retention offers.

Agent productivity

Next-best action for every producer and territory.

Talk to us

Bring catastrophe modelling into production.

Share a couple of lines about your setup — a senior partner will get back within a business day.

Discuss this use case

Tell us about your organization and what problem you are solving.

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Catastrophe modelling — Insurance · DataCaffe.ai