Forge Pool

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Insurance Risk Modeling ​

Insurance systems do not fail at the mean. They fail in the tail.

Catastrophe clustering, reserve instability, treaty sensitivity, and capital stress emerge from distributions of possible outcomes — not single expected values.

Forge Pool turns insurance risk into a deterministic, distributed execution problem over uncertainty.

The System ​

Insurance is not a reporting problem. It is a distribution exploration problem.

A portfolio must be evaluated across:

  • stochastic event generation
  • severity and frequency variation
  • regional exposure shifts
  • treaty structures
  • correlated catastrophe behavior

Not as isolated scenarios — but as a complete loss distribution surface.

Execution Shape ​

text
exposure + hazard + treaty structures
    ↓
adapter (portfolio + catastrophe model mapping)
    ↓
mc@1 (stochastic loss simulation)
    ↓
graph@1 (optional correlation / contagion propagation)
    ↓
ensemble@1 (aggregation + confidence)
    ↓
artifacts + replay

Primitive Composition ​

Insurance workloads are built from a small number of primitives:

  • mc@1 generates large-scale stochastic loss trajectories

  • graph@1 (when applicable) models dependency, correlation, and cascade effects

  • ensemble@1 aggregates multi-run outputs into stable distributions and confidence bands

This composition produces a complete view of portfolio risk, not a sampled approximation.

What Gets Computed ​

Forge does not compute:

  • expected loss
  • single scenario outcomes

Forge computes:

  • full loss distributions
  • deep-tail exposure (P95 / P99 / beyond)
  • treaty payout behavior across structures
  • portfolio fragility surfaces
  • sensitivity across assumptions

Output Artifacts ​

text
loss_distribution
p50_loss
p95_loss
p99_loss
tail_exposure_surface
portfolio_fragility_score
treaty_payout_distribution
capital_adequacy_signal
replay_token

Every output is:

  • deterministic
  • replayable
  • auditable

Pilot Example ​

Catastrophe Portfolio Execution

Inputs:

  • exposure dataset
  • catastrophe event assumptions
  • policy and treaty structure
  • severity and frequency scenarios

Execution:

  • 100M+ stochastic catastrophe trajectories
  • distributed execution across agents
  • deterministic aggregation

Outputs:

  • portfolio loss distribution
  • deep-tail exposure analysis
  • treaty sensitivity comparison
  • capital adequacy stress signals

Why Forge ​

Insurance risk is limited by compute.

Forge removes that constraint.

It enables:

  • full distribution exploration
  • interactive tail-risk analysis
  • reproducible regulatory workflows
  • scenario comparison at scale

This is not a faster actuarial tool.

This is an execution layer for risk uncertainty.