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Orchestrate Multi-Agent Actuarial Risk Rating using AutoGen & Hydra

Actuaries must evaluate complex commercial property catastrophe risks using diverse datasets. Orchestrate an AutoGen multi-agent system with Hydra configuration management to dynamically simulate risk models, parse GAIP case scenarios, and output audited premium recommendations with less than 2% calculation variance across multi-run trials.

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What you are building

Build an AutoGen multi-agent system managed by Hydra configurations to evaluate commercial actuarial risk and catastrophe exposure.

How work is evaluated

Evaluation

Evaluates the consistency, accuracy, and auditability of premium recommendations across stochastic multi-agent deliberation runs.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

consensus_achieved

Verifies that AutoGen agents reached consensus within configured max turns.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

premium_variance

Variance of technical premium calculations across 5 runs. • target: 0.015 • range: 0-0.05

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

  • Master AutoGen multi-agent conversation patterns for actuarial consensus

  • Use Hydra for reproducible execution configurations and experiment tracking

  • Implement actuarial risk calculation tools within AutoGen agent routines

  • Evaluate multi-agent deliberation workflows for stability and variance reduction

Resources

Dataset notes

Synthetic catastrophe risk dataset featuring Singapore commercial maritime infrastructure portfolios.

Challenge setup

Evaluates the consistency, accuracy, and auditability of premium recommendations across stochastic multi-agent deliberation runs.

Challenge input

Hydra dynamic YAML config + property portfolio details

AutoGen

Enables specialized multi-agent conversation and consensus flows.

Hydra

Provides dynamic hierarchical configuration for multi-agent parameters.

Evaluated output

JSON actuarial opinion summary with calculated technical premium

Evaluation checks
  • Verifies that AutoGen agents reached consensus within configured max turns.
  • Variance of technical premium calculations across 5 runs. • target: 0.015 • range: 0-0.05
Configured evaluation evidence
  • Benchmark: ActuaryBench
  • Premium Variance target: 0.015
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • AutoGen · Required
  • Hydra · Optional
  • Ax (Adaptive Experimentation) · Optional

Evaluation contract

  • consensus_achieved · Weight 1
  • premium_variance · Weight 1

Metrics

  • premium_variance · Target 0.015

Benchmarks

  • ActuaryBench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: Hydra dynamic YAML config + property portfolio details

    Output: JSON actuarial opinion summary with calculated technical premium

    Execution harness: Python

Evaluation tools

  • AutoGen · Multi-Agent Orchestration
  • Hydra · Configuration Management

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Orchestrate Multi-Agent Actuarial Risk Rating using AutoGen & Hydra