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.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an AutoGen multi-agent system managed by Hydra configurations to evaluate commercial actuarial risk and catastrophe exposure.
How work is evaluated
Evaluates the consistency, accuracy, and auditability of premium recommendations across stochastic multi-agent deliberation runs.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
consensus_achieved
Verifies that AutoGen agents reached consensus within configured max turns.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
premium_variance
Variance of technical premium calculations across 5 runs. • target: 0.015 • range: 0-0.05
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
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
Reference links and supporting material
Synthetic catastrophe risk dataset featuring Singapore commercial maritime infrastructure portfolios.
How this agent runs
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
- 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
- Benchmark: ActuaryBench
- Premium Variance target: 0.015
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- AutoGen · Required
- Hydra · Optional
- Ax (Adaptive Experimentation) · Optional
Evaluation contract
- consensus_achieved · Weight 1
- premium_variance · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.