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Challenge

CrewAI Multi-Agent GAIP Insurance Risk Underwriter

Orchestrate a team of CrewAI agents with distinct roles (risk assessor, policy analyst, auditor) to process commercial insurance claims and calculate risk scores. Achieve zero policy hallucination errors and automated audit logging.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Design a collaborative multi-agent system using CrewAI with defined roles and delegated tasks for underwriting regional commercial insurance.

Delivery guide

How work is evaluated

Evaluation

Evaluates multi-agent CrewAI task completion accuracy and calculated payout precision.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

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

Math Calculation Correctness

Verifies payout calculation accurately factors in deductibles

Binary check

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

Dimension 2

payout_accuracy

Accuracy of payout recommendation • target: 1 • range: 0-1

Binary check

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

Learning goals

What you should walk away with

  • Configure CrewAI agents with distinct backstories, goals, and role capabilities

  • Implement sequential and hierarchical agent delegation processes

  • Enforce compliance and coverage boundaries for regional commercial insurance

  • Generate structured claim settlement reports with full rationale

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic commercial property and casualty claim files tailored to Asian insurance markets.

How this agent runs

Evaluates multi-agent CrewAI task completion accuracy and calculated payout precision.

Challenge input

JSON containing policy terms, claim loss details, and surveyor report

CrewAI

Framework for orchestrating role-playing collaborative agents

Evaluated output

JSON containing approved_amount, deduction_reasons, and crew_task_status

Checks for
  • Verifies payout calculation accurately factors in deductibles
  • Accuracy of payout recommendation • target: 1 • range: 0-1
Proof of success
  • Benchmark: InsurBench
  • Payout Accuracy target: 1
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • CrewAI · Required
  • crewAI · Optional
  • Aim · Optional

Evaluation contract

  • Math Calculation Correctness · Weight 1
  • payout_accuracy · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about CrewAI Multi-Agent GAIP Insurance Risk Underwriter