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Case study · MGSC 697 · capstone

Portfolio Committee

A governed multi-agent investment committee

13/13adversarial scenarios pass

The question

Does a multi-agent committee add enough governance value over one generalist advisor to justify the added coordination complexity?

Macro, Sector, Risk and Compliance agents bid through a risk-budget auction, with veto controls and a human CIO approver. Governance fails closed: unsafe or ambiguous decisions escalate instead of trading. Tested against prompt injection, stale data, restricted assets, replay, over-budget bids and specialist timeouts.

How it works

  1. 01

    Macro and Sector agents write independent views to separate, role-scoped state — fan-out, then a stable gather.

  2. 02

    Their bids compete in a contract-net auction for a scarce, deterministic risk budget; unsupported, over-budget, restricted or concentrated bids are rejected.

  3. 03

    Risk and Compliance act as independent veto gates — concentration, turnover, cash floor and drawdown on one side; restricted assets, stale data and instruction attacks on the other.

  4. 04

    Risk may ask for exactly one diversified Sector revision: recovery without an unbounded self-correction loop.

  5. 05

    Hard breaches, a missing specialist or ambiguity go to a human CIO as a structured approval ticket. Every message carries a typed header with trace and correlation IDs.

Results

13/13

deterministic scenarios pass

8

evaluated cases routed to CIO review

1

bounded revision allowed — never a loop

Bottom line

Yes for shadow decision support, no for autonomous deployment. The committee can propose weights, run the auction, reject unsafe bids and draft CIO tickets — but it cannot trade or rebalance an account.

From the repo

Coordination outcomes across the deterministic evaluation suite

Known limits

  • —The portfolio, market conditions and scenarios are synthetic — built to demonstrate system design.
  • —Shadow-only authority: the prototype cannot trade, rebalance an account, or approve autonomous deployment.
Multi-agent systemsOpenAI Agents SDKPythonEvals
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