Here's a question that keeps compliance officers awake at 2am: when your algorithmic strategy blows up a position, who actually owned that decision? Was it the quant who built the model? The portfolio manager who approved the parameters? The investment committee that signed off the mandate? Or the trustee who ticked the governance box? This question is harder than it looks — and the answer genuinely matters.

The honest answer is: ownership is shared, but accountability must be assigned. Governance frameworks that spread responsibility across everyone often end up holding no one truly accountable. Best practice structures name a single decision authority for model deployment — typically the Chief Investment Officer or a designated Model Governance Officer — while the investment committee retains mandate-level oversight rather than trade-level approval. That distinction is everything.

CONCEPTThe investment committee owns the mandate boundaries — the model owner owns what happens inside them.
WARNINGCommittees that approve algorithms without documented parameter limits carry trustee liability exposure they rarely realise exists.
KEY IDEAGovernance clarity prevents the blame shuffle — everyone pointing sideways when an algo misfires.

Think of it like approving a construction project. The council (investment committee) approves the building envelope — height, footprint, materials. The architect (model owner) decides where the internal walls go. If a wall collapses, the architect answers for the design. But if the building exceeds the approved envelope entirely, that's a governance failure — the council failed its oversight duty. Algo mandates work the same way. The committee sets the envelope; the model owner works within it.

Trustee / Responsible Entity — Mandate Legality Investment Committee — Mandate Parameters Model Governance Officer — Deployment Quant / Dev Team — Model Build

Practically, well-governed funds document this with a Model Governance Policy that sits alongside the Investment Management Agreement. It specifies who can alter strategy parameters, what triggers a mandatory committee review (drawdown thresholds, volatility regime changes, data feed substitutions), and how model changes are logged for audit purposes. ASIC's guidance for responsible entities under the Corporations Act reinforces that trustee obligations don't disappear just because execution is automated. Useful foundations for building this framework include investment committee structures on Investopedia, the algorithmic trading overview on Wikipedia, and the broader context of corporate governance principles on Investopedia — all of which underpin how institutional frameworks are evolving to handle automated decision-making.

Start today by mapping every live algo strategy to a named human decision owner — not a team, not a committee, one name. If you can't do that in under ten minutes, your governance structure has a gap worth fixing before ASIC finds it for you.

This content is for educational purposes only and does not constitute financial product advice. Past performance is not indicative of future results. Profit Logic Ltd (ACN 688 669 936) accepts no responsibility for errors or omissions in this content or anywhere on this website. Always seek advice from a licensed financial adviser before making investment decisions.