Data governance: the bedrock of AI in stockbroking
Why this matters: James Dickson’s SIAA article argues that AI succeeds only when firms fix their data first. In stockbroking, poor data quality, access control and ownership don’t just blunt value - they create confidentiality, conduct and reputational risk. The message is simple: governance first, AI second.
The regulatory lens
Regulators expect any AI adoption to uphold responsible conduct, market integrity and client protection. APRA’s CPS 230 brings data firmly into operational resilience; AML/CTF monitoring is only as effective as the underlying client and trade data.
What good looks like: six pillars
James sets out six interlocking pillars that make AI safe and useful in broking: Quality, Segregation, Privacy, Security, Accountability, and Ethics. Each needs equal and continuous attention - none are optional.
Where AI is landing today (and why governance decides outcomes)
Trading & risk models: great for strategy and anomaly detection - until inconsistent or delayed market data skews results.
Client analytics: powerful personalisation - if privacy controls and data stitching are sound.
Productivity AI (Copilot/ChatGPT): boosts speed - unless it surfaces sensitive information from collaboration tools.
All roads lead back to governed, validated inputs.
Common pain points holding firms back
Legacy platforms and siloed data, multi-regulator scrutiny, the tendency to treat governance as “cost”, and scarce specialist talent - especially outside the big banks.
Five practical actions for leaders
Audit your data landscape (what you hold, where it lives, who can see it).
Govern collaboration tools (apply entitlements/labels/controls before enabling AI).
Establish data ownership (named stewards with accountability).
Align with CPS 230 (a benchmark for resilience and data governance).
Set AI guardrails (scope, red lines, monitoring).
Bottom line
The winners won’t be the first to pilot AI; they’ll be the firms that prepare their data, build guardrails and then deploy with confidence. Note: partnerships like ours with RecordPoint deliver structured/unstructured data governance frameworks at scale.
