Perspective on data governance, regulatory compliance, and the infrastructure decisions that separate organisations that survive audits from those that don't.
There is a question that every Chief Data Officer should be able to answer without hesitation: if a regulator walked in today and asked you to prove that your data handling has been compliant for the past 12 months, what would you hand them?
For most organisations, the honest answer is: a collection of policy documents, a governance framework, an assessment report produced by consultants six months ago, and perhaps a spreadsheet of manual checks. What they cannot hand over is a continuous, timestamped, independently verifiable record of what their data was actually doing.
The distinction matters enormously. A policy document tells a regulator what an organisation intended to do. Evidence tells them what actually happened. As regulatory enforcement becomes more sophisticated — and OSFI, the OPC, and the EU's data protection authorities are all becoming more sophisticated — the gap between intention and evidence is becoming a liability.
The organisations that will navigate the next decade of regulatory complexity are the ones building governance infrastructure that produces evidence automatically, at the moment of data movement, before anyone asks for it. The audit should reveal a record, not trigger the creation of one.
Enterprise data systems are typically built to move data efficiently. Governance is added later — as a layer of monitoring, reporting, and periodic assessment that sits alongside the pipeline rather than inside it. This architectural decision is so common that most organisations do not recognise it as a decision at all. It is simply how governance is done.
The problem is structural. When governance is external to the data movement process, it can only observe outcomes — not enforce standards at the point of data movement. It can tell you that a compliance gap exists. It cannot prevent the gap from occurring. And by the time a periodic assessment surfaces the issue, data has already moved through affected systems hundreds of thousands of times.
Governance built into the architecture of data movement operates differently. It does not observe outcomes after the fact — it enforces compliance standards at the moment of movement and records verifiable evidence before that movement is considered complete. The distinction is architectural, not operational. And it changes everything about what compliance evidence looks like.
OSFI Guideline B-10 — Technology and Cyber Risk Management — establishes expectations for how federally regulated financial institutions manage risks arising from technology and cyber incidents, including those originating in third-party relationships. For data governance, the implication is significant: institutions must be able to demonstrate continuous oversight of data flowing through third-party systems, not periodic reviews.
The challenge is that most institutions have designed their third-party governance processes around periodic assessments — vendor questionnaires, annual reviews, point-in-time audits. These processes satisfy the documentation requirement. They do not satisfy the continuous oversight requirement that a sophisticated regulator will look for when examining an institution's actual data control environment.
Continuous oversight requires infrastructure. It requires a system that validates data movement against defined standards at the moment of transaction and produces a verifiable record that demonstrates compliance is happening — not that compliance was intended or assessed, but that it is demonstrably occurring in the live operational environment.