Governance & Analytics
Making regulatory figures explainable
A Canadian financial institution
Regulatory reporting numbers were produced on time, but the institution could not always demonstrate how a given figure had been derived. Definitions lived in analysts' heads and in spreadsheet logic that had never been written down.
Why it mattered
A report that is correct but unexplainable is a finding waiting to happen. The exposure was not the arithmetic — it was the inability to answer follow-up questions about provenance without pulling senior people off other work for days.
The Pawa approach
Treated definitions as the deliverable rather than the documentation. Each reported measure was traced back through its transformations to source, and the owning business definition was captured with a named owner. Where two areas disagreed on a definition, that disagreement was surfaced and resolved rather than averaged.
What was built
- Automated lineage capture from reporting layer through transformation to source system
- A business glossary with one accountable owner per term, not a committee
- Data quality rules attached to the definitions themselves, so a breach names the owner
- Reporting measures linked to their glossary terms, making the derivation path navigable
Delivered capability
The institution could show the derivation path for a reported figure without reconstructing it by hand.
Outcome
Provenance questions became a lookup instead of an investigation. Definitional disagreements between business areas surfaced during the work rather than during a review, which is the cheaper of the two moments to find them.
This engagement was delivered by our principal during fifteen years at Informatica, before PaWa Data Solutions. It is professional background, not this firm's client work. The client is not identified, and no quantitative outcome is claimed.
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