AI risks mapped before scaling
Source: completed data and governance assessment; deliverables documented in the executive report.
A credit fintech was accelerating AI faster than its governance could keep up. Maxxi conducted a data and governance assessment, diagnosed maturity, surfaced AI risks and established where to start. The fintech gained clarity on where to invest.
Scaling AI without governance means scaling risk
The fintech was accelerating AI initiatives, but decisions still relied on manual analysis and tools were proliferating outside governance, a pattern known as shadow AI.
In a regulated sector, scaling this way increases risk rather than outcomes. Before investing further, the fintech needed an evidence-based view of its maturity and exposure.
Four weeks to expose maturity, risk and priorities
Maxxi conducted a data and governance assessment using the DAMA-DMBOK framework through four connected steps.
Kickoff, interviews and mapping of the data ecosystem.
A maturity heatmap and current-state map.
A shadow AI map and prioritized AI risks.
A sequenced action plan, quick-win backlog and playbook that transferred the method to the internal team.
From manual analysis to evidence-based decisions
How can data maturity and AI risks be assessed before scaling?
Decisions supported by manual analysis and AI tools operating without governance.
A maturity diagnosis, mapped AI risks and an action plan with quick wins.
Decision enabled
The fintech gained a clear view of its maturity, its 10 priority AI risks and where to start, creating a basis for deeper investigation where it mattered most.
What stayed with the team
A handoff playbook transferred the method to the internal team so it could continue strengthening governance without depending on Maxxi.
Map the risks before scaling AI
Accelerating AI without governance accelerates risk, particularly in a regulated sector. A focused assessment exposes real maturity, material risks and the right starting point before investment moves to scale.
The work also drew on Data & AI Governance.
Published 2026.
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