Industry
Finance
Transaction data under regulatory scrutiny
The constraint
DORA · GDPR · transaction scrutiny
Transaction data is abundant, which is the problem. Everything is measurable, so everything gets measured, and the useful signal sits under a great deal of noise that looks meaningful. Add a regulator entitled to ask how a given decision was reached and the binding constraint becomes traceability rather than accuracy. A dedicated financial services capability is planned for 2027; until then this work runs through AI Engineering.
What applies here
AI Engineering
Building AI systems and getting them into production, inside the constraints the environment imposes.
87% forecast precision on consumer transactions
AI Assurance
We test AI systems the way a security team tests infrastructure: adversarially, with documented evidence at the end.
Coverage boundary reported on every deliverable
Where it starts
Most work in finance begins one of two ways.
Discovery
Consultancy & diagnostics
Consultancy. We work with your teams to understand the data you hold, the processes running on top of it and where optimisation is genuinely available, then say plainly what is worth building and what is not.
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Engineering & delivery
Building. A senior-led team takes a decision, yours or one that came out of Discovery, through architecture, delivery and release, then stays with the system as load, scope and the business around it grow.
Read moreAlso in regulated practice