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AI behind the compliance desk, not in front of the customer

Onboarding, KYC, sanctions screening, periodic reviews. We automate the reading-and-summarising work so the human team makes the calls.

FinTech compliance workloads scale with customers, but compliance headcount doesn't. The fastest wins are in the document-reading layer: KYC summaries, source-of-funds reviews, and periodic refresh packs. AI prepares the file; the analyst decides.

What AI typically helps with

The jobs we'd look at first.

01

KYC and onboarding summarisation

Structured summaries of customer-supplied documents, with a clear audit trail of what the model read and what it concluded.

02

Periodic review packs

Pre-built review packs at customer anniversaries, surfacing the changes that matter so analysts review exceptions, not whole files.

03

Sanctions and adverse media triage

First-pass classification of screening hits with the reasoning attached, so analysts spend their day on the genuine edge cases.

04

Internal policy Q&A

Grounded answers from your own policy library so first-line ops staff don't have to interrupt compliance for a citation.

What we wouldn't do here

The projects we'd turn down.

Worth being explicit. These are the asks we'd say no to in this sector — and saying no is part of the work.

We would not automate the final approve/decline decision on a customer. The model prepares the file; a human decides.

We would not pretend a model removes regulatory liability. Every output is reviewable, logged, and clearly attributable to a person.

We would not bolt AI on top of broken process. If the workflow is broken before automation, it is broken after — only faster and more confidently wrong.

Next step

A first call, no slides.

Tell us the workflow. We'll tell you, plainly, whether it's worth a Diagnostic and what we'd expect to find.