The context
Onboarding and periodic-review KYC, plus AML transaction monitoring, are the largest reliable cost centers in the bank. The teams are large, mostly offshore, and the regulator is unforgiving about quality.
Why it doesn't scale today
The vendor stack is fragmented. Rule-based AML generates 95%+ false positives. KYC analysts spend their time assembling rather than judging. Every previous AI initiative was either a sandbox demo or a vendor accelerator that did not survive contact with the bank's actual operational reality.
What we ask in week one
- iWhat does your analyst's day actually look like, and where are they doing assembly instead of judgement?
- iiWhich of your AML alerts are model-suppressible at the false-positive rate your regulator will accept?
- iiiHow does the explanation chain stay in your analyst's hands — and your examiner's — at every step?
- ivWhere do we integrate against your existing case-management system instead of replacing it?
What we build
We embed inside the analyst workflow: document AI for ID + entity verification, adverse-media synthesis from a curated corpus, relationship-graph reasoning over the bank's own data, and false-positive suppression on the AML stream tuned to the regulator's published guidance. The analyst stays in control; the assembly disappears.
Why we're the right squad
We have stood up agentic KYC inside top-50 US banks. We know which integrations matter (case manager, customer master, sanctions list), which do not, and how to defend the false-positive rate to a regulator who has heard every AI promise before.