AI in fintech that runs the checks your team still does by hand.

We build automation systems for fintech companies under FCA (UK), CBI (Ireland), MAS (Singapore), ASIC (Australia), and EU regulatory frameworks including DORA, PSD2, and GDPR. Compliance requirements shape the architecture from the first design session: data residency requirements determine which cloud regions are permissible; audit trail requirements define log format and retention; operational resilience requirements define recovery time and recovery point objectives. We build to the architectural specifications your compliance team defines and deliver a compliance documentation package as part of every project.

KYC automation handles structured, rule-based checks for every applicant: document OCR, authenticity verification, liveness check, sanctions screening, PEP and adverse media checks, and credit bureau queries. Edge cases are identified by rule: unusual document formats, sanctions matches above the fuzzy-match threshold requiring human disambiguation, high-risk country of origin, complex corporate ownership structures, or applicants whose score lands at the boundary between automated approval and decline. Edge cases are routed to a manual review queue with all automated check results pre-populated. We design the flow to clear low-risk consumer applications straight through without a human touching them. How high that straight-through rate goes is your decision, not a fixed benchmark: it depends on the risk thresholds and applicant mix you set with your compliance team during calibration, and we tune the rules against your real applicant data before go-live.

Yes. Most fintech automation projects involve integrating with an existing system of record rather than replacing it. Modern cloud-native core banking platforms like Thought Machine and Mambu expose full REST APIs. Temenos Transact and Finacle expose APIs of varying quality depending on version and module configuration. Payment processors including Stripe, Adyen, and Braintree expose well-documented REST APIs and webhook event streams. We scope the integration during discovery by reviewing API documentation, testing against sandbox environments, and identifying data flows the automation requires.

Start where payback is obvious: close and reconciliation, AP and invoicing, loan processing, AML monitoring, regulatory reporting. The stalled-effort mistake is boiling the ocean. Pick one expensive repetitive process, prove the return, fund the next step. Pilot narrow enough to ship in weeks, visible enough the CFO feels it. Usually you do not need to replace systems first. Most early value comes from connecting and automating the systems already in place. The application that sat in a review queue for three days is the process to start with.

Privacy minimization is the design rule: the automation reads only the fields the decision needs. Data governance, human review, and clear ownership manage the compliance risk. We audit existing compliance processes first, choose tooling that fits your regulatory needs, and keep the design updated as rules change.

Ask for the simpler non-AI option alongside the AI one, and pick whichever the evidence supports. Define what done looks like and who owns the system after deployment before signing. Ongoing management is part of the price: without governance, processes drift and returns decline.

Four questions. One: which expensive repetitive process goes first, and why that one? Two: what data does the automation read, and what does it never touch? Three: can they recommend a non-AI answer? Four: who owns it after deployment, and what happens when the process drifts?

Cost follows scope: one workflow or many, the systems it must integrate with, and the compliance requirements it must satisfy. We model the ROI on your real volumes before you commit. The price is fixed and agreed in writing before the build starts.