Industry / 01
Banking
Banks already run on models, and supervisors now treat AI as part of that estate. The institutions that move fastest are not the ones with the most pilots — they are the ones whose governance lets them say yes safely.
AI opportunity map
Where AI earns its place in this sector.
Credit and risk decisioning
Document analysis and structured judgment support in underwriting and adjudication, with every recommendation explainable to the second line of defence.
Financial crime operations
Alert triage and case preparation that cut investigation time while producing a complete, reviewable audit trail.
Client and advisor support
Assistants grounded in your policies, products, and client files — not in the open internet.
Back-office reconciliation
Extraction and reconciliation across core banking, payments, and treasury systems that still exchange documents.
Regulation & compliance
Compliance is part of the architecture.
Banking is where AI governance is most mature — and most demanding. We design for the examiner's questions from day one.
OSFI Guideline E-23 on model risk management, which brings AI and ML models into formal scope
AML obligations under the PCMLTFA and FINTRAC guidance when AI touches monitoring or reporting
PIPEDA and Québec's Law 25 for client data used in training, retrieval, or logging
EU AI Act high-risk classification for creditworthiness systems serving European clients
Third-party risk expectations (OSFI B-10) when models are hosted outside the institution
Relevant services
How we typically engage.
Contact
Talk to our engineers.
Describe your sector, your constraints, and the problem in front of you. We come prepared or we do not come.