AI under the constraints regulators actually impose.
AI for Financial Services
Banking, capital markets and fintech operate under explainability, retention and residency rules that shape the architecture before a line of code is written. We design for those first.
What makes this sector different
Explainability is not optional
A model that cannot justify a decision is a model you cannot deploy against credit, pricing or suitability.
Data is fragmented across decades
Core banking, CRM, spreadsheets and document stores rarely share a customer key.
Residency and retention
Where data lives and how long it is kept constrains which models may be used at all.
Where it pays back
Document-heavy onboarding and KYC
Retrieval-augmented generationExtract and verify identity and corporate documents, with every extraction traceable to its source page.
Analyst research assistant
Retrieval-augmented generationGrounded question answering over filings, research and internal notes, with citations.
Transaction anomaly detection
Classical MLScore transactions for fraud and AML review with explainable feature attribution.
Customer service copilot
HybridDraft responses grounded in policy documents, with a human approving anything that commits the firm.
How the Financial Services assessment differs
Financial services assessments start from the compliance position, because it determines whether a hosted model API is usable at all.
Compliance we ask about first
Data sources we expect
Questions this template pushes on
- Which decisions must be explainable to a regulator?
- Is customer data permitted to leave your network?
- What is your retention obligation on model inputs and outputs?
These are suggestions surfaced alongside the questions — never pre-filled answers. The assessment still asks you everything, because a score built on assumptions you never confirmed is not a score you could act on.
Questions people ask
- Can we use a hosted model API at all?
- Sometimes, with redaction and a data-processing agreement. Where policy forbids it, self-hosted open models on dedicated GPUs keep everything inside your boundary. The assessment decides which applies from your answers.
Services most used here
AI Strategy & Assessment
Find out what is worth building before you build it.
Enterprise AI Software
Secure, multi-user AI applications with the controls audit will ask for.
Predictive AI
Forecasting, scoring and anomaly detection.
Generative AI / LLM
RAG, agents, copilots and fine-tuning — chosen on evidence.
Scope an AI project for financial services
The Financial Services template sharpens the questions. Ten minutes gets you a feasibility score, an architecture and a costed plan.