Hybrid AI for Fintech
Private models in your own cloud for customer data, managed models like Claude or GPT for public work, and the evidence sponsor banks, enterprise customers and regulators ask for. At unit economics that improve as you grow.
Four problems we hear from payments, lending and banking-as-a-service teams.
Reason 1Partner Diligence
Sponsor banks and enterprise customers ask where their customers’ data goes when your product uses AI, and “to a model vendor” ends the conversation.
The cost: Longer sales cycles and deals that stall in security review.
Reason 2Unit Economics
Every transaction you categorise, every dispute you summarise and every onboarding you check becomes a variable cost that grows faster than revenue.
The cost: AI features that get more expensive the more successful they are.
Reason 3Build Drag
Standing up private models, retrieval, evaluation and monitoring takes a platform team you haven’t hired.
The cost: The roadmap slips while infrastructure gets built.
Reason 4Regulatory Reach
Banks must register and oversee their ICT providers, and credit-scoring features can fall into the AI Act’s high-risk category.
The cost: Compliance work lands on a team that isn’t sized for it.
Argivio runs private models in your own cloud for customer data, uses Claude or GPT only for public work, and gives you the evidence your partners and regulators ask for.
Discuss a pilotEvery request passes a policy check before any model sees it. Customer data stays on private models in your cloud; public work can use managed models, billed per token for that share only.
| Task | Route | What the model sees |
|---|---|---|
| Fraud alert triage | Private AI | Card and payment transactions, device and customer data |
| AML case summaries and SAR/STR drafts | Private AI | Customer identities, transaction chains, investigator notes |
| KYC and beneficial-ownership review | Private AI | Identity documents, registry extracts, ownership structures |
| Credit memos and risk scoring | Private AI | Financial statements, exposures and your proprietary risk models |
| Explainability packs for auditors | Private AI | Model inputs, scores and decisions on real cases |
| Regulatory change tracking | Managed AI | Public texts from supervisors and standard setters |
| Market and sector research | Managed AI | Published reports, filings and news, never your positions |
| General drafting from public sources | Managed AI | Templates and public material, formatted privately in your house style |
Common first features, each running where it belongs.
Summaries of disputed transactions and chargeback evidence, drafted against your scheme rules and policies.
PrivateIdentity documents and company extracts read and checked against your onboarding policy, with gaps flagged for review.
PrivateAffordability and cash-flow summaries from bank statements, with reasons your credit team and auditors can read.
PrivateReplies to account and payment questions drafted from your help centre and the customer’s own history.
PrivateNew rules and scheme changes read from public sources by managed models, mapped privately to your policies.
ManagedCall Argivio from your own services, with the same policy check, audit trail and cost controls behind every request.
Private + ManagedPrivate runs in your cloudManaged public sources onlyPrivate + Managed routed per request
Every AI workload has a break-even point. Below it, paying per token is cheaper; above it, owned capacity wins. Risk work scales with every transaction, so most of it crosses that line early. Argivio puts each workload on the right side of the line, and moves it when it crosses.
Illustrative. Monthly cost (vertical) against monthly usage (horizontal); dots mark each break-even point.
At very low volumes, pay-per-use can be cheaper. Our break-even calculator shows where your institution sits. Cost is one reason for hybrid AI, not the only one: client confidentiality and banking secrecy often justify private AI before the numbers do.
Tell us the feature you want to ship and the partner or regulator you need to satisfy. We’ll show you how it runs in your own cloud.