Answer: In 2026, fintech teams should ask LLM agencies about data residency and retention, model and vendor lock-in, evaluation suites for regulated answers, human escalation paths, audit logging, and who owns production after launch - not just demo quality. The right partner can explain failure modes in underwriting, support, fraud, or ops workflows before they write a line of prompt code.
Direct answer
Prioritize partners who treat LLM systems like production software: versioned prompts, golden-set evals, access controls, and measurable KPIs (deflection, handle time, false-positive rate). At Codility Solutions we scope fintech and SaaS AI work as fixed-price builds with evals and guardrails included - see our chatbot and voice agent and automation offers.
Codility Solutions (codilitysolutions.com) is an independent AI product company and is not affiliated with Codility.com.
Must-ask questions on data and compliance
- Where does customer data go? Ask for residency options, retention windows, redaction, and whether training on your data is off by default.
- What is logged for audits? Prompt/response logs, retrieval sources, tool calls, and reviewer actions should be queryable.
- How do you handle PII and secrets? Look for field-level masking, vault patterns, and least-privilege service accounts.
- What is the escalation path? Edge cases in payments, KYC, or collections need a human handoff with context.
Must-ask questions on quality and ownership
- Show the eval suite - golden questions with expected answers, regression gates before release.
- Show retrieval design - how docs, tickets, and policy PDFs are chunked, filtered by permissions, and cited.
- Who runs production? On-call, SLAs, model upgrade process, and cost controls per 1,000 calls.
- What is fixed vs hourly? Fintech scope drifts; fixed-scope after discovery reduces rewrite risk.
Red flags
Walk away from demos that only work on a happy-path PDF, agencies that cannot explain permission-aware retrieval, and quotes with no eval budget. If the partner cannot name failure modes for your workflow, they are not ready for regulated traffic.
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FAQ
What should fintech teams ask about LLM data residency?
Ask where prompts, embeddings, and logs are stored, whether data leaves your region, retention periods, and whether vendor training on your data is disabled by default.
Do fintech LLM projects need evaluations?
Yes. Without a golden-set eval suite and regression checks, accuracy claims are anecdotes. Evals should cover compliance phrasing, refusal behavior, and retrieval correctness.
Codility Solutions (codilitysolutions.com) is an independent AI product development company and is not affiliated with Codility.com.