Fintech AI development — KYC, fraud, compliance & finance copilots.

Yes — regulated work is one of our most common engagement types. We sign DPAs, NDAs, and BAAs as required, run engagements SOC 2-aligned, deploy inside customer VPC (AWS Mumbai for India / AWS EU for EU / on-prem on customer hardware) so financial data never leaves your network, and provide audit logs on every model and tool call exportable in formats your compliance team can review.

Yes. For regulator-facing decisions (loan acceptance, fraud flagging, claim acceptance), we operate the LLM in deterministic mode with temperature=0, pinned model version, and pinned prompt versions logged per output. The same input + same model version + same prompt always produces the same output, and the full chain is reproducible from the audit log. Non-determinism is reserved for conversational and copilot use cases where it is acceptable.

PII redaction at ingress for any LLM call — PAN, Aadhaar, account numbers, card numbers are masked before the LLM sees them. Audit logs store original (encrypted at rest with customer-managed KMS keys) + redacted versions. Self-hosted Llama 3 deployments inside your VPC keep raw data fully on your network. AWS Mumbai for India data residency, AWS EU for GDPR-aligned EU residency.

Yes. Our India HQ in Mohali gives us deep experience with Indian BFSI regulatory requirements — DPDP-aligned data handling, AWS Mumbai data residency for RBI account-aggregator and KYC workflows, audit logs exportable in formats RBI auditors accept, multi-language (English + Hindi) interfaces. We have shipped for Indian banks, NBFCs, insurers, and payment platforms.

Most v1 fintech AI engagements at Aiinfox land between ₹40 lakh and ₹1.2 crore ($50,000 to $150,000) fixed-price. KYC + fraud automation pipelines for mid-size banks typically reach ₹1.5–2.5 crore over 4-6 months including ongoing tuning. Pilots are ₹10-15 lakh with acceptance criteria written into scope. International clients pay in USD via wire transfer.

Six to eight weeks for a focused v1 — a KYC automation pipeline, a fraud-scoring model deployment, or a customer-service chatbot. Twelve weeks for a full BFSI compliance copilot with multi-source RAG, audit infrastructure, and on-prem deployment. Multi-product rollouts (KYC + fraud + customer service) are typically 16-20 weeks with a phased go-live.

Yes. We integrate routinely with Salesforce Financial Services Cloud, core banking platforms (Finacle, Flexcube, Temenos), payment processors (Stripe, Razorpay, PayU), KYC providers (HyperVerge, Karza, Onfido), and CRM (HubSpot, Pipedrive). Custom integrations via REST / SOAP / direct database extracts where standard connectors do not exist.

No. Every Aiinfox fintech deployment is designed so the AI accelerates the human (extracting, summarising, flagging, drafting) but human reviewers approve every consequential action — loan acceptance, claim payouts, fraud flags, regulatory filings. This is both a compliance requirement and the only design that compliance teams actually adopt. The AI is a productivity multiplier, not a replacement.

Yes. We have shipped fintech AI for UK lenders and insurers under FCA rules, for clients navigating the EU AI Act's high-risk credit-scoring obligations, and for Canadian and Australian fintechs under OSFI/PIPEDA and APRA/Privacy Act respectively. The regulator and the specific audit-log schema change per jurisdiction; the delivery mechanics — 30-minute scoping call, fixed-price scope in 72 hours, six-week target, compliance review checkpoint before production — stay the same everywhere we work.

Credit scoring and creditworthiness assessment are named high-risk use cases under the EU AI Act, which means any AI system used for that purpose by an EU-regulated lender carries mandatory obligations: a documented risk-management system, human oversight designed into the workflow rather than bolted on, technical documentation sufficient for a regulator to audit the system's logic, and logging that supports post-market monitoring. We design underwriting and adverse-action systems for EU clients against those obligations from week one — deterministic outputs, structured reasoning, and an audit trail built to survive a conformity assessment, not just a customer complaint.

OFAC and the EU consolidated sanctions list are the two we integrate most often, alongside PEP (politically exposed person) screening providers and jurisdiction-specific equivalents — the UK's OFSI list for FCA-regulated clients, DFAT's sanctions list for Australian clients. Screening runs at onboarding and on an ongoing basis against transaction and counterparty data, with every hit routed to a human review queue and logged with the screening-list version and timestamp so the audit trail survives a look-back review.

Yes. The most common request is a compliance copilot — RAG over your internal policies, the relevant regulator's handbook or circulars, and prior examination findings, with citation-required answers and a refusal layer for anything outside the approved corpus. The less common but higher-value request is examiner-response tooling: structuring your existing audit logs, model documentation, and control evidence into a format that answers a data request in the time it takes to run a query, not the weeks it takes to reconstruct a paper trail.