AI Automation
for Fintech,
New York.
KYC, AML, reconciliation, and regulatory reporting. Built for the compliance requirements of New York.
The workflows that move the needle.
KYC/AML onboarding and ongoing monitoring
Transaction reconciliation and exception handling
Regulatory reporting and audit trail generation
Built to spec.
Every automation we ship in New York is engineered around the compliance frameworks that govern fintech data in United States.
SEC Rule 17a-4, FINRA Rules 3110 and 3120, BSA/AML requirements, and SOX Section 302/404 for publicly listed companies govern all financial AI automation.
We run a data protection impact assessment on every project, document the legal basis for all automated processing, and build human-in-the-loop controls wherever a decision carries legal or material effect. You receive full audit logs and runbook documentation at handover.
Everything the automation says to a customer is both a regulated communication and a preserved record.
In most sectors an automated message is just a message. In financial services it is two regulated artefacts at once. Under the FCA's Consumer Duty, set out in PS22/9, firms must deliver good outcomes for retail customers, which includes communications customers can understand and the support they need when they need it. An automated response that is technically accurate but incomprehensible is a Consumer Duty problem, not a copywriting one.
At the same time it is a record. SEC Rule 17a-4 and FINRA Rule 3110 require covered firms to preserve communications and to supervise them. If a system generates customer communications at volume, the retention and supervisory review architecture has to exist before the system ships, not after somebody asks for it.
Where the automation informs a decision rather than a message, the Prudential Regulation Authority's model risk management principles apply. The expectation is documented ownership, validation, and an understanding of how the model behaves outside its training conditions. Most of the effort in a regulated build goes here rather than into the model itself.
What it has to connect to
- Core banking and ledger
- Usually the constraint: batch windows and read-only access
- KYC and screening providers
- Rate limits and match thresholds shape the workflow
- Archival and supervision
- Retention under 17a-4 and supervisory review under 3110
- Accounting systems
- QuickBooks, Xero, NetSuite in the SME segment
What we will not automate here
- Final credit and risk decisions
- Automation handles extraction and preliminary scoring; the decision on a higher-risk customer stays with a person.
- Suitability and advice
- Regulated advice is not an output we let a system produce unreviewed.
- Unlogged customer communications
- A communication that is not preserved is a supervision failure regardless of its content.
Sector sources
- 01PS22/9: A new Consumer Duty, Financial Conduct Authority
- 02Model risk management principles for banks (SS1/23), Bank of England, Prudential Regulation Authority
- 0317 CFR 240.17a-4, Records to be preserved, Electronic Code of Federal Regulations
- 04FINRA Rule 3110, Supervision, Financial Industry Regulatory Authority
NYDFS supervises AI as a cybersecurity matter under Part 500, not as a separate AI regime.
New York's financial regulator has not written a standalone AI rulebook. It folds AI into 23 NYCRR Part 500, the cybersecurity regulation covered entities already run. In practice that means an AI deployment does not get its own governance track; it goes into the existing Part 500 risk assessment, and a risk assessment that does not address AI-related threats has to be revised.
The guidance has arrived as a sequence of industry letters rather than a single rule: an October 2024 memorandum on the risks posed by artificial intelligence, an October 2025 letter on managing third-party service providers including AI and fintech vendors, and a May 2026 letter on the heightened risks of frontier AI models. The final provisions of the 2023 amendment to Part 500 took effect on 1 November 2025.
One control deserves specific mention because it changes build decisions. NYDFS advises covered entities to use authentication factors that withstand AI-generated deepfakes, which means moving away from SMS, voice and video verification toward digital certificates and physical security keys. If an automation touches identity verification, that is a design constraint rather than a policy footnote.
The full New York briefing sets out the rest of the local picture.
Who you answer to here
- NYDFS
- 23 NYCRR Part 500; AI supervised through the cybersecurity regime
- FINRA and SEC
- Supervision and record-keeping obligations run in parallel
- NY SHIELD Act
- State data security requirements for private information
Sources
- 01Cybersecurity Resource Center, 23 NYCRR Part 500 and industry guidance, New York State Department of Financial Services
- 02FINRA Rule 3110, Supervision, Financial Industry Regulatory Authority
- 0317 CFR 240.17a-4, Records to be preserved, Electronic Code of Federal Regulations
Common questions.
- Is there an AI automation agency for fintech in New York?
- Yes. Axonari engineers AI automation systems for fintech businesses in New York, working remotely from our engineering base in Jaipur. We have built systems covering kyc/aml onboarding and ongoing monitoring and transaction reconciliation and exception handling for organisations across New York, NY. Projects start within 2–3 weeks of the initial brief.
- Is AI automation compliant with HIPAA in New York?
- Compliance is engineered into every project we ship in New York. SEC Rule 17a-4, FINRA Rules 3110 and 3120, BSA/AML requirements, and SOX Section 302/404 for publicly listed companies govern all financial AI automation. All automations that process personal or regulated data include a data protection impact assessment, human-in-the-loop controls for decisions with legal or material effect, and full audit logging.
- How much does fintech AI automation cost in New York?
- Cost in New York depends on complexity and scope. A focused single-workflow automation — for example, kyc/aml onboarding and ongoing monitoring — typically runs $10,000–$35,000. Multi-workflow builds with integrations and compliance scaffolding run $40,000–$100,000. All projects are fixed-price with agreed deliverables — no hourly billing.
- How long does a fintech AI automation project take in New York?
- A single-workflow automation for a New York-based fintech business takes 6–10 weeks from brief to go-live: 1–2 weeks for discovery and data mapping, 3–5 weeks for engineering and integration, and 1–2 weeks for testing, compliance review, and handover. Multi-workflow builds run 12–20 weeks. Timelines are fixed at the brief stage.