AI agents for fintech that clear KYC, fraud, and reconciliation work inside your own systems
Gaper builds fintech agents for KYC/KYB, fraud triage, reconciliation and compliance reporting in your cloud. A human approves every action touching money.
AI agents for fintech are software agents that run financial operations and compliance workflows like KYC/KYB, AML and fraud alert triage, transaction reconciliation, and dispute handling end to end, with guardrails, an audit trail, and human approval required before any action moves money.
KYC, AML and reconciliation queues mean pulling data from five systems by hand. Point-SaaS covers one slice.
- Does it touch real systems?
- Can the outcome be measured?
- Where does human approval stay?
- Who owns it after launch?
One workflow, a build-vs-buy call and the smallest production release, scoped in a free assessment.
From strategy to production, owned by your team.
- 01
Map the workflow
Your documents, systems and edge cases, turned into an agent workflow map.
- 02
Build the supervised agent
The right model, with retrieval, evals, guardrails and human approval gates.
- 03
Connect your systems
Data, APIs and write-backs, so work finishes inside your systems of record.
- 04
Sandbox, verify, go live
Sandbox first, every run verified, then supervised production with rollback and an owner.
Agents wired into the systems you already run.
KYC/KYB and onboarding review
Faster clear-path onboarding, with analysts on borderline decisions.
AML and fraud alert triage
Alerts enriched with cited evidence. Never auto-closes or auto-files.
Transaction reconciliation
Match bank, processor and Plaid feeds, approve before posting.
Dispute and chargeback handling
Draft representments from Stripe evidence, a person decides.
Compliance reporting
Recurring reports reconciled, every figure traceable before sign-off.
Evals, guardrails, and audit trail
Evals, guardrails, named approver, audit log, code you own.
Deployed in your cloud, with money moves gated by a human
Financial workloads carry real liability, so the deployment model matters as much as the model.
- Runs in your cloud or VPC, no customer data on shared infrastructure
- Human approval required before any money-moving or filing action
- Full audit trail of every input, decision, and output
Low confidence, policy exception, or protected data.
Which AI governance rules apply in fintech, and to whom?
Five rule sets come up most often, and each reaches a different party: two pieces of US bank guidance reach fintechs mostly through bank partners, Regulation B binds any creditor, including anyone regularly participating in a credit decision, and two EU laws bind EU financial entities and the providers or deployers of credit-scoring AI used there. This is information, not legal advice.
On 17 April 2026 US bank regulators replaced SR 11-7 with revised model risk guidance (Fed letter SR 26-2), aimed mainly at banks over $30 billion in assets and excluding generative and agentic AI. The 6 June 2023 third-party guidance names fintech partners; an 11 September 2026 proposal would replace it. None of this guidance is binding. An LLM agent sits outside SR 26-2 but within reach of a partner bank's governance and due diligence.
Regulation B (12 CFR 1002.9) requires a creditor taking adverse action to give the specific principal reasons, or disclose the right to request them; citing only a missed qualifying score is insufficient. The CFPB withdrew its adverse action circulars, one on complex algorithms, on 12 May 2025; the regulation stands, so an agent drafting notices should take reasons from the decision model.
The EU AI Act (2024/1689) classes AI scoring individuals' creditworthiness as high-risk, fraud detection excepted; the Digital Omnibus on AI (2026/1744) moved those systems' high-risk duties from 2 August 2026 to 2 December 2027. A firm that puts such a system into service under its own name, even one built for it, counts as its provider. DORA (2022/2554) has applied since 17 January 2025 to EU financial entities, including banks, payment and e-money institutions, account information service providers, investment firms and crypto-asset service providers. They stay fully responsible when using an ICT vendor, such as an agent builder still running the agent.
A fractional Chief AI Officer can own this rule map until you hire one.
Where fintech point-SaaS stops
Vertical SaaS tools each solve one piece: a KYC vendor, a fraud scoring engine, a reconciliation product. They do that piece well, then hand the integration, judgment calls, and cross-system glue back to your team. Gaper builds agents that operate across those tools and your own systems, doing the connective work the products leave behind. When a product is genuinely the right answer for a workflow, we will tell you to buy it rather than build around it.
- Point tools cover one workflow; agents span the chain across systems
- Agents call your existing vendors instead of replacing them
- Honest guidance when buying a product beats building an agent
Use a product when the workflow is standard and the data path is simple.
Build when integration, compliance, or differentiation decide the outcome.
Model-agnostic, with an owner and evals from day one
Gaper works across OpenAI, Claude, Gemini and open models. This is implementation work, not staffing or seat-based access.
- Model choice tuned per workflow and swapped as models improve
- Evals and guardrails wired in before launch, not bolted on later
- An accountable owner per agent and code you keep
Access your auth
Data your environment
Ops monitor or handoff
Snowflake
Salesforce
Postgres
OpenAI
ClaudeQuestions buyers ask us.
What are AI agents for fintech?+
Where do the agents run, and is our data safe?+
Can an agent move money or close an alert on its own?+
How is this different from the fintech SaaS tools we already use?+
Which AI models do you use?+
Is Gaper a staffing or recruiting firm?+
Ready to deploy your first agent?
Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.