agents × financial-services

Enterprise AI agents for financial services.

Agents that clear AML alerts, screen KYC files, and reconcile breaks in sub-second time — and back every call with a provable, regulator-ready audit trail. Built for the middle and back office, where a wrong decision is a finding.

AML / KYC automation Trade surveillance Append-only audit logs

Decisions a regulator can replay

In financial services, the bottleneck is rarely raw analytics — it is the army of analysts triaging alerts, the reconciliation teams chasing breaks at quarter close, and the surveillance desk reading flags one by one. The work is repetitive, rules-bound, and unforgiving: a missed structuring pattern or an unscreened sanctioned party is not an error, it is an enforcement action. That combination of high volume and zero tolerance is exactly where a disciplined agent earns its place.

An eeko agent reads the alert, pulls the customer's history and counterparty data, applies your written policy, and either clears, escalates, or routes for human sign-off — in milliseconds, every time. What makes it deployable on a regulated desk is not the speed but the receipts: the exact rule invoked, the data retrieved, the threshold compared, and the reviewer who approved are all written to an append-only log a regulator can replay months later.

Agents wired into your core banking stack.

Three hardened layers, tuned to the realities of a regulated financial institution.

01 / toolingCORE
Tool-calling into financial systems
Typed, permissioned connectors into your case manager, core banking ledger, custodian feeds, sanctions screening, and market-data services — so the agent acts through controls, never with raw credentials.
  • AML case-manager + sanctions APIs
  • Ledger & custodian reconciliation feeds
  • Order/EMS surveillance hooks
02 / retrievalCORE
RAG on financial data
Grounded retrieval over your BSA/AML policy, KYC files, regulatory guidance, and counterparty records so every disposition cites the clause and the evidence it relied on — not a model guess.
  • Policy + procedure citations
  • Counterparty & beneficial-owner records
  • Permission-aware, segregated retrieval
03 / oversightSECURE
Audit, guardrails & human-in-the-loop
Every plan, retrieval, and disposition is traced to an immutable record, with mandatory human approval on any SAR filing, account freeze, or threshold override.
  • Append-only, replayable audit logs
  • Sign-off gates on SARs & freezes
  • On-prem / in-VPC inference

Where AI agents pay back in financial services

The fastest returns come from the alert queues and reconciliation backlogs that scale with volume but not with headcount:

  • AML alert triage — agents enrich each alert with transaction history and network context, clear the obvious false positives, and hand investigators a pre-built case file, collapsing review time and shrinking the backlog.
  • KYC & onboarding screening — automated document extraction, sanctions and PEP screening, and beneficial-ownership checks, with anything ambiguous routed to a human before an account opens.
  • Reconciliation & break resolution — agents match positions and cash across ledgers, custodians, and counterparties, propose the journal entry for each break, and escalate only the exceptions a person must judge.
  • Trade surveillance — continuous review of order and execution flow for spoofing, wash trades, and front-running, with each flagged pattern packaged into an evidenced, regulator-ready narrative.

Common questions.

How do AI agents apply to financial services?

AI agents work the high-volume, rules-bound tasks that fill a bank's back and middle office — enriching AML alerts, screening KYC documents, reconciling breaks across ledgers and custodians, and surfacing trade-surveillance exceptions. Each agent calls into your core systems through typed interfaces, grounds its judgment in your policies and counterparty data, and renders a decision in well under a second while writing every step to an immutable record.

How do you satisfy regulators and auditors?

Every agent decision is reconstructable: the alert it read, the policy clause it cited, the data it retrieved, the threshold it applied, and the human who approved it are all captured in an append-only audit log. Models can run inside your own cloud or on-prem so customer and transaction data never leaves your perimeter, and human-in-the-loop gates sit in front of any action a regulator would expect a person to sign off on.

Related paths.

Clear the queue, keep the receipts.

Bring us your worst alert backlog or your messiest reconciliation, and we will scope an agent that works it at machine speed with an audit trail your examiners will accept. Response inside 24 hours.