Let agents work in regulated systems. Keep the authority to stop them.

Kontext helps financial institutions discover agents, map their access, block prohibited actions, and detect runtime risk with decision evidence for review.

Kontext for Financial Services. Banks, fintechs, and insurers are putting AI agents next to payment rails, ledgers, and customer records. Kontext decides what those agents may actually do at the moment they try to do it, and leaves a record you can hand to an auditor.

Why finance is different

In a bank, a wrong agent action is not a wrong answer. It is a real payment, a real limit change, or a real export of customer records.

Maker-checker assumes two humans. An agent acting on a developer's or analyst's delegated authority collapses separation of duties into a single step.
An agent calling a third-party API is ICT usage, but it rarely appears in the third-party register that DORA expects you to maintain.
Long-lived keys in .env files, notebooks, and agent config are an audit finding on their own, before anything goes wrong.

What Kontext gives financial institutions

Agent Discovery & Access Posture: Discover agents in connected environments and understand the tools, systems, and data they can access.
Runtime Policy Enforcement: Define permitted actions and block prohibited activity before execution at supported control points.
Activity Monitoring & Risk Detection: Understand agent activity, identify risky actions, and retain decision evidence for investigation.
Spend Management & Optimization: Understand agent spend, identify waste, and find savings by reducing unnecessary costs.

Top risks in finance

These are action risks, not output risks. The question is not whether the model said something wrong — it is what the agent was allowed to do next.

Unauthorized money movement: an agent initiates, modifies, or approves a transfer beyond the mandate its user actually has.
Bulk data extraction: a reporting or support agent pulls account and transaction records far past the task it was given.
Credential sprawl: long-lived keys to core banking, payment, or ledger APIs sit in agent config, notebooks, shell history, and logs.
Collapsed separation of duties: one agent session both prepares and approves a change, with no second party in the path.
Unregistered third-party reach: an agent calls an ICT provider that never entered the register, or touches an in-scope system outside a change window.
Untraceable action: something changed in a production system and nothing records which person, agent, or policy stood behind it.

How we help

Discover agents and map access. Validate policy. Then enforce it.

Discover and observe: identify agents, map their access, and review real activity before choosing a restriction.
Validate policy: replay expected and prohibited actions and review decision evidence.
Enforce: block prohibited actions at supported control points and retain the evidence.

Agent coverage

Kontext protects your AI workforce, from coding assistants and workplace agents to custom-built agents, across endpoints and cloud environments. Bring agent discovery, access policies, risk monitoring, and spend management together across the agents your organization uses.

Good first policies

Require human approval for anything that moves money, changes a limit, or writes to the ledger.
Deny agent reads of production customer records; allow aggregate queries instead.
Block bulk export of transaction and account data, whatever tool asks for it.
Block tool access outside the approved task.
Escalate tool calls that touch in-scope systems outside an approved change window.

Evidence

Most agent programs can describe their controls but cannot evidence them per action. A decision record closes that gap for questions control owners already get: which third-party systems agents reached and under whose authority (DORA ICT and third-party register), whether a sequence of actions can be reconstructed (MiFID II record-keeping and equivalents), whether least privilege is enforced for non-human actors (EBA ICT and security risk guidelines), where AI controls are evidenced (NIST AI RMF), and which agents can export customer data (SOC 2 and ISO 27001 control catalogs).

Kontext produces the decision record these controls depend on. It does not certify compliance, and nothing here is legal advice.

Get started

Start by seeing what agents already do in your environment, then move money movement, customer data, and production systems behind runtime authorization. Talk to sales or read the deployment docs.