Shared passwords
A session on the customer’s credentials can be the customer, an aggregator or an AI agent. To most systems they look the same.
AI agents are already inside customer accounts, often logged in on the customer’s own password. Candor Agent Defense for Fintech helps institutions see every agent at the account edge, hold each one to what the customer actually approved, stop it when it drifts, and tie every money movement to the agent and the approval behind it.
In October 2026, major U.S. banks reported finding unvetted third-party AI agents inside customer accounts. Many were logged in with credentials customers had handed over, and some took actions the customer never approved (reported by Axios on 22 October 2026 and CBS News on 23 October 2026).
A session on the customer’s credentials can be the customer, an aggregator or an AI agent. To most systems they look the same.
An agent connected to read balances can try to pay a bill, add a payee or send a transfer.
A hijacked or careless agent can reach accounts its customer never connected.
Injected instructions can turn an approved assistant into a payment nobody asked for.
Cutting off one provider should end every one of its sessions, not just the ones you can find.
When a customer disputes a transfer, the institution needs to show which agent acted and under whose approval.
Candor Agent Defense for Fintech is in build. It brings Candor Agent Defense, whose controls are tested on Candor’s own ranges (results below), to the account edge of financial institutions.
Agents that act in your customers’ accounts carry an identity your institution can check and revoke, instead of hiding behind a customer password.
Each agent is held to what the customer approved: which accounts, which payees, how much and until when.
Automation logged in on a customer’s password is identified, kept away from money movement and recorded.
Designed to run inside the institution, with customer data kept there. A Candor-hosted option is planned for institutions that prefer it.
Security and fraud teams see agents, decisions and money movements as they happen.
Tamper-evident records that support dispute investigations, board reporting and examination preparation.
For the CISO and the fraud and risk teams who must answer which agents are inside customer accounts and what they did.
For API-first institutions whose customers connect assistants, budgeting apps and payment agents.
For the platforms that run online banking for many institutions and can protect all of them at once.
Selected results from Candor Agent Defense on Candor’s own test ranges. These are not results from a financial institution; bank-specific results will be published with their dates and environment when they are run.
In a compromised-supervisor drill, all ten affected agents lost authority.
Reported endurance run; 90th-percentile decision latency was 2.4 seconds on the local model.
Revocation, scope and unapproved-destination scenarios contained in a local test range.
It is in build. Banks, credit unions and fintechs can request early access now. Candor confirms scope and dates with each institution directly; nothing on this page is a delivery date.
The design keeps customer data inside the institution. Discovery works from a log slice the institution exports itself, pseudonymized before it leaves: hashed customer ids, no names, no account numbers, no credentials.
No. The aim is to tell customer-approved providers apart from unvetted automation and hold each one to what the customer approved, so legitimate providers keep working.
No. It adds an agent layer your current tools do not have: which agent acted, for which provider, under which customer approval. It is designed to work beside your fraud and identity controls.
No certification is claimed on this page. Candor publishes dated internal test results with their environment; coverage is validated in each institution's environment.
Join the early access list for Candor Agent Defense for Fintech.