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unmatrixai

Fraud, onboarding, and payments

AI agents for fintech: fraud, onboarding and payments

AI agents for fintech are systems that investigate fraud alerts and disputes, onboard customers and businesses, resolve payment exceptions and handle support cases at the volume and speed a growing platform needs. Unmatrix AI builds them into your existing stack in a twelve-week deployment, with the controls a sponsor bank or regulator will ask about.

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Workflows

What do we build for fintech?

The workflows we usually start with, and the architecture each one is built on.

  • Fraud alert and dispute investigation

    Gather transaction, device and account evidence, apply your rules, and draft the case for an analyst or the chargeback package.

    Built as

    Autonomous agents (ReAct)

  • KYB and KYC onboarding

    Verify documents, registries and sanctions, and route only the exceptions to a person.

    Built as

    LangGraph workflow agents

  • Payment exceptions

    Investigate failed, delayed or mismatched payments across processors and ledgers and propose the fix.

    Built as

    Autonomous agents (ReAct)

  • Support automation

    Resolve routine account and card questions from your knowledge base and account data, escalating with a summary.

    Built as

    RAG agents

Constraints

What shapes the build?

Sponsor bank and regulator scrutiny
Controls, evals and audit logs designed to survive a partner bank's review.
Latency
Real-time authorisation paths stay deterministic. Agents work the queues behind them, in seconds to minutes.
PCI scope
Card data never enters a prompt. Agents work with tokenised references only.
Speed of delivery
Built on your stack in weeks, with your engineers pairing from day one.

Worked example

A typical build: card dispute investigation

A payments company handles thousands of disputes a month. Analysts spend most of each case collecting evidence from five tools.

  1. 01

    Trigger

    A cardholder files a dispute and it lands in the queue.

  2. 02

    Collect

    The agent gathers the transaction, device and session data, account history and merchant details.

  3. 03

    Assess

    It applies your rules and prior patterns and writes a recommendation with the evidence attached.

  4. 04

    Review

    Below a threshold the recommendation is accepted automatically. Above it, an analyst decides in minutes.

  5. 05

    Submit

    The chargeback or resolution package is filed with the network or the customer.

Analysts decide with the evidence already assembled. Packages are complete, so representment outcomes improve.

Integration

Which systems do we work with?

  • Stripe
  • Adyen
  • Marqeta
  • Plaid
  • Alloy
  • Unit21
  • Sardine
  • Zendesk
  • Snowflake

Anything with an API or a file interface can be integrated. These are the systems we meet most often in fintech.

Questions

What fintech teams ask

How fast can you ship?

A first agent on live volume inside the twelve-week deployment, and usually sooner for a well-scoped queue.

Will our sponsor bank accept this?

We design for that review: documented controls, eval results, audit logs and human approval for decisions that affect customers.

Can it act in real time?

Agents suit case work measured in seconds to minutes. Real-time authorisation stays rule-based. Agents work the exceptions.

Does card data go into prompts?

No. Tokenised references only. PCI scope stays with your existing systems.

Related

Next step

Pick one workflow. We will be at your office in two weeks.

A thirty-minute call to find the right first workflow, followed by a written scoping note. No deck, no pilot.

Book a call