Phinite for Banking

AI agents for banking

A model that hallucinates returns a wrong answer. An agent inside your bank posts a wrong credit, clears a wrong alert, or opens a wrong account. Phinite checks every action against policy before it runs.

Start Building

Book a Demo

90+

Challenges

Four pressures your operations budget is already carrying

Cost, alert volume, and switching speed all press on the same queues. Phinite puts agents on them with policy checked before anything posts.

Manual review is priced into every account

Cost to serve is set by the work your team does twice, on every account you open and every one you keep. Phinite agents clear the routine path end to end and escalate the exceptions, so review time goes to the files that actually need a person.

Analysts spend the day closing alerts that were never cases

Screening volume forces triage by sampling, and most of what reaches an analyst resolves to nothing. Phinite agents enrich the alert, gather the evidence, and draft the narrative, then hand a reviewer a decision-ready case instead of a raw hit.

A customer can move a deposit relationship in an afternoon

Your customer compares you to whichever app answered fastest, not to your peer group. Phinite agents resolve balance, statement, and maintenance requests across channels, and hand off with the full context attached when a person should take it.

Your core was not built to give a new workflow a clean interface

Every change lands as integration work, which is why good ideas sit in a backlog. Phinite runs above the core and reaches it as a typed, permissioned tool, alongside your card, case, and CRM systems, so nothing has to be migrated first.

Manual review is priced into every account

Analysts spend the day closing alerts that were never cases

A customer can move a deposit relationship in an afternoon

Your core was not built to give a new workflow a clean interface

What are AI agents for banking?

`Phinite is a multi-agent AI platform used in retail and commercial banking to run account onboarding, payments and disputes, financial crime operations, lending, and servicing as governed agent systems, with policy checked at runtime before an agent touches an account.`

Functions

Where AI agents already carry a queue

Phinite runs onboarding, payments, financial crime, lending, and servicing against your core, with policy in front of every action.

Account onboarding
Collect, verify, and route new account applications, and escalate the exceptions rather than guessing at them.
Payments and disputes
Work a disputed transaction from intake through evidence gathering to the network deadline.
Financial crime operations
Assemble the alert file, narrate the finding, and hand a reviewer a decision-ready case instead of a raw hit.
Lending origination
Move an application through intake, document verification, and analysis, with each stage recorded.
Servicing and contact center
Resolve balance, statement, and maintenance requests across channels, and hand off with the context attached.
Collections and recoveries
Sequence outreach against the treatment your policy allows, and log every contact attempt.

Account onboarding

Collect, verify, and route new account applications, and escalate the exceptions rather than guessing at them.

Illustration for Order support and WISMO

Payments and disputes

Work a disputed transaction from intake through evidence gathering to the network deadline.

Illustration for Returns, refunds, and exchanges

Financial crime operations

Assemble the alert file, narrate the finding, and hand a reviewer a decision-ready case instead of a raw hit.

Illustration for Conversational shopping and discovery

Lending origination

Move an application through intake, document verification, and analysis, with each stage recorded.

Illustration for Cart recovery and lifecycle messaging

Servicing and contact center

Resolve balance, statement, and maintenance requests across channels, and hand off with the context attached.

Illustration for Catalog and content operations

Collections and recoveries

Sequence outreach against the treatment your policy allows, and log every contact attempt.

Illustration for Fraud, chargebacks, and fulfillment exceptions

Enterprise platform

Built for secure, enterprise AI at scale

Deploy AI agents with enterprise-grade security, governance, observability, and infrastructure designed for production from day one.

Multi-Tenant Workspace Isolation

Every organization operates in its own isolated workspace with dedicated knowledge, permissions, and execution environments.

Enterprise Deployment

Deploy across development, staging, and production environments with controlled releases and predictable scaling.

Governance & Auditability

Track every agent action with role-based access, approval workflows, and comprehensive audit logs.

Observability & Guardrails

Monitor agent performance in real time while enforcing security policies, human oversight, and operational guardrails.

Usecases

Three queues to put live first

Start where volume is high, ambiguity is low, and one person in operations owns the outcome.

Deposit Account Opening

Dispute and Chargeback Handling

Screening Alert Triage

Deposit account opening

Take an application from submission to funded account, with identity and documentation checks recorded step by step.

Identity Checks

Documentation

Funded Account

Dispute and chargeback handling

Intake the customer's claim, pull the transaction evidence, and file inside the network window, with provisional credit routed for approval.

Transaction Evidence

Network Window

Provisional Credit

Screening alert triage

Enrich and narrate every alert, close the plainly clear ones under policy, and escalate anything ambiguous to a named analyst.

Alert Enrichment

Drafted Narrative

Analyst Escalation

Deployment path

How to deploy AI agents for banking

Start on one queue, then reuse the same policy and tooling across onboarding, payments, financial crime, and lending.

Pick the queue

Start where volume is high, ambiguity is low, and one person in operations owns the outcome.

Compose the graph

Build the flow in Agent Graph Studio, and wire your core, card, and case systems as typed tools.

Replay against history

Run the agent in Evaluation over real past volume, before a live account is involved.

Release under policy

Turn it on with approval thresholds and audit already attached, then reuse the pattern on the next queue.

Integrations

Connect your banking technology stack

Your core, card processor, case management, screening, and CRM systems connect as typed tools with scoped credentials. No agent reaches one without passing policy first.