A customer request rarely ends in one step. It moves through verification, evidence, exceptions, and approval before it resolves. Agentic AI could support that multi-step work within limits the bank defines.
Agentic AI describes software that can plan and carry out multi-step work toward a goal, instead of only answering a single question. For a fuller explanation, see what agentic banking means.
This overview describes nine illustrative workflows where agentic AI could apply. It offers a market view of possibilities. Each workflow is a possibility that a bank can adapt to its own limits.
Nine illustrative workflows where agentic AI could apply
Each example describes work an agent could support. The bank decides where a person reviews the outcome.
1. New-customer onboarding and evidence collection
An agent could build the document checklist for a product and request whatever is missing. It might flag mismatches for a person to review before the account opens.
2. Loan origination and credit-file preparation
An agent might collect supporting documents and flag inconsistencies, so the file reaches the underwriter ready for review. See how loan origination fits into the sales process.
3. Payment inquiries and status tracing
An agent could trace a payment across several systems and give the customer a status update. The bank sets when the agent answers directly and when an employee steps in.
4. Customer-initiated transaction disputes
When a customer disputes a charge, an agent might gather the transaction details and check them against the bank's dispute rules. It could then prepare a recommended outcome for review.
5. Bank-initiated fraud investigation
When the bank's own monitoring raises a flag, an agent could compile transaction history and related accounts into a case summary. A human investigator would likely confirm the finding before action. For detail, see the page on agentic AI fraud prevention in banking (link to https://www.backbase.com/blog/agentic-ai-fraud-prevention-banking).
6. KYC/CDD remediation for existing customers
An agent might identify which customer files are due for a refresh and request updated documents. It could check them against current requirements before a compliance officer confirms.
7. Formal complaint resolution
An agent could log a formal complaint and route it to the right team. It might then track the case against the response timeline set by bank policy.
8. Reconciliation exceptions
An agent might investigate a mismatch between systems such as ledgers and payment rails, then propose a correction. A finance team member could approve it.
9. Relationship manager preparation and guidance
Before a client meeting, an agent could assemble the client picture from several systems and suggest a next step. The relationship manager still leads the conversation.
Commercial banks are exploring what continuous monitoring of a portfolio might look like in this piece on continuous relationship intelligence. Private banks are looking at how to redesign RM workflows around this kind of support in this piece on freeing relationship managers to perform.
How banks connect work across systems
As work moves between a customer channel, employee teams, and existing systems before reaching an outcome, banks need shared context and bank-defined policy to travel with it.
Backbase built the AI-native banking OS, which acts as a bank's control plane and turns fragmented operations across channels into a Unified Frontline. It connects customers, employees, and AI agents, giving each shared context and the authority the bank has defined for them.
Its Digital Banking offering creates the interface, and the AI-native Banking OS powers Agentic Banking as it resolves the work. Within Agentic Banking, Conversational Banking engages, Relationship Intelligence guides, and Customer Operations resolves banking work.
Frequently asked questions
Why does resolving a request differ from just answering it?
Resolving a request moves the underlying task forward, such as updating a record or closing a case. That difference shapes which of these workflows suit an agent well.
Where can I compare agentic AI providers for banks?
See our comparison of agentic AI providers for banks for a closer look at how different vendors approach this space.
