Agentic AI is moving from an idea to an execution question for banks: where can it actually take work off people’s hands, and where should people stay in control?
For a CDO or COO, answering that question means looking beyond the promise of AI. Each use case needs to be concrete enough to assess: What would the agent actually do? Where does a person step in? And how would a pilot prove that it is delivering value?
This guide puts six retail servicing workflows under that lens, showing what agentic AI could look like in practice and what it takes to move each idea from concept to pilot.
For the bigger picture, start with our overview of agentic AI use cases in banking.
Agentic AI use cases in retail banking: 6 workflows to assess
The six workflows below are illustrative designs, offered as candidates for assessment. Test each against your own policies and systems. Your bank defines every baseline from its own records.
1. Transaction dispute intake
Trigger. A customer questions a card transaction and asks the bank to review it.
Steps and context. The agent confirms identity through the bank's standard authentication. It locates the transaction and records the customer's account in their own words. It needs transaction history and card status, plus the bank's policy for each dispute type.
Agent role. The agent builds a complete case file and routes it to the right queue. If the bank approves the wording, it tells the customer the next step.
Human decision boundary. Staff decide liability and any credit. The agent shares an outcome only after a person has made one.
Example exception. The customer cannot identify the transaction, and no match appears in the records. The agent hands the case to a person with the conversation attached.
Pilot measure. Track the share of cases that reach first review with a complete file. Add how often reviewers return to the customer for missing details.
This page stays at the intake step. The full workflow is covered in our guide to AI banking dispute resolution automation.
2. Payment inquiry
Trigger. A customer asks where a payment they sent is and when it will arrive.
Steps and context. The agent confirms identity and finds the payment. It reads the current status and payment messages. It also needs the bank's guidance on expected timing.
Agent role. The agent explains the position in plain language. If the status shows a problem, it prepares an investigation request with the details operations need.
Human decision boundary. Operations staff decide on any recall or amendment. In this design, the agent does not change a payment.
Example exception. The payment shows no status data at all. The agent says so and routes the inquiry to operations.
Pilot measure. Count follow-up contacts per inquiry and compare them with your current figure.
3. Complaint intake and triage
Trigger. A customer reports a problem with a fee and asks for a complaint to be recorded.
Steps and context. The agent captures the complaint in the customer's words and links it to earlier contacts. It needs the bank's complaint categories and handling rules.
Agent role. The agent drafts a summary with a suggested category and routes the case to the owner. It can send the acknowledgement wording the bank has approved.
Human decision boundary. Staff confirm the category, decide any redress, and approve the response. Whether the complaint is upheld stays a staff decision.
Example exception. The message mentions legal action. The agent skips standard routing and sends the case to a senior handler.
Pilot measure. Audit a sample of cases and record how often the suggested category survives review. Compare time to first acknowledgement with your baseline.
4. Onboarding evidence collection
Trigger. An applicant submits an account application with supporting documents.
Steps and context. The agent compares the uploads with the product's evidence list. It needs the application and identity check results, plus the eligibility rules.
Agent role. When an item is missing or unreadable, the agent asks the applicant for a replacement. When the list is complete, it assembles the file for a reviewer.
Human decision boundary. Staff accept the evidence and approve or decline the application.
Example exception. The names on two documents do not match. The agent flags the conflict and passes the file to a reviewer.
Pilot measure. Measure the time from application to complete file. Add the number of requests for missing items per application.
BCG's article on putting agentic AI to work in retail banking discusses onboarding. It also covers how banks can evaluate and oversee agents across the front and back office.
For the wider journey around identity and compliance checks, see our guide to digital onboarding in retail banking.
5. KYC and CDD remediation
Trigger. A periodic review comes due for a customer file that holds outdated information.
Steps and context. The agent reviews the profile, risk rating, and documents on file against the bank's remediation policy.
Agent role. The agent lists the outdated items and contacts the customer through a channel the bank has approved. As documents arrive, it checks each against the requirement. The analyst receives a file with gaps closed or clearly marked.
Human decision boundary. Compliance staff set the risk rating and decide whether the relationship continues. Risk judgment stays with staff.
Example exception. The customer does not respond after the number of attempts the bank defines. A compliance analyst decides the next step.
Pilot measure. Track the share of remediation cases returned complete at first pass. Ask analysts to log why cases come back.
An illustrative refresh with evidence gathering, human review, and exception routing appears in our piece on agentic AI in banking compliance.
6. Routine servicing requests
Trigger. A customer asks for a standard change, such as a card replacement or an address update.
Steps and context. The agent confirms identity and the request type. It needs the customer profile and product rules, plus access to the core and card systems.
Agent role. The agent checks eligibility and submits the change within limits the bank sets. It then tells the customer what happens next.
Human decision boundary. The bank decides which changes an agent may submit alone. Anything outside that list goes to staff for approval.
Example exception. Authentication fails midway. The agent stops, offers the bank's approved alternative route, and hands off to staff.
Pilot measure. Track the share of requests resolved without a handoff. Read it alongside repeat contacts on the same request.
How to evaluate agentic AI workflows in retail banking
Deloitte's guidance on agentic AI in banking points to scope, complexity, effort, and regulatory context when selecting use cases. Use the questions below as discussion prompts for a working session on each workflow.
Scope. Can you state the customer intent in one sentence? Can one queue own the first test?
Complexity. How many rules govern the workflow, and are they written down?
Integration effort. Which systems must the agent read, and which must it write to?
Regulatory context. Which obligations apply to this workflow? Who in compliance signs off on the agent's role?
Authority. Where does the staff decision begin? Is that boundary recorded in policy?
Exceptions. Can you list the most common exceptions from your own case history?
Measurement. Do you have a baseline today, and who owns it?
Use the criteria above in two passes. The CDO leads the first pass and prioritizes the customer and digital workflows worth assessing. The COO co-reads and stress-tests the shortlist in the second pass. That review covers ownership, queues, handoffs, exceptions, staffing, and baselines. A workflow moves forward when the CDO can name the customer case for it. The COO then confirms the operation can support it and measure it.
Where Backbase fits
Customer Operations turns a customer's intent into a resolved outcome. From that intent it runs a customer resolution loop all the way to resolution. Its public-facing featured use-case areas are: Transaction dispute resolution, payment inquiry, complaint resolution, onboarding evidence collection, and KYC / CDD remediation.
Five of the six workflows in this article map to those featured areas. Along the loop, the work includes the following steps:
- classify the customer need
- collect and validate required information
- rules, thresholds, eligibility, controls
- create, update, and route operational work
- keep the customer informed
- escalate when judgment, approval, or exception handling is required
Next step: Prioritize your shortlist
This page helps you describe and question each workflow. Choose two or three that your CDO and COO both want to test. Then use the agentic banking use cases prioritization and readiness method to compare them in detail.
