Banking, built around the relationship

Know your customer.Make the next movematter.

AI-Powered Customer Relationship Agent for Banking

One intelligent relationship cockpit. Bring customer context, credit insights and the right next action into every banker’s conversation.

Relationship cockpit

Customer 360

Illustrative view

“Can Mohammed get a loan top-up? What should I do next?”

MA

Mohammed Ali

Premier customer · 8-year relationship

Total deposits$180,000
Loan exposure$320,000
Credit score768

A clearer way forward

$30,000 of a $50,000 top-up request may be eligible.

Illustrative partial eligibility · Subject to bank review

Next best action

Keep the relationship moving

Create a lead with the context and next step for the relationship manager.

Customer context → Policy checks → Explained next action

More informed conversationsClearer decisionsConnected follow-through

The business opportunity

Less searching.More relationship building.

Your teams already have the questions. Help them connect the information, understand the options and move the conversation forward.

01 / Outcome

Know the whole customer

Bring accounts, deposits, loans and engagement history into one relationship view.

Measure: meeting preparation time

02 / Outcome

Make growth more relevant

Identify top-up, card and cross-sell opportunities in the context of a customer’s needs and eligibility.

Measure: qualified lead conversion

03 / Outcome

Move with greater clarity

See exposure, policy checks and decision reasons together, with a clear next step for your team.

Measure: time to review & follow up

Outcomes to target and measure in a pilot; no performance improvement is guaranteed.

Built around the people who bank

Different responsibilities.One connected relationship.

For the next customer conversation

Walk into every meeting with the full picture.

Spend less time piecing together information and more time understanding what your customer needs next.

Questions this role asks

01“What should I know before Mohammed’s review?”

02“Is he eligible for an additional loan?”

03“Which opportunities need my follow-up?”

From a question to a next step

A better conversationstarts here.

Follow Mohammed’s relationship from understanding his needs to assessing an opportunity and arranging a follow-up.

01 / Prepare for the meeting

“Give me the full customer picture.”

Understand the relationship before the conversation.

Total deposits
$180,000
Loan exposure
$320,000
Credit card balance
$18,500
Term deposit balance
$75,000

Recommended next stepPrepare a relationship review, then explore relevant borrowing needs and follow-up opportunities.

02 / Assess an opportunity

“Can Mohammed get a $50,000 top-up?”

Connect eligibility, risk and a clear explanation.

Requested top-up
$50,000
Illustrative eligible amount
$30,000
Outcome
Partially eligible
Review context
Affordability · exposure · policy

Recommended next stepCreate a lead with the request, eligible amount and decision reason. Assign it to the relationship manager to discuss the remaining requirement and alternatives.

03 / Explore a card limit increase

“Can we increase his credit limit?”

Review the right evidence and plan the next action.

Known card balance
$18,500
Current limit & utilization
Required for assessment
Policy & affordability
Check configured rules
Eligible increase
Pending authorized assessment

Recommended next stepPresent the recommendation and reasons for authorized review. Capture a follow-up lead where the customer needs a conversation or an alternative.

Illustrative experience using sample data from the concept. Recommendations require configured rules, available evidence and authorized review.

Relationship orchestration

One request.
The right expertise, working together.

01

Understand

Ask in everyday language. Start with the customer and the decision you need to make.

02

Connect

Bring together customer, credit, loan, card and risk perspectives.

03

Explain

See the eligible option, the decision reason and any constraints.

04

Follow through

Capture a qualified lead, assign an owner and track the next conversation.

Next step

Whatever the outcome, keep the next step clear.

01

Eligible

Confirm the option for authorized review.

02

Partially eligible

Discuss the available amount and alternatives.

03

Not eligible

Explain the reason and arrange a follow-up.

Confidence at every step

Your relationships.Your rules.Your people in control.

Give bankers useful answers within the boundaries of their role, their portfolio and your bank’s policies.

  • 01

    The right information for the right role

    Scope customer records and insights to authorized responsibilities, branches and portfolios.

  • 02

    Decisions that can be explained

    Bring customer context, policy checks and reasons into the review, with a record of the action.

  • 03

    Bankers retain decision authority

    Credit decisions and execution follow your bank’s approval process. The agent supports authorized people.

For technology & data teams

Explore what’s under the hood.

Architecture, specialist agents and the governed data foundation.

One relationship agent. Eight specialist roles.

01Customer 36002Credit assessment03Credit cards04Loans05Risk06Loan top-up07Credit top-up08Lead creation

Microsoft Fabric connects source data through OneLake, curated data layers and domain semantic models. Specialist agents bring those insights into a coordinated relationship experience, with Power BI for visual analysis.

01

Data foundation

Customer profiles, accounts and transactions, loans and repayments, cards, deposits, business rules, product pricing and leads.

02

Access & accountability

Role-based access, row-level security and model permissions scope the information available. Decision and lead records support auditability.

03

Authorized operations

The current site also describes a separate Operations Agent for approved credit workflows. Integration scope and platform availability must be confirmed for each deployment.

Solution architecture

Relationship ecosystem
Download relationship ecosystem
AI-Powered Customer Relationship Agent for Banking: relationship manager asks in natural language, the Customer Relationship Agent orchestrates eight specialists, and Microsoft Fabric supports data, experience and governance.

Scroll sideways to read the full diagram. Download for a full-resolution view.

Reference architecture from the NeoStats relationship concept. Final controls, integration design and service availability depend on the agreed deployment.

Start with a business priority

Make your first
pilot count.

Bring your business and technology teams together around a focused customer journey and measurable success criteria.

  1. 01

    Choose the moment

    Customer reviews, loan top-ups, card limit increases or relationship follow-ups.

  2. 02

    Define the boundaries

    Agree customer data, business rules, role permissions and approval responsibilities.

  3. 03

    Measure what matters

    Track preparation time, review turnaround, follow-up completion and lead conversion.

Let’s build stronger customer relationships

Make your next customer
conversation your best one.

See what a connected relationship experience could look like for your bank.