The Smartest Payment Is the One You Barely Have to Think About
Reimagining everyday banking through behavioural intelligence and predictive payments.
Domain
Banking & Finance
Tools used
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Claude and ChatGPT
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NPCI
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Nikhil Kamat's Podcast
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Figma
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Ground Research & observations
Usage
P2P
Duration
3 weeks, 2026
Overview
People are creatures of habit.
Rahul visits the same tea stall every morning, buys groceries from the same neighbourhood shop and gets milk from the same vendor. His spending patterns are predictable, yet every UPI payment requires him to repeat the same steps: scan, enter an amount and confirm.
What if his banking application could recognise familiar merchants, understand his spending habits and suggest what he is likely to pay?
This concept explores how AI can transform transaction history into a more intelligent, personalised payment experience.
What was the problem?
Imagine Rahul stopping at his regular tea stall before work.
He scans the QR code, enters ₹55 and completes his payment. The next morning, he repeats the same process.
His banking application has a history of previous payments, including the merchant, amount and transaction frequency. However, it treats every payment as an independent interaction.
The challenge wasn't making UPI faster. It was making payments more contextual.
This created opportunities around:
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Repetitive amount entry.
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Limited use of transaction history.
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No contextual recognition of familiar merchants.
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Generic payment experiences.
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Missed opportunities for personalised assistance.
Why This Matters
Digital payments have become part of everyday life. Yet the experience remains largely transactional.
Customers repeatedly interact with the same merchants, make familiar purchases and develop predictable spending habits. Here's an opportunity to make these interactions more meaningful.
This matters because:
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Everyday convenience: Small, repetitive interactions add up across daily life.
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Behavioural understanding: Transaction history can help applications understand customer routines.
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Relevant personalisation: Familiar payment experiences can become more contextual instead of generic.
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Customer confidence: Transparent suggestions can make digital payments feel more intuitive.
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Smarter banking: Applications can evolve from recording transactions to actively helping customers.
What was the design opportunity?
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Recognising frequently visited merchants.
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Understanding recurring payment patterns.
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Predicting likely transaction amounts.
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Simplifying repeat payment journeys.
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Introducing contextual AI assistance.
The opportunity is to make banking understand recurring behaviour instead of simply recording transactions.
Key Pointers
25.47 Bn
UPI transactions
October 2026
₹31.53 Lakh Cr
Transaction value
October 2026
25.47 Bn
Person-to-merchant payments
August 2025
63.5%
Share of UPI transaction volume
P2M August 2025
Source: NPCI UPI Product Statistics and UPI Ecosystem Statistics. The P2M share is calculated from NPCI's August 2025 figures; reporting periods differ.
What did I do?
I conceptualised an AI-powered payment experience that turns transaction history into useful, contextual recommendations.
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Behavioural Experience Mapping: Identified recurring payment habits and everyday interactions.
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Payment Journey Design: Explored a simpler QR scanning and payment confirmation experience.
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AI Experience Strategy: Defined opportunities for predictive amount suggestions.
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Merchant Recognition: Explored identifying familiar merchants through payment identifiers.
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Personalisation Strategy: Conceptualised recommendations based on historical transactions.
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Future-State Vision: Defined opportunities to evolve towards intelligent financial assistance.
Experience Vision
Imagine scanning a familiar merchant's QR code and seeing more than just a payment screen.
The application recognises the merchant and understands how much you usually spend there.
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Recognise: Identify familiar merchants using payment details.
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Confirm: Let customers accept, edit or manually enter the amount.
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Understand: Retrieve relevant transaction history.
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Suggest: Recommend a likely payment amount.
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Pay: Complete the transaction after customer authorisation.
Value Created
The concept creates value beyond reducing the number of steps in a payment journey.
For Customers
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Less repetitive effort.
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More relevant payment suggestions.
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Personalised everyday banking.
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Greater convenience and control.
For Banks
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More meaningful customer engagement.
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Better understanding of recurring payment behaviour.
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Opportunities for personalised financial services.
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A foundation for intelligent banking experiences.
For Banking Ecosystem
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More contextual digital interactions.
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Opportunities for responsible AI adoption.
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A foundation for connected commerce and agentic payments.
North Star Metric
Make everyday payments faster, simpler and more personalised.
The experience will be measured by how effectively AI reduces repetitive effort while maintaining customer confidence.
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Payment Time: Reduce time taken to complete a payment.
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Suggestion Adoption: Track how often customers use suggested amounts.
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Prediction Accuracy: Measure how relevant the suggested amounts are.
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Repeat Usage: Track usage across familiar merchants.
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Customer Trust: Monitor feedback and corrections.
North Star Metric: Increase the percentage of repeat-merchant payments completed using AI-suggested amounts.
UX Thinking
The design focuses on making technology anticipate needs without taking control away from customers.
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Understand Before Suggesting: Use historical behaviour to make relevant recommendations.
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Build Trust Through Context: Explain why an amount is recommended.
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Reduce Repetitive Effort: Avoid asking customers to repeatedly enter familiar information.
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Keep Customers in Control: Make every suggestion editable.
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Automate Responsibly: Introduce intelligent assistance without compromising payment security.
What Makes This Interesting
Most banking applications are designed around transactions.
This concept explores how they could be designed around the people making those transactions.
Instead of simply recording where money goes, the application begins recognising patterns, understanding routines and making the next interaction easier.
The shift is from transaction-based banking to behaviour-aware banking.
Visual Glimpse
What's Next
The future vision extends beyond individual payment suggestions towards a connected, agentic commerce ecosystem.
Merchant Intelligence
Integrate merchant billing and POS systems to understand best-selling products, popular combinations, peak hours and customer buying patterns.
Personalised Purchase Recommendations
Identify products customers regularly purchase and surface relevant suggestions.
Merchant Growth Insights
Help small businesses understand demand, plan inventory and identify purchasing trends.
Conversational Payment Agents
Allow customers to request purchases through natural language, such as "Pay for usual breakfast at the tea stall." or "Order 3 McAloo Tikki burgers without Coke from Zomato at Home."
Delegated Agentic Payments
Enable authorised agents to complete eligible transactions within customer-defined limits and permissions.
Connected Neighbourhood Commerce
Connect local merchants, product discovery, ordering and payments into a more integrated experience.
Future value: Better merchant decision-making, more relevant customer recommendations and a connected local commerce ecosystem.