Credit Card Decision-Making App
Credit Card Decision-Making App
Find the best credit card for every purchase and maximize your cashback effortlessly.
Finance
credit card
Role
UI/UX Designer
Timeline
3 weeks
team
Solo
platform
Mobile
Project Overview
Project Overview
There are 100M+ active credit cards in India, yet most users are leaving money on the table. Around 70% fail to optimize rewards, 50% let points expire, and 60% aren’t even aware of key benefits like lounge access or travel perks.
Instead of making informed decisions, users default to a single card or use UPI for convenience missing out on better rewards simply because choosing the right card is too complex.
There are 100M+ active credit cards in India, yet most users are leaving money on the table. Around 70% fail to optimize rewards, 50% let points expire, and 60% aren’t even aware of key benefits like lounge access or travel perks.
Instead of making informed decisions, users default to a single card or use UPI for convenience missing out on better rewards simply because choosing the right card is too complex.
The Problem
The Problem
Despite having multiple credit cards, users often struggle to decide which card to use for each purchase, as reward structures are complex, there are hidden conditions, and real-time guidance is not available. This leads users to either use a single default card or opt for UPI for convenience, thus missing out on potential cashbacks and rewards.
Despite having multiple credit cards, users often struggle to decide which card to use for each purchase, as reward structures are complex, there are hidden conditions, and real-time guidance is not available. This leads users to either use a single default card or opt for UPI for convenience, thus missing out on potential cashbacks and rewards.
Objective
Objective
Making credit card usage simple and effortless for users, where they can choose the best card for every transaction without any confusion and maximize their rewards and cashback.
Making credit card usage simple and effortless for users, where they can choose the best card for every transaction without any confusion and maximize their rewards and cashback.
Goal
Goal
Giving users fast, clear and actionable recommendations on every transaction, so they can choose the right credit card without guesswork and consistently maximize their rewards.
Giving users fast, clear and actionable recommendations on every transaction, so they can choose the right credit card without guesswork and consistently maximize their rewards.
The Solution
The Solution
Design a smart decision-making system that analyzes a user's purchase context (merchant, amount, category) to recommend the best credit card in real-time, with clear reasoning, and guides users step-by-step from decision to tracking so they can extract maximum value from every transaction.
Design a smart decision-making system that analyzes a user's purchase context (merchant, amount, category) to recommend the best credit card in real-time, with clear reasoning, and guides users step-by-step from decision to tracking so they can extract maximum value from every transaction.
Research
Research
Understanding user behavior, pain points, and decision-making patterns
Understanding user behavior, pain points, and decision-making patterns
Survey
A survey was conducted to understand users' credit card usage behavior, with 32 participants responding. The survey focused on understanding how users use their credit cards, their awareness of rewards, and their purchasing decisions.
5+ Interview
To gain a deeper understanding of users' real-world behavior and decision-making, I conducted one-on-one interviews with over 5 credit card users. These interviews focused on understanding how users use their credit cards, when they get confused, and how they perceive rewards.
Key Insights
Key Insights
Majority users feel they are only capturing 25–50% of rewards.
UPI + single default card dominance, category-specific value mostly missed.
Strong signal: 60%+ users clearly want to use the “best card suggestion” app.
Cognitive overload is universal – 10–90 literate, exhausting complex rules for everyone.
Users “want automation, not more dashboards” – already statements, CRED, reward portals, but no real‑time decision help.
Trust erosion: “upto X%” + caps + exclusions = expected value vs actual value gap.
Latent willingness to switch: 65% users are ready to switch primary card for better benefits, if real value is felt.
Majority users feel they are only capturing 25–50% of rewards.
UPI + single default card dominance, category-specific value mostly missed.
Strong signal: 60%+ users clearly want to use the “best card suggestion” app.
Cognitive overload is universal – 10–90 literate, exhausting complex rules for everyone.
Users “want automation, not more dashboards” – already statements, CRED, reward portals, but no real‑time decision help.
Trust erosion: “upto X%” + caps + exclusions = expected value vs actual value gap.
Latent willingness to switch: 65% users are ready to switch primary card for better benefits, if real value is felt.
Competitor Analysis
Empathy Mapping (Primary Persona – Aditi)
User Flows
Sketchs
UI Design
Design Impact
Design Impact
This solution is expected to reduce decision complexity by making the best credit card choice instantly visible at the moment of purchase. As a result, users can move from guess-based behavior to informed decision-making, leading to better reward utilization and reduced cashback loss.
Over time, the product aims to build a habit loop where users consistently rely on the system for every transaction, improving both engagement and financial outcomes.
This solution is expected to reduce decision complexity by making the best credit card choice instantly visible at the moment of purchase. As a result, users can move from guess-based behavior to informed decision-making, leading to better reward utilization and reduced cashback loss.
Over time, the product aims to build a habit loop where users consistently rely on the system for every transaction, improving both engagement and financial outcomes.