Reducing Loan Drop-Offs
How UX Research Reduced Early Drop-Offs by 35% and Boosted Loan Applications by 25%
Role
UX Research Lead
Goal
Understand why eligible users abandoned mid-flow and design a more trustworthy, effortless borrowing experience.
Method
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15 user interviews
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Task-based cognitive walkthroughs
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3 user journey maps
Outcome
35% fewer early drop-offs with upfront eligibility.
25% more completions from clearer cost summaries
Turning Loan Drop-Offs Into User Confidence
When eligible users abandoned the loan flow early, the fintech team suspected deeper experience and trust gaps. Through interviews, journey mapping, and task-based walkthroughs, I uncovered three root causes: eligibility anxiety, hidden costs, and lack of in-flow reassurance. These insights informed a redesigned 3-step flow with upfront eligibility and transparent cost summaries, reducing abandonment and helping users feel confident choosing formal loans over informal sources.
01. The Challenge
Business Challenge
Loan-eligible users were dropping off before completing the flow, even though they fit the salary criteria and had borrowing intent. Instead of using the app, many turned to informal sources like moneylenders or friends and family. For the product team, this raised two critical questions:
Experience Barriers: Was the app’s flow itself pushing users away? For example: unclear eligibility, hidden costs, or a long and effortful process compared to informal borrowing.
Value Perception: Or was the app failing to deliver on its core promise of instant, judgment-free loans in a way that matched users’ mental models and cultural context?
The team needed to understand where trust was broken and why users preferred quicker, but often riskier alternatives.
Research Goals
The study aimed to uncover both behavioral drivers and experience-level barriers influencing loan abandonment, with three key goals:
Pinpoint Drop-Off Triggers
Identify the exact points in the journey where users abandoned and what emotions or doubts drove that decision.
Decode Borrowing Mental Models
Explore how users weigh formal vs. informal options, what “instant” means to them, and where judgment or trust concerns come in.
Inform Design Interventions
Translate findings into actionable design changes that simplify the flow, reduce uncertainty, and increase confidence in formal borrowing.
02. Research Strategy
To uncover why users dropped off and what would make them choose formal instant loans, I conducted a generative study blending interviews with real borrowing stories and task-based walkthroughs of the app. This let me capture both the why behind borrowing decisions and the where of usability breakdowns.
Semi Structured Interviews
Goal: Understand motivations, mental models, and trade-offs users make between formal and informal borrowing.
Methods: 15 in-depth interviews with recent borrowers across fintech apps, local moneylenders, and friends/family.
Output: Narratives on borrowing triggers, perceived risks, and what users value most when choosing a loan source.
Task-Based Cognitive Walk-Through
Goal: To observe real moments of hesitation and information-seeking behavior in the app flow.
Methods: Asked participants to check eligibility or simulate starting a loan application.
Output: Pinpointed usability friction such as early document barriers, cost confusion, and anxiety moments, captured with verbatim quotes.
Together, these methods revealed not just what users said about borrowing, but also how they acted in real moments of hesitation, giving me both the behavioral context and in-flow evidence needed to design solutions with confidence.
03. From Raw Data to Behavioral Patterns
I combined user stories from interviews with observed behaviors from walkthroughs to uncover not only why people dropped off, but also where trust and confidence broke down in the app.
01
Borrowing Stories
Why Users Borrow and How They Choose Their Source
Interviews revealed the motivations and trade-offs behind borrowing:
“If I ask my uncle, I can clear doubts in two WhatsApp messages—here, I don’t even know who to ask if I’m stuck. With friends, it’s done in one conversation. No forms, no waiting.”
Trust and Speed
Friends, family, or moneylenders felt faster and safer in emergencies (no documents, trust-based).
“It feels odd to ask family for money just to buy a new bike. They’ll think I’m being careless. With apps, no one knows why I’m borrowing, it feels more private.”
Social Judgement versus Discretion
Borrowing for “wants” (like a new bike) carried stigma socially, but fintech apps felt more discreet.
For once, I can get money without being judged. I just need the app to actually be as quick as it says. These apps make me feel like I can finally buy things for myself, not just emergencies.”
Formal Loans as
an Opportunity
Young salaried users saw instant loans as a way to upgrade their lives—if the process delivered on its promise of speed and simplicity.
While interviews revealed why people chose or avoided certain borrowing options, the walkthroughs showed where those doubts turned into drop-offs inside the app.
02
From Pain Points to Patterns
Synthesizing Data to Uncover Where The Flow Breaks
By clustering observations from task-based walkthroughs, three clear categories of in-app barriers emerged:
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Emotional → Eligibility anxiety, fear of rejection, and frustration with wasted time during urgent borrowing needs.
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Cognitive → Confusion around repayment costs, unclear breakdowns, and jargon-heavy language.
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Procedural → Early document uploads, lengthy multi-step flows, and lack of in-flow support or FAQs.
These patterns uncovered not just moments of drop-off, but root causes, making it clear where the experience needed simplification, reassurance, and clarity to earn user confidence.
03
Different People, Different Journeys
User Personas and Journey Maps
Not all users experienced the loan flow in the same way. By cross-referencing borrowing triggers with the friction categories from walkthroughs, I identified three borrower personas, each with distinct motivations, thresholds for risk, and abandonment points.
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The Anxious First Timer → Urgent needs but no prior loan experience. Hesitates at eligibility, fears wasted effort, and easily abandons when clarity is missing.
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The Hesitant Optimizer → Evaluates multiple options. Motivated by stretching every rupee, but drops off if cost details are unclear or scattered.
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The Time-Starved Juggler → Pressed for time, juggling responsibilities. Bounces quickly when flows are too long or require documents too early.
Personas highlighted different trust thresholds and borrowing triggers, ensuring solutions worked for more than one type of borrower. To go deeper, I mapped user journeys for each persona, capturing their actions, emotions, friction points, and “switch-out” moments when they abandoned the app.
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The Anxious First Timer → Marketing drew him in, but lack of upfront eligibility and long flows triggered fear of rejection. Switched out to family for reassurance.
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The Hesitant Optimizer → Compared apps side-by-side. Left when this app couldn’t provide clear repayment terms as quickly as a competitor.
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The Time-Starved Juggler → Needed speed above all. Dropped off at document upload, opting instead for a faster employer advance—even at higher long-term cost.
Journey maps revealed the emotional peaks and drop-off moments driving loan abandonment. Although each persona had unique motivations, one common theme emerged:
Users weren’t rejecting the idea of loans, they were rejecting uncertainty.
This insight directly informed the design solutions: reduce ambiguity, provide upfront clarity, and reassure users at critical decision points.
04. Turning Insights Into Design Solutions
My research didn’t just reveal what was broken, it showed exactly where design could make the biggest difference. I translated friction points into targeted opportunities to reduce cognitive load, increase clarity, and meet users where they were emotionally and contextually. Each solution focused on reshaping the borrowing flow to feel faster, easier, and more human, without compromising compliance or control.
01
Show Eligibility First, Ask Later
Simplified the flow, restored confidence, increased conversions
Friction Point: Users dropped off early when asked for documents and personal details before knowing if they were even eligible.
Key Insight: Lack of clarity made users feel the app wasted time, especially in urgent borrowing situations.
Design Direction: Reworked the experience to surface a lightweight eligibility check as the first step on the homepage - no documents or login required.
Impact: Reduced cognitive effort and drop-offs, making the product feel faster, more transparent, and worth exploring.
Before
After
Step 1
Scan Through App's Offerings
Step 2
Click 'Apply for Loan'
Step 3
Log In or Sign Up
Step 4
Fill Out a Long Form with Personal Details
Step 5
Upload Documents
Step 6
See Eligibility
Procedural Friction Point
causing hesitation or abondonment
Simplified 3-step flow
02
See the Full Picture Before You Borrow
Turning abstract numbers into a clear, upfront loan calculator
Friction Point: Borrowers struggled to understand what a loan would actually mean for them financially. Interest rates and percentages felt abstract, and without a simple breakdown, users were left to sit with calculators, piecing together EMIs, fees, and total repayments on their own.
Key Insight: Users didn’t want abstract percentages; they wanted a real preview of their loan commitment. They wanted to see: “If I take this loan, how much will I pay every month, and how much in total?”
Design Direction: Introduced a cost summary module that displays loan amount, interest, repayment schedule, and total payable immediately after eligibility is confirmed.
Before
After
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Costs revealed late and scattered across steps
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EMIs and totals shown only at final offer stage
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Users had to calculate on their own
Cognitive overload
causing confusion and stress
Instant Transparency
helping informed decision-making
Impact: Made loan costs transparent upfront, reducing confusion and hesitation, and increasing user confidence to proceed.
03
Offer a Human-Like Touchpoint at Key Moments
Built trust through instant answers + simpler financial guidance
Friction Point: Users trusted informal sources because they could “talk to someone.” The app lacked both real-time answers and help in understanding financial terms, leading to hesitation.
Key Insight: Even small, human-like interactions, whether quick answers in the moment or plain-language guidance that feels personal, can bridge the trust gap and keep users moving forward.
Design Direction: Added layered support: smart FAQs, quick chat prompts, proactive reassurance messages, and guides/tutorials to simplify confusing financial language.
Before
After
Start Loan Application
Fill Out Form
Review Terms
Submit Application
😟
APR? Foreclosure charges? What does this mean?
😰
Step 1
Step 2
Step 3
Step 4
Am I missing something? Should I ask someone first?
Emotional Drop-Off Triggers
making users feel uncertain and isolated
Impact: Reduced last-minute abandonment and positioned the app as a reliable, user-friendly ally.
Layered guidance and handholding
increading usertrust and confidence
04
Surface the 'Judgement-Free' Promise
Made the value proposition obvious, relatable, and stigma-safe
Friction Point: The app promised judgment-free loans, but the experience didn’t highlight it. Users, especially when borrowing for “wants” (honeymoon, scooter, home upgrade), feared social judgment from friends/family and couldn’t tell if such reasons were acceptable.
Key Insight: Formal loans felt attractive because they’re private. Users wanted clear, visible reassurance that any legitimate reason is okay, and proof that people 'like me' have used the app for aspirations, not just emergencies.
Design Direction: Made the judgment-free promise visible by mapping borrowing needs into relatable themes and embedding real user stories.
Aspirations made possible by
FastFinance
Impact: Highlighting the judgment-free promise reduced stigma-driven hesitation and built trust, boosting confidence in using FastFinance for both needs and aspirations.
05. Impact at a Glance
35%
reduction in early drop-offs after eligibility checks were moved upfront.
25%
increase in applications completed when loan costs were shown transparently in a calculator format.
40%
of applicants engaged with new in-app support (FAQs, chat, tutorials), showing a measurable shift away from relying on friends/family for reassurance.
3
unique borrower personas mapped, guiding future product iterations and marketing strategies.
06. What I Bring to Future UX Projects
Through this project, I strengthened core research-to-design skills, from uncovering hidden barriers to shaping adoption-ready solutions, that I now carry into every future UX project.