Education Loan Decision & Repayment Survey
Map how student borrowers evaluate lenders, compare interest structures, and navigate repayment terms, so you can sharpen acquisition targeting, fix pricing positioning, and reduce early-stage drop-off in your loan conversion funnel.
CONTEXT & RELEVANCE
Why run this survey now
Most education lenders don't lose borrowers purely on interest rate. They lose them due to opaque fee structures, misread repayment capacity, co-borrower friction, disbursement delays, and post-graduation income uncertainty, none of which fully show up in credit bureau reports or loan origination system data.
If you are...
- Bank vs NBFC/fintech lender
- Education loan product head
- Retail credit portfolio leader
- Student lending growth head
- EdTech or institution partner
You're likely facing...
- Drop-offs at co-borrower stage
- Lender fit confusion: bank vs NBFC
- Banks = safe/slow perception
- NBFCs = fast/high-cost perception
- Repayment stress vs early prepayment gap
This will help answer...
- Lender preference drivers beyond rate
- Application drop-off stage
- Borrower segment by institution type
- Fee and tenure sensitivity
- Refinance and switching triggers
RESEARCH THEMES
What This Survey Investigates
Eight interconnected research themes that map the complete borrower journey from loan awareness to full repayment.
Discovery & Awareness
- First information source consulted
- Lender shortlisting triggers
Lender Preference
- Public bank vs. NBFC vs. fintech preference
- Collateral requirement as selection filter
Product & Coverage
- Loan amount vs. actual cost gap
- Covered vs. uncovered expense categories
Application Friction
- Document submission drop-off points
- Approval timeline vs. admission deadline conflict
Pricing & WTP
- Interest rate sensitivity by loan tenure
- Processing fee tolerance thresholds
Repayment Behaviour
- EMI start timing vs. employment status
- Prepayment frequency and trigger events
Servicing & Support
- Relationship manager accessibility post-disbursal
- Digital self-service vs. branch dependency
Switching & Advocacy
- Balance transfer consideration and triggers
- Referral intent by satisfaction segment
SAMPLING STRATEGY
Tell us about your ideal sample
Help us understand your target respondent profile. Select what applies, we'll design the optimal sample plan based on your inputs.
METHODOLOGY
Survey approach
For the Education Loan Decision and Repayment Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across borrower segments and repayment stages.
EXECUTION PROCESS
How we execute
A proven 9-step process from scoping to delivery, designed to ensure quality, speed, and actionable insights.
Define the decision frame
Confirm objectives, target cohorts, geographies, and reporting cuts
Define the decision frame
Design the instrument
Build workstream modules mapped to outputs (drivers, friction, pricing, retention, trust)
Design the instrument
Lock the questionnaire
Review wording, sequencing, LOI, and competitive context; approve final version
Lock the questionnaire
Pilot and calibrate
Test comprehension and ease quality; refine quotas and remove friction where needed
Pilot and calibrate
Run fieldwork
Execute collection with active quota management and feasibility controls
Run fieldwork
Assure quality
Dedupe, attention checks, speed/consistency rules, removals with audit trail
Assure quality
Prepare the dataset
Clean data and deliver codebook/variable definitions
Prepare the dataset
Analyse and synthesise
Driver ranking, leakage diagnostics, pricing bands, segment insights
Analyse and synthesise
Deliver and align
Executive deck (optional dashboard) and leadership readout with recommendations
Deliver and align
COMMERCIAL TERMS
Request a Commercial Proposal
Pricing depends on cohort, geography, sample size, approach, LOI, and deliverables. Configure below for an indicative estimate.
Select Sample Size
Geography
Select Mode of Survey
Length of the Interview
$0.00
+ applicable taxes
Cost Breakdown
Note: Estimate is indicative only. Final pricing is subject to scope finalization after discovery call.
REFERENCE CASELETS
Reference
Real-world examples of survey work in the education finance and student lending space.
Student loan channel preference & lender shortlisting behaviour (India)
OBJECTIVE
WHAT WE DID
DELIVERED
Student loan channel preference & lender shortlisting behaviour (India)
Education loan repayment stress & restructuring intent study (India)
Student loan channel preference & lender shortlisting behaviour (India)
OBJECTIVE
A digital-first NBFC needed to map how first-generation college borrowers and repeat postgraduate applicants shortlist lenders, weigh interest rate versus disbursal speed , and decide between public sector banks and private fintech lenders.
WHAT WE DID
Ran a structured quant survey across 6 cities with 480 respondents, capturing lender shortlist composition, channel of first contact, documentation friction points, and co-borrower influence on the final lender selection decision.
DELIVERED
A lender preference map by borrower segment, a ranked friction list across the application journey, and a set of channel levers identifying where digital-first lenders could displace incumbent bank relationships at the shortlisting stage.
FREQUENTLY ASKED QUESTIONS
Common Questions
Answers to frequently asked questions about this survey mandate.
What decisions will this survey enable?
Who is the buyer vs who are the respondents?
Can we see differences between public sector bank borrowers, private bank borrowers and NBFC borrowers?
How will you measure loan selection decisions beyond simple ratings?
Will the survey map the full loan application and repayment journey and drop-offs?
Can this survey inform product and pricing strategy?
How will findings improve our borrower acquisition and retention performance?
Still have questions?
Schedule a discovery call to discuss your specific needs and get a custom quote.