SME LENDING & FINANCE

Bank vs NBFC Preference Survey (SMEs)

Small and medium enterprises weigh interest rates, approval timelines, and relationship flexibility when choosing between banks and NBFCs for credit, so you can sharpen acquisition targeting, recalibrate pricing tiers, and reduce borrower attrition.

Pan-India sample
SME finance decision-makers (Founders & CFOs)
15-20 min
Talk to a Survey Consultant
Lender evaluation friction & drop-offsIdentify where SME borrowers stall, switch lenders, or abandon credit applications mid-process.
Selection drivers & pricing trade-offsRank the approval speed thresholds, collateral expectations, and rate sensitivities that determine lender choice.
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CONTEXT & RELEVANCE

Why run this survey now

Most lenders don't lose SMEs purely on interest rates. They lose them due to slow disbursals, opaque fee structures, collateral rigidity, relationship gaps, and poor renewal experiences, none of which fully show up in branch MIS or portfolio dashboards.

If you are...

  • Bank SME lending head
  • NBFC product or credit leader
  • Distribution or channel head
  • Fintech SME growth team
  • Strategy lead, retail lending

You're likely facing...

  • SME fit confusion: bank vs NBFC
  • Drop-offs at documentation stage
  • Banks perceived stable but slow
  • NBFCs perceived fast but expensive
  • Renewal switching over service gaps

This will help answer...

  • Preference drivers beyond rate
  • Funnel drop-off stage mapping
  • Segment splits by lender type
  • Fee and tenure tolerance bands
  • Renewal and switch triggers

RESEARCH THEMES

What This Survey Investigates

Eight interconnected research themes that map the complete SME borrowing journey from first lender discovery to long-term institutional loyalty.

TENETS 01

Discovery & Awareness

  • First lender contact channels
  • Referral vs direct outreach triggers
TENETS 02

Preference Drivers

  • Bank vs NBFC selection criteria
  • Speed, collateral, relationship weight
TENETS 03

Product & Structuring

  • Facility type, tenure, collateral mix
  • Cash credit vs term loan preference
TENETS 04

Journey Friction

  • Drop-offs across application stages
  • Documentation, verification delays
TENETS 05

Pricing & WTP

  • Rate sensitivity by facility type
  • Fee transparency, hidden charge perception
TENETS 06

Servicing & Stickiness

  • RM responsiveness, digital self-service
  • Renewal, top-up conversion triggers
TENETS 07

Trust & Credibility

  • Institutional trust, regulatory comfort
  • Data privacy, grievance resolution
TENETS 08

Competitive Positioning

  • Multi-lender usage, wallet share split
  • Switching intent by lender category

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.

Sample size
How many respondents do you need?
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Target audience
Who should we survey?
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Region
Which regions should we cover?
Not Selected
Segments
How should we slice the data?
Not Selected
Discuss sample plan

METHODOLOGY

Survey approach

For the Bank vs NBFC Preference Survey (SMEs), we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification.

PRIMARY
Online web surveySelf-administered survey shared via email / panels to capture structured responses at scale.
Best for
1
Measuring bank vs NBFC preference and usage
2
Ranking lending decision drivers by SME segment
3
Comparing satisfaction across size, industry, region
Deliverables
Driver ranking
Gap matrix
Pricing bands
OPTIONAL
CATI (phone survey)Interviewer-led telephone interviews to reach owners who are harder to get online.
Best for
1
Micro and small SME owners with low digital comfort
2
Quick pulse across multiple towns and clusters
Deliverables
Representative SME coverage
Call-log diagnostics
SELECTIVE
Face-to-faceOn-ground surveys or interviews in key industrial clusters or high-value cohorts.
Best for
1
Larger-ticket borrowers needing in-person verification
2
Contextual mapping of local lending ecosystems
Deliverables
Cluster insights
Rich journey maps
OPTIONAL
FGDs
Deliverables
Themes and quotes
Concept feedback
OPTIONAL
Mixed surveysAny 4-mode combo Online + CATI + F2F + FGDs to maximise reach and representation. Mode-specific quotas and weighting for clean comparisons.
Deliverables
Unified dataset
Mode-adjusted analytics
Our Recommendation
Start with: Online web survey as the core quant instrument, supported by CATI to capture micro and small SME owners in low-digital segments.
Consider adding: Face-to-face interviews in strategic industrial clusters and a focused FGD layer to pressure-test messaging and proposition concepts.

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

Step 01

Define the decision frame

Design the instrument

Build workstream modules mapped to outputs (drivers, friction, pricing, retention, trust)

Step 02

Design the instrument

Lock the questionnaire

Review wording, sequencing, LOI, and competitive context; approve final version

Step 03

Lock the questionnaire

Pilot and calibrate

Test comprehension and ease quality; refine quotas and remove friction where needed

Step 04

Pilot and calibrate

Run fieldwork

Execute collection with active quota management and feasibility controls

Step 05

Run fieldwork

Assure quality

Dedupe, attention checks, speed/consistency rules, removals with audit trail

Step 06

Assure quality

Prepare the dataset

Clean data and deliver codebook/variable definitions

Step 07

Prepare the dataset

Analyse and synthesise

Driver ranking, leakage diagnostics, pricing bands, segment insights

Step 08

Analyse and synthesise

Deliver and align

Executive deck (optional dashboard) and leadership readout with recommendations

Step 09

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

100

Geography

  • India
  • APAC (Singapore, Vietnam, Philippines, Indonesia, Australia, NZ, Japan, Thailand)
  • Middle East (UAE, KSA, Qatar, Bahrain, Oman, Kuwait)
  • North America (US, Canada)
  • Europe
  • Africa (South Africa, Kenya, Nigeria, Egypt, Algeria)
  • LATAM (Brazil, Mexico)

Select Mode of Survey

  • Online
  • CATI
  • Online FGD (5 people per FGD)
  • F2F

Length of the Interview

  • Select
  • 0-15
  • 16-20
  • 21-30
  • 31-45
  • 46-60
  • Custom
Indicative Estimate
  • Indian Rupee (INR)
  • United Arab Emirates Dirham (AED)
  • Afghan Afghani (AFN)
  • Albanian Lek (ALL)
  • Armenian Dram (AMD)
  • Netherlands Antillean Guilder (ANG)
  • Angolan Kwanza (AOA)
  • Argentine Peso (ARS)
  • Australian Dollar (AUD)
  • Aruban Florin (AWG)
  • Azerbaijani Manat (AZN)
  • Bosnia-Herzegovina Convertible Mark (BAM)
  • Barbadian Dollar (BBD)
  • Bangladeshi Taka (BDT)
  • Bulgarian Lev (BGN)
  • Bahraini Dinar (BHD)
  • Burundian Franc (BIF)
  • Bermudian Dollar (BMD)
  • Brunei Dollar (BND)
  • Bolivian Boliviano (BOB)
  • Brazilian Real (BRL)
  • Bahamian Dollar (BSD)
  • Bhutanese Ngultrum (BTN)
  • Botswana Pula (BWP)
  • Belarusian Ruble (BYN)
  • Belize Dollar (BZD)
  • Canadian Dollar (CAD)
  • Congolese Franc (CDF)
  • Swiss Franc (CHF)
  • Chilean Peso (CLP)
  • Chinese Yuan (CNY)
  • Colombian Peso (COP)
  • Costa Rican Colón (CRC)
  • Cuban Peso (CUP)
  • Cape Verdean Escudo (CVE)
  • Czech Koruna (CZK)
  • Djiboutian Franc (DJF)
  • Danish Krone (DKK)
  • Dominican Peso (DOP)
  • Algerian Dinar (DZD)
  • Egyptian Pound (EGP)
  • Eritrean Nakfa (ERN)
  • Ethiopian Birr (ETB)
  • Euro (EUR)
  • Fijian Dollar (FJD)
  • Falkland Islands Pound (FKP)
  • British Pound (GBP)
  • Georgian Lari (GEL)
  • Ghanaian Cedi (GHS)
  • Gibraltar Pound (GIP)
  • Gambian Dalasi (GMD)
  • Guinean Franc (GNF)
  • Guatemalan Quetzal (GTQ)
  • Guyanese Dollar (GYD)
  • Hong Kong Dollar (HKD)
  • Honduran Lempira (HNL)
  • Croatian Kuna (HRK)
  • Haitian Gourde (HTG)
  • Hungarian Forint (HUF)
  • Indonesian Rupiah (IDR)
  • Israeli New Shekel (ILS)
  • Iraqi Dinar (IQD)
  • Iranian Rial (IRR)
  • Icelandic Króna (ISK)
  • Jamaican Dollar (JMD)
  • Jordanian Dinar (JOD)
  • Japanese Yen (JPY)
  • Kenyan Shilling (KES)
  • Kyrgyzstani Som (KGS)
  • Cambodian Riel (KHR)
  • Comorian Franc (KMF)
  • South Korean Won (KRW)
  • Kuwaiti Dinar (KWD)
  • Cayman Islands Dollar (KYD)
  • Kazakhstani Tenge (KZT)
  • Lao Kip (LAK)
  • Lebanese Pound (LBP)
  • Sri Lankan Rupee (LKR)
  • Liberian Dollar (LRD)
  • Lesotho Loti (LSL)
  • Libyan Dinar (LYD)
  • Moroccan Dirham (MAD)
  • Moldovan Leu (MDL)
  • Malagasy Ariary (MGA)
  • Macedonian Denar (MKD)
  • Burmese Kyat (MMK)
  • Mongolian Tögrög (MNT)
  • Macanese Pataca (MOP)
  • Mauritian Rupee (MUR)
  • Maldivian Rufiyaa (MVR)
  • Malawian Kwacha (MWK)
  • Mexican Peso (MXN)
  • Malaysian Ringgit (MYR)
  • Mozambican Metical (MZN)
  • Namibian Dollar (NAD)
  • Nigerian Naira (NGN)
  • Nicaraguan Córdoba (NIO)
  • Norwegian Krone (NOK)
  • Nepalese Rupee (NPR)
  • New Zealand Dollar (NZD)
  • Omani Rial (OMR)
  • Panamanian Balboa (PAB)
  • Peruvian Sol (PEN)
  • Papua New Guinean Kina (PGK)
  • Philippine Peso (PHP)
  • Pakistani Rupee (PKR)
  • Polish Złoty (PLN)
  • Paraguayan Guaraní (PYG)
  • Qatari Riyal (QAR)
  • Romanian Leu (RON)
  • Serbian Dinar (RSD)
  • Russian Ruble (RUB)
  • Rwandan Franc (RWF)
  • Saudi Riyal (SAR)
  • Solomon Islands Dollar (SBD)
  • Seychellois Rupee (SCR)
  • Sudanese Pound (SDG)
  • Swedish Krona (SEK)
  • Singapore Dollar (SGD)
  • Saint Helena Pound (SHP)
  • Sierra Leonean Leone (SLL)
  • Somali Shilling (SOS)
  • Surinamese Dollar (SRD)
  • São Tomé and Príncipe Dobra (STD)
  • Syrian Pound (SYP)
  • Swazi Lilangeni (SZL)
  • Thai Baht (THB)
  • Tajikistani Somoni (TJS)
  • Turkmenistani Manat (TMT)
  • Tunisian Dinar (TND)
  • Tongan Paʻanga (TOP)
  • Turkish Lira (TRY)
  • Trinidad and Tobago Dollar (TTD)
  • New Taiwan Dollar (TWD)
  • Tanzanian Shilling (TZS)
  • Ukrainian Hryvnia (UAH)
  • Ugandan Shilling (UGX)
  • United States Dollar (USD)
  • Uruguayan Peso (UYU)
  • Uzbekistani Som (UZS)
  • Vietnamese Đồng (VND)
  • Vanuatu Vatu (VUV)
  • Samoan Tālā (WST)
  • Central African CFA Franc (XAF)
  • East Caribbean Dollar (XCD)
  • West African CFA franc (XOF)
  • CFP Franc (XPF)
  • Yemeni Rial (YER)
  • South African Rand (ZAR)
  • Zambian Kwacha (ZMW)
  • Zimbabwean Dollar (ZWL)

$0.00

+ applicable taxes

Proposal turnaround typically 24–48 hours

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 SME lending and financial services space.

CASELET 1

MSME Working Capital Channel Preferences & Friction Mapping (India)

CASELET 2

SME Trade Finance Product Gaps & Pricing Sensitivity (Western India)

MSME Working Capital Channel Preferences & Friction Mapping (India)

OBJECTIVE

Quantify how micro and small manufacturers select between digital lending platforms and traditional branch-based lenders for working capital, isolating the role of turnaround speed, collateral requirements, and relationship trust in shaping channel stickiness and switching triggers.

WHAT WE DID

Fielded a structured quant survey across 6 cities with 480 MSME owners, capturing channel discovery path, application completion rates, documentation burden, disbursement timelines, and satisfaction scores segmented by loan ticket size and vintage of borrowing.

DELIVERED

Channel preference corridor by MSME size tier, a ranked friction list per lending channel , a switching trigger framework identifying 5 displacement moments, and segment-level message territories for digital-first acquisition campaigns targeting first-time borrowers.
CASELET 1

MSME Working Capital Channel Preferences & Friction Mapping (India)

CASELET 2

SME Trade Finance Product Gaps & Pricing Sensitivity (Western India)

MSME Working Capital Channel Preferences & Friction Mapping (India)

OBJECTIVE

Quantify how micro and small manufacturers select between digital lending platforms and traditional branch-based lenders for working capital, isolating the role of turnaround speed, collateral requirements, and relationship trust in shaping channel stickiness and switching triggers.

WHAT WE DID

Fielded a structured quant survey across 6 cities with 480 MSME owners, capturing channel discovery path, application completion rates, documentation burden, disbursement timelines, and satisfaction scores segmented by loan ticket size and vintage of borrowing.

DELIVERED

Channel preference corridor by MSME size tier, a ranked friction list per lending channel , a switching trigger framework identifying 5 displacement moments, and segment-level message territories for digital-first acquisition campaigns targeting first-time borrowers.

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 bank-only, NBFC-only and mixed borrowers?

How will you measure lender preference beyond simple ratings?

Will the survey map the full credit journey and drop-offs?

Can this survey inform product and pricing strategy?

How will findings improve our sales and marketing messaging?

Still have questions?

Schedule a discovery call to discuss your specific needs and get a custom quote.

Book a Discovery Call