The Indian Digital Credit Market Research report: The explanation gap after a loan refusal

79.9% of recorded lender-refusal accounts give no reason in Relvo’s research. That is an evidence gap, not proof of what every lender communicated.

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  • 79.9% of recorded lender-refusal accounts contain no reason in Relvo’s digital-credit research.
  • Eligibility or credit-score reasons account for 12% of the same recorded events.
  • The accounts do not establish what information every lender actually provided.

No reason is recorded in 79.9% of lender-refusal events in Relvo’s digital-credit research (n=626), in the snapshot dated 2 October 2026. Eligibility or credit-score reasons account for 12%. The finding describes the borrower accounts available to the research, rather than an audit of lenders’ decision notices.

How to read the numbers: Shares describe sampled accounts or opinions, with their bases shown. Reviews were sampled across star ratings, which over-represents critical voices. Separate evidence sets can come from the same accounts. Small bases are indicative; bases below 10 are reported directionally.

What rejection accounts explain. No reason recorded: 79.9%; Eligibility or credit-score reason: 12.0%; Other coded reasons: 8.1%. Base: recorded lender-refusal events (n=626). Source: Relvo research, snapshot 2 October 2026.
Share of recorded lender-refusal events. Base: recorded lender-refusal events (n=626). Source: Relvo research, snapshot 2 October 2026. Reviews sampled across star ratings; critical voices over-represented. Not loan transaction data and not a representative survey.

A refusal leaves two questions: what happened to this application, and what should the applicant understand about any future application? A message that closes the first question may leave the second open. The evidence cannot establish whether the borrower received an explanation elsewhere, overlooked it or was never given one.

For the India digital credit market research, that boundary matters. Missing detail in an account should prompt examination of the communication, rather than an assumption that a lender failed to communicate. The explanation gap is still commercially relevant because this is how borrowers describe the experience afterwards.

A useful product review would compare the actual decision message, the information available in the account and subsequent support contacts. Does the applicant understand the outcome? Do different screens describe the same status? Does support have enough information to answer the question consistently? These are proposed checks, not demonstrated ways to improve approval or retention.

Relvo’s consumer behavior evidence separates reported refusals from recorded reasons. It does not supply lender underwriting data, application-level approval rates or a conclusion about why a particular person was declined. Those require additional evidence.

Questions about the research

Does 79.9% mean lenders never explain their refusals? No. It means the sampled borrower accounts contain no coded reason. The research does not independently inspect every communication between lender and applicant.

Is this based on lender transaction data? No. It uses coded borrower accounts and opinions. It is not loan transaction data and not a representative survey.

Related research: The India Digital Credit Market Report, 2026 on NBW Brain examines borrower decisions, experiences and behavioural patterns, with evidence available through its Market Brain.

Methodology

Source: Relvo digital-credit research, snapshot dated 2 October 2026. Borrower accounts and opinions are coded to a fixed codebook with evidence and coding checks. Accounts span October 2025–October 2026. Reviews were sampled across star ratings; critical voices are over-represented. Each share refers to the event, profile or opinion set named alongside it. A profile is a coded account, not a verified unique borrower or credit file. Opinion and action layers may overlap. Bases of 10–29 are indicative; bases below 10 are reported directionally. Findings do not establish population prevalence, loan approval rates, legal breaches or causal effects.

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