The Indian Digital Credit Market Research report: Support and resolution are different tests

81.4% of sampled support opinions are negative; grievance-resolution opinions are 96% negative in a separate set. Relvo measures reported experience.

ON THIS PAGE

  • 81.4% of sampled customer-support opinions are negative in Relvo’s research.
  • Grievance-resolution opinions are 96% negative within a separate, smaller set.
  • These measures describe sampled opinions, not the share of support tickets that remain unresolved.

Customer-support opinions are negative in 81.4% of their sampled set in Relvo’s digital-credit research (n=371), snapshot dated 2 October 2026. Grievance-resolution opinions are negative in 96% of a separate set (n=99). The figures reflect reported experiences, with critical voices over-represented by the sampling.

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.

Support contact and resolution attract criticism. Customer support: 81.4%; Grievance resolution: 96.0%. Bases: support opinions n=371; grievance-resolution opinions n=99. Source: Relvo research, snapshot 2 October 2026.
Negative share within each separately coded opinion set. Bases: support opinions n=371; grievance-resolution opinions n=99. 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.

Contacting support and having a problem resolved are different stages. A borrower can reach someone and still leave uncertain about a rejection, a charge or an account status. Counting a contact as a successful outcome would miss that distinction.

The India digital credit market research codes support and grievance resolution separately. Their percentages should not be read as a progression from one to the other. The research does not follow a defined set of tickets, establish resolution times or inspect the lender’s internal handling of each case.

For a service team, the accounts provide a starting point for comparing the borrower’s question with the response and final status. Did the reply address the specific issue? Was the explanation consistent with information elsewhere in the product? Was the borrower told what would happen next? Actual case records would be needed to answer those questions.

The evidence includes favourable support experiences as well. The negative share cannot establish that every interaction is poor or that all lenders face the same problem. Relvo’s consumer behavior research helps locate reported frustrations; ticket data and case reviews are needed to measure service performance and test an improvement.

Questions about the research

Is 96% the proportion of complaints left unresolved? No. It is the negative share of sampled grievance-resolution opinions. It is not an audited complaint-resolution rate.

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.

Make sense of what's next.

A clear-eyed digest of AI, products, and ideas worth understanding. Join the NextBigWhat newsletter.

more AI news

Google launches synth-id to identify AI-generated content

Google has introduced a standalone platform called SynthID Detector, designed to help users determine if online content was generated using Google AI or its partner tools. This initiative aims to enhance transparency and trust in digital content, amidst growing concerns about the authenticity of AI-generated materials. The tool reflects Google’s commitment to ethical AI usage and the accountability of content creators.

US halts green card access for major IT firms amid H-1B abuse claims

The US Department of Labor has suspended major tech companies, including Microsoft, Infosys, and Cognizant, from the green card program due to allegations of H-1B visa abuse. This decision impacts several prominent IT firms such as TCS, Wipro, and Capgemini, potentially affecting their ability to recruit foreign talent. The move underscores increasing scrutiny on visa practices within the tech industry.

Amazon cuts ties with Meta’s Muse AI over transparency issues

Amazon has terminated its partnership with Meta’s Muse AI shopping agent, citing concerns over the agent’s credentials and transparency. This decision reflects Amazon’s commitment to safeguarding its customer journey and maintaining control over its retail ecosystem. The move highlights the ongoing scrutiny of AI tools in e-commerce and their impact on customer trust.