In a major boost to credit accessibility for Micro, Small, and Medium Enterprises (MSMEs), Union Finance Minister Nirmala Sitharaman and Minister of State for Finance Pankaj Chaudhary launched a New Digital Credit Assessment Model during a post-budget interaction in Vishakhapatnam.
This initiative was first hinted at during the Union Budget 2024-25, and is designed to modernize the credit evaluation process by leveraging digital footprints instead of relying on traditional asset-based or turnover-based assessments.
The new model shifts away from external credit assessments and empowers Public Sector Banks ( PSBs ) develop their in-house digital credit scoring mechanisms. By analyzing real-time digital transactions and financial behavior, this system ensures a more transparent, efficient, and data-driven loan approval process for MSME borrowers that are Existing to Bank (ETB) and New to Bank (NTB).
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The credit assessment model incorporates various digital verification mechanisms to automate loan processing including PAN and name authentication via the National Securities Depository Limited (NSDL), mobile and email verification through OTP, API-based GST data fetching, bank statement analysis using account aggregators, and ITR verification.
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Additionally, the new mechanism shall integrate commercial and consumer credit bureau checks, fraud detection systems, and Hunter database scans to ensure robust due diligence before granting loans.
The changes are in line with the continued approach to digitize the governmental processes in India and eliminates the need for physical paperwork and branch visits, allowing entrepreneurs to submit loan requests from anywhere.
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Moreover, the model ensures instant in-principle loan sanctions, reduced turnaround time (TAT), and an end-to-end Straight Through Process (STP), significantly improving loan disbursal speed. MSMEs covered under the Credit Guarantee Fund Trust for Micro and Small Enterprises (CGTMSE) scheme will also benefit from collateral-free loans, further simplifying access to credit.
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