KOCHI:
Continuing their mission of supporting banks and financial institutions to sustainably grow their MSME credit portfolios while driving access to finance for underserved and unserved MSMEs, TransUnion CIBIL, in collaboration with Online PSB Loans Limited (OPL), under the mentorship of SIDBI, today launched FIT Rank – a comprehensive ranking model for MSMEs.
FIT Rank leverages the power of Goods and Services Tax (GST), Bank Statements, and Income Tax returns (ITR) information to provide a ranking model for MSME lending. This ranking model uses machine learning algorithms to predict the probability of an MSME becoming a non-performing asset (NPA) in the next 12 months. FIT Rank provides a ranking for the MSME, based on its financial, income, and trade data on a scale of 1 to 10, FIT Rank 1 being for the least risky MSME and FIT Rank 10 being for the most at-risk MSME. Each FIT rank corresponds to a Probability of Default (PD) (see Figure 2: FIT Rank corresponding PD). The lower the FIT Rank, the lower the perceived risk of default associated with the MSME. This is the first time TransUnion CIBIL in collaboration with OPL has developed a credit default predictor model based on financial, income and trade data which has been made possible due to the improved digitization in the credit industry.
FIT RANK triangulates information from multiple sources to provide a unified view of financial, income and trade data for an MSME, enabling improved risk differentiation and sharpened credit underwriting for MSME loans. In the last financial year (FY 2021-22), 27 lakh MSME’s availed credit, out of which 11.6 lakh MSMEs were new-to-credit. By incorporating GST, Bank statements and Income Tax return data, the model enables intensive risk differentiation of more than three times on the 11.6 lakh new-to-credit MSMEs. Of the remaining 15.4 lakh MSMEs with an existing credit footprint, more than 9 lakh MSMEs (58%) fall into the medium-risk segment (CMR-4 to CMR-6) through the CIBIL MSME Rank (CMR) model. The FIT Rank enables more than five times risk differentiation in this medium-risk segment by ranking MSMEs based on their GST, Banking and ITR data. With banks and credit institutions being able to assess credit risk using this comprehensive ranking model, they can confidently lend and provide financial assistance to many more MSMEs (see Figure 1: Mapping India’s MSME sector through the FIT Rank Lens).
Commenting on the utility of FIT RANK, the Chairman and Managing Director of SIDBI, Sivasubramanian Ramann, expressed: “Insights show that only about one-third of MSMEs in India are served through the formal credit ecosystem, indicating significant opportunities for increasing credit penetration in this key sector. Credit flow to MSME entities can be further expanded and also made more efficient by widening the risk underwriting parameters of MSMEs based on multiple data sources available in the marketplace. FIT Rank will benefit MSMEs with a satisfactory track record of GST payments, banking behavior and Income Tax Returns to be able to become more credit eligible. He also mentioned that appreciating the power of FIT to enhance credit underwriting, SIDBI has launched a new Express loan Product for MSMEs to provide them loans up to INR 50 lakh for purchase of machinery and roof top solar through straight through processes. ”
Insights from TransUnion CIBIL’s latest analysis show that INR 7.3 lakh crore of credit has been disbursed to the MSME sector by banks and financial institutions in FY 2022. With the implementation of FIT Rank, banks and financial institutions will be able to assess the profiles of many more MSMEs and can drive incremental credit growth for India’s MSME sector by having access to even better means of assessing risk.
Speaking at the launch of FIT Rank, the MD & CEO of TransUnion CIBIL, Rajesh Kumar, said: “MSMEs form the backbone of India’s economic engine and are the catalysts of sustainable economic growth. In order to strengthen pathways to achieving the goal of making India a USD five trillion economy, it is vital to drive access to financial opportunities for many more deserving MSMEs across the country’s geography. The lack of a comprehensive and one-stop source of information on MSMEs is one of the key roadblocks to credit growth in the sector. FIT Rank aims to bridge this information asymmetry by leveraging the existing information infrastructure of GST, Banking and Income Tax data to provide a triangulated view of financial, income, and trade related transactions. Using this modular rank along with our flagship CIBIL MSME Rank (CMR), banks and credit institutions will be able to objectively and quickly assess and drive access to credit for a significantly larger number of MSMEs across India’s geography.”
Adding to this, Jinand Shah, the Managing Director of Online PSB Loans, said: “OPL is committed to helping credit institutions expand their credit portfolios while delivering quick, seamless, and digital access to finance for the MSME sector. FIT Rank brings the power of best-in-class credit information analytics by TransUnion CIBIL combined with OPL’s expertise and experience in delivering smart, interactive, simple, and innovative end-to-end financial solutions. We believe that FIT Rank will be able to help India’s credit industry in significantly scaling portfolio growth while also supporting the government’s Atmanirbhar Bharat initiative by increasing access to finance for MSMEs”
Insights from TransUnion CIBIL show that more than 90 lakh MSMEs exhibit CIBIL MSME Rank in the range of 1-6, indicating a substantial number of deserving MSMEs which fall in the stable credit risk segment and can be extended credit opportunities for growing their businesses. This includes a growing population of new-to-credit MSMEs. By implementing FIT Rank based lending policies and processes, India’s credit industry can scale sustainable portfolio growth, drive digital transformation, and enable incremental credit growth for the MSME sector.
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