12-05-2022 02:22 PM | Source: PR Agency
Jocata announces pan-India launch of AI/ML based score SME DNA to power banks and NBFCs to scale priority sector lending
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Mumbai: On the occasion of International Day of Banks, celebrated globally by the banking fraternity on December 4, B2B lending and compliance fintechJocataannounced panIndia roll out of SME DNAscore, a proprietary AI/ML based risk and business intelligence score – after having successfully beta testedthe model on the GSTN filings of over 20,000 MSMEs with two of the top Indian private lenders and one of the largest development banks in the country

Jocata’sSME DNA score comes at a time when there is a growing demand for GST-based analytics. A strong regulatory push, growing GST filing compliance and the recent announcement of GSTN as a Financial Information Provider (FIP) under the Account Aggregator framework is expected to ease access to large volumes of consent-based GST data and grow the analytics outcomes.

The SME DNA score will aid underwriters with enhanced'Go-No-Go' decision within 2 minutes, thereby fast-tracking priority sector lending for banks and financial institutions. With predictive insights, the SME DNA score will also spur credit innovation for banks in the form ofcontextual and targeted lending solutions aimed at the MSME segment, including embedded lending, GST bridge loans, sachet loans, BNPL, and cash-flow based loans, among others.

During its beta stage, the SME DNA scoreaidedone of the top 5 private banks in India to build a business model in the small ticket segment of unsecured business loans in the range of Rs.2 lakh to 20 lakh, and also secured overdraft of up to Rs.2 crores digitally from the ground up.

GSTN filings are considered a goldmine of authentic, reliable, digitally available, dynamic data.By leveraging cutting edge data science techniques on GSTN filings, SME DNA can empower underwriters with more transparent insights throughout the business cycle of credit seekers and reduce the Time-to-Credit (disbursal) for MSME borrowers from 2-5 days to less than 6 hours.

Jocata Managing Director and CEO Prashant Muddu said, " The outlook for GST-based analytics is very promising and it can significantly reduce the current problems that bankers face in credit decisioning for the priority sector that stem from a heavy reliance on expert judgement leading to longer decisioning times. In addition to spurring credit innovation and in scaling up the priority sector lending for banks, the SME DNA score can kick-start a virtuous cycle by also empowering MSMEs to improve their business performance and get access to credit, build credit history, avail loans on more favourable terms, to unlock their potential in India's growth story."

Jocata’sdata sciences team has analyzed MSMEs' filing data from GSTN since its adventto develop the score that represents the risk of the MSME business. The score assesses the entityfor its propensity to pay tax, checks the health of and (over)dependence on theMSMEs' buyers and suppliers,among other risk factors. It also helpsbanks’underwriters and business teamsin improving credit decisioning and monitoring, besides identifyingearly warning signals at entity and portfolio level,which is especially important at a time when banks and financial institutions are facing pressures due to Non-Performing Assets (NPAs). This is key to easing the trust deficit financial institutions face in lending to MSMEs and giving transparency and information throughout the business cycle."

Jocata has been working with some of the largest financial institutions to power their digital transformation journey across a suite of fintech solutions including digital onboarding, risk scoring and assessment, credit underwriting, fraud prevention, API infrastructure and management, early warning systems among others. Some of the key banking partners include ICICI Bank, Axis Bank, Bank of Baroda, IndusInd Bank, Kotak Mahindra Bank, RBL Bank, Federal Bank, Standard Chartered, DBS Bank, Tata Capital, Airtel Payments Bankand American Express.

 

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