Subrata Das, Chief Innovation Officer, U GRO Capital

Subrata leads the Innovation Group at U GRO Capital, where he and his team are part of a fascinating journey towards solving the unsolved needs of the MSME sector – through the use of knowledge and technology. “Social Distancing and avoidance of face-to-face contact in the post-pandemic era is something that is here to stay in the foreseeable future. Hence, the loan on-boarding process is witnessing massive shifts, especially in business loan application by MSMEs,” opines Subrata, who is passionate about applying AI/ML and emerging technology to solve real-world problems. In a conversation with Digital First Magazine, Subrata talks about the application of AI and ML in small business lending, U GRO Capital’s innovative programs and much more.

 

How is the SME financing witnessing an evolution in the analytics utility?

When it comes to the application of Data Science in the banking industry, historically, consumer lending has received a majority of the focus. Use of analytics in SME lending has been next to negligible and even if applied, it mostly is, in a one-size-fits-all manner. This may be due to a lack of readily available data. However, raw data, of which there is no dearth of when used intelligently can unleash immense potential and this holds true for MSME data available in India.

Data-driven decision making is at the core of our business and the organisational culture. We were the first organisation to adopt a sector-specific strategy. We realised that the cashflows of an electrical equipment manufacturer are very different than that of an educational institution or a pharmacy store – which implies that these entities need to be assessed in very different ways. We have solved for this heterogeneity using our proprietary sector-specific statistical scorecards.

Social distancing and avoidance of face-to-face contact in the post-pandemic era is something that is here to stay in the foreseeable future. Hence, the loan onboarding process is witnessing massive shifts, especially in business loan application by MSMEs. While Loan Service Providers have acknowledged the need to digitise the last-mile physical processes, regulatory sponsorship such as KYC, signing of legal agreements, collecting repayment instructions, payments and on-site verifications have enabled the digital transformation. The advent of the Open Credit Enablement Network (OCEN) and Account Aggregator frameworks will democratize credit, and lay emphasis on data-driven models. Further, it will accelerate digital adoption especially among MSMEs who want to benefit from these government-led initiatives.

What is the application of AI and ML in small business lending, including credit assessment process?

There are several areas of application in the customer onboarding process, for example, OCR of documents, signature matching and facial recognition during video KYC. The application of predictive modelling in credit assessment is well known, and it is witnessing rapid evolution in method and approach, as data sources are getting richer. AI/ML is also an investment area, we are building capabilities which will be used in the future. We have hit a few early milestones; investment and IP creation will continue, and these solutions will be productized gradually in the days to come. We will remain in a state of readiness to switch more applications to machine-mode; the timing of the same will depend on the maturity of the models over economic cycles as well as market conditions.

Elaborate on U GRO Capital’s innovative programs, utilizing sectoral expertise and digitalization

From a portfolio assessment perspective – during lockdown period, the Company has estimated the COVID-19 stress on the existing portfolio using a combination of macroeconomic data on sectors, financial data from multiple sources and on-ground impact feedback from direct customer surveys. Insights from these exercises have gone into portfolio management preparations and provision planning.

The best example is our onboarding platform powered by our patent-filed sector-specific scorecards, which produces an in-principle decision in 60 mins; it also includes an OCR engine to read p/l & balance sheet, API integrations for banking/ GST and customer due diligence. During the lockdown, we pivoted to a digital journey and launched our cashflow-assessment based lending product Sanjeevani – incorporating digital agreements and video KYC. Our deep data science capabilities and advanced system architecture make us well-positioned to cater to many new segments with innovative cash flow-based products.

How has U GRO Capital deployed data analytics initiatives towards effective operations?

We have spoken about a few of them. For credit assessment – we have our sectoral scorecards, banking analyser models, banking & GST based cash flow assessment models. We are launching 100 new branches under our Gro Micro program and the location selection exercise was done based on location analytics leveraging Google Places API data. From a portfolio assessment perspective – during the lockdown period, we have estimated the COVID-19 stress on our portfolio using a combination of macroeconomic data on sectors, financial data from multiple sources and on-ground impact feedback from direct customer surveys. Insights from this exercise have gone into portfolio management preparations and provision planning.

We position ourselves in the sweet spot between “fintech” and “fin-touch” – and data capabilities is a key driver of the same. Our expertise is not developed on the back of specialization in terms of product or geography, but we have still created a completely digital delivery mechanism – in the days to come this can help us achieve scale across a wide geographic footprint.

What is the business outlook for U GRO Capital, regarding the product evolution utilizing technology and digital initiatives to reach out to a number of SMEs?

U GRO Capital has, very recently, applied for a patent for its distinguished methods and systems for modelling scorecards. The distinctive underwriting model generates credit scores customized to suit the peculiarities and nuances of varied business enterprises. This is done by analysing the historical loan delinquency patterns and cash flow within each selected business segment. The model’s utility is not restricted to businesses, as it enables effective underwriting of individual borrowers, as well. Further, it facilitates trade financing by providing an assessment of downstream and upstream counterparties. Also, it provides a basis for revenue sharing in co-lending arrangements and helps estimate first loss guarantees in the securitization of transactions by providing an assessment of the underlying pool.

As a listed entity, the Company does not make futuristic projection but has been using this model since its inception in 2018 and had made disbursals of INR 1,700 Cr in the form of secured and unsecured loans.

Going forward, the company aims to target 250,000 MSMEs in the coming 4 financial years.

More About Subrata Das

A seasoned banking professional, Subrata’s career experience across MNC banks and Indian NBFC sector covers a diverse spectrum of customer segments and their financial needs – through products such as credit cards, personal loans, affordable housing, mortgages/ LAP, CASA, gold loans, commercial vehicle, SME loans and supply chain finance. He has worked extensively in the areas of product development, customer activation, pricing, cross-sell, risk decision frameworks, stress testing, loss forecasting.

He is rigorously trained in applied statistics and predictive modelling with extensive experience in development, deployment, and governance of risk/ marketing models across India and South Asian markets.

At U GRO Capital, Subrata and his team are focusing on creating holistic data-driven product frameworks which would be deployed through a seamless digital journey. A few months earlier, U GRO Capital filed for a patent for their suite of sector-specific statistical scorecards; several exciting new products are in the making.

Subrata is an alumnus of Indian Statistical Institute, Kolkata and is based out of Mumbai.

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