Data Analysis

Why GST Data Stack is a One Stop Solution to SME's Credit Problem

Struggling to get loans in order to expand your company's wings and charter into newer territories? Maybe, your sales invoice is the solution.
Why GST Data Stack is a One Stop Solution to SME's Credit Problem
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Entrepreneur Staff
Senior Correspondent, Entrepreneur India
5 min read

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When the Central Government introduced the much-awaited Good and Services Tax (GST) in 2017 to the Indian economy, there were many concerns related to crossover from the existing tax regime.

However, this new tax reform would probably help the country organize its small and medium enterprises sector, which contributes almost 30-35 per cent to India’s GDP. To what degree the move succeeded is debatable as a great many experts are of the opinion that the GST would take considerable time to show positive results. However, in the era of analytics, what GST did is more applaudable – it has created a huge amount of financial data of companies.

Earlier this year, while announcing the annual budget 2018-19, finance minister Arun Jaitley also shared that the Trade Receivables Discounting System (TReDS) platform could access the central GSTIN date.

The platforms such as A.Treds, Receivables Exchange of India Ltd (RXIL) and M1 TReDs, that connect the SMEs to factors to discount their invoices can now use the GSTIN stack to verify the authenticity of the bills raised. The larger picture here what if the access to this data is extended to fintech platform that is trying to solve $60 billion SME credit gap in the domestic market?

Issues With the SME Financing

Almost 10 per cent of 55 million SMEs in India have access to formal credit. One of the key issues, when it comes to SME financing is that the sector is heavily informal and hence, there is very little or no data available.

Shachindra Nath, executive chairman and managing director of Ugro Capital says these SMEs operate in sectors and sub-sectors with unique business models and therefore, there exists unfamiliar cash-flows. This lends itself to heterogeneity, making credit appraisal more difficult. “In addition to the difficulty in credit appraisal, the high cost of origination and later servicing of these customers has resulted in these segments being relatively unbanked,” he shares.

To top it all, the past 2-3 years have been amongst the most tumultuous years for the Indian businesses, especially the MSME basket. Manish Lunia, co-founder, Flexiloans says, “Demonetization broke the back of the cash transacting MSMEs with a heavy disruption in business proceedings and the GST implementation was the nail in the coffin. These two mega-events, in consequence, led to a heavy credit crunch in the market with people holding back business amidst elongated working capital cycles. If this was not enough, PSU banks that were the saving factor for smaller SMEs faced the PCA ban and with the NPA mess around, they virtually stopped lending.”

On the other side, working capital demanded by MSMEs is roughly about Rs 26 lakh crore of which Rs 15 lakh crore is estimated supply fulfilled by banks and factoring companies. This gap is creating a host of opportunities for both new and traditional companies to play along.

GSTIN Data – a Bane?

While crossing over to GST was a nightmare for SMEs, the financial data which was generated over the past 15 months is tremendous and can be used in multiple ways to solve the credit problem of the industry.

Kalyan Basu is the CEO-MD of A.Treds. He feels one of the biggest issues GST will solve is the assessment of the credit history of the MSME. “Being the most credible data on the supply chain of the MSME, combining it with the e-way bill will ensure that there will be an absolute precision,” he says. While on the other side, fintech companies can use this data to create a customized product and offer better rates as per the borrower’s need. This, in turn, also lowers the servicing cost for the lender.

Also, Alok Mittal, CEO and co-founder, Indifi Technologies and president, DLAI data thinks that this data can be used for real-time credit scoring of borrowers. “By building a relevant statistical model and applying it to a fresh loan application or an existing account, fintech platforms can gain near-instant insight into the overall credit behaviour of the applicant,” he points out while sharing that, “The differentiation that data drives for fintech players is one of the major reasons why their loan default rates are significantly lower than those of traditional BFSI companies.”

Data Security

With the growing influence of analytics, data security of both personal and companies’ stack is a major concern globally. And one cannot stop stressing on how important is consent here. “From a lender perspective, two aspects are very important. First of all, it’s important to ensure that the customer not only gives an approval but is also completely aware of how data is being used. Secondly, it’s critical to ensure that the data collected is stored safely,” Nath adds. He doesn’t cancel out the chances of misuse of data but the overall benefit outweighs this and hence, the Personal Data Protection Bill is a step in that direction.

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