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Big Data and Analytics Easing the Process of Providing Capital to SMEs

We Spoke to Harshavardhan Lunia, Co-founder and CEO, Lendinkart about the challenges in providing capital to India SMEs, technologies involved and how they can mitigate financial challenges in future

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Nijhum Rudra
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Big Data and Analytics Easing

We Spoke to Harshvardhan Lunia, Co-founder and CEO, Lendingkart about the challenges in providing capital to India SMEs, technologies involved and how they can mitigate financial challenges in future

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Lendingkart is a fin-tech startup in the working capital space. The company has developed technology tools based on big data analysis which facilitates lenders to evaluate borrower’s credit worthiness and provides other related services. The organization aims to make working capital finance available at the fingertips of entrepreneurs, so that they can focus on business instead of worrying about the gaps in their cash-flows.

Challenges faced

“In providing capital to the Indian SMEs in rural areas the biggest challenges are inaccurate and outdated hardware access, illiteracy in the rural areas and huge lack of internet penetration, said Lunia.” Keeping above challenges in mind, Lendingkart is working with government towards solutions that will help them overcome these concerns. In rural areas where literacy rate is low, Lendingkart has already introduced application forms in Hindi and other languages with help from the government. This will make it easier for SMEs to comprehend and apply. Additionally, the rural areas must come up with mobiles apps that do not consume too much internet data, therefore, making it easier for them to download and fill forms even at low internet bandwidth. “Our forms are designed in a way that they can be filled offline as well. To tackle the hardware issue, we now also have presence in mobile phones. This reduces the dependability on desktops and SMEs can apply for a loan, on the move,” added Lunia.

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Lendingkart's Business Model in Providing Capital

“Our usual process requires applicants to visit www.lendingkart.com to apply for the loan. They then need to give background information and upload requisite documents,” said Lunia. Those documents are then handed over to their NBFC that verifies and transfers them to its analytics team to determine the intent of applicants to repay the loan amount. The entire process is integrated with technology and the NBFC disburses loan within 72 hours from the time of application. This helps SMEs avoid the cumbersome paperwork that is usually associated with taking loans.

The Role of Big Data and Analytics in

Providing Capital

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Lendingkart Group enables SMEs to apply for loans on basis of only an online application. “Our NBFC has algorithms and use their proprietary knowledge to do credit scoring.

“Our NBFC assesses the credit worthiness for ecommerce vendor/market place sellers based on their online foot print,” added Lunia. Without any collateral and physical offices, the digital lending platform provides short-term working capital loans of INR 50,000 to INR 10 Lakhs based on an online form filled by the borrower in a short span of 15 minutes. Since its inception, the organization has been able to assess SMEs in more than 135 cities across 22 states in India.

Enough data is available to determine a customer’s intent to pay back a loan, quality of his product/service, financial health of his business, and ability to survive with competition etc. “We don’t ask customers to ‘fill large forms’. In a country like India where thin file problem amongst borrowers exists at a vast level, big data and analytics help lenders in reaching out to the underserved MSMEs,” concluded Lunia.

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Harshavardhan-Lunia Harshvardhan Lunia Co-founder and CEO, Lendinkart

Harshvardhan Lunia

Harshvardhan Lunia

“Lendingkart Group enables SMEs to apply for loans on basis of only an online application. Their NBFC has algorithms and it also uses proprietary knowledge to do credit scoring. Those algorithms use 2200 raw data points to generate a lending decision almost instantaneously resulting in loan approval within 72 hours from the time of application.”

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