The B2B fintech platform helps lenders make critical decisions based on credit scores assigned to new-to-credit and thin-file customers through data.
As India charges ahead to become a digital economy, Abhishek Agarwal, Co-founder and CEO, CreditVidya, believes there is going to be a huge spike in demand for product and services for fraud and credit risk assessment of individuals.
The B2B fintech platform today raised its series B funding of $5 million. Launched in 2013, this is CreditVidya’s second round of funding. It was led by Matrix Partners. Existing investor Kalaari Capital also participated in the funding. Between last year and this year, the total amount of funding raised by the company stands at $11 million.
CreditVidya works with different lenders – banks, NBFCs and insurance companies.
“However, recently there are demands from e-commerce and wallet companies, which are looking at our product for credit risk for their new customers,” explains Abhishek.
The company will use the funding to add a wide range of fraud and verification services to its existing big data underwriting platform. The funds will also be used to further improve AI-based algorithms that use more than 10,000 data points for risk assessment.
CreditVidya claims to have partnered with more than 20 leading lending institutions to apply big data analysis for credit underwriting, so that they can assess the risk of first-time borrowers more accurately.
According to Bala Srinivasa, Partner, Kalaari Capital, CreditVidya has grown remarkably since the last round of funding. He adds that as lenders aggressively expand their retail credit portfolios, it becomes important that these lenders focus on reducing turnaround time, cost of customer acquisition and also not compromise on the portfolio risk.
With the digital footprint in India increasing, it becomes easier for companies like CreditVidya to mine digital data and ensure that deserving individuals get funded. “These were otherwise not covered in the traditional model,” informs Abhishek.
CreditVidya also offers ‘decision-as-a-service’ with seamless integration into existing client systems. It has assessed more than five million potential borrowers to date and the platform now processes more than 200 gigabytes of unstructured data per day on an average, compared to a few hundred megabytes last year.
“CreditVidya’s ability to innovate and add value to lenders has made them the provider of choice to leading banks and NBFCs in India,” says Bala.
The team adds that their big data underwriting platform applies advanced machine learning techniques to identify creditworthy customers among the 300 million deserving individuals who do not have any credit history.
Abhishek adds that by leveraging India Stack they have managed to reduce the cost of underwriting small ticket loans by more than 50 percent, and the turnaround time from several days to under 30 minutes.
“Most of the work we have done so far is in unsecured products such as two-wheeler loans, personal loans and consumer durable loans,” adds Abhishek.
Also, today every bank, NFBC and company in the financial services space has recognised the need to embrace technology to suit a wider audience. Vikram Vaidyanathan, Managing Director, Matrix Partners believes that CreditVidya’s ability to find unique insights by acquiring and processing complex data while giving very simple tech solutions sets them apart.
"Today every bank and NBFC has created a digital arm of their own — India Stack has made this switch to digital a necessity. And while they understand lending really well, they work with different tech companies. CreditVidya's founders Abhishek and Rajiv have a deep background in credit rating and underwriting. Their goal is to help banks and NBFCs underwrite new to existing credit borrowers and increase their business," explains Vikram.
According to information provided by alternate lending platform KredX, 98 percent of the Indian SMEs were reported to have granted trade credit to foreign and domestic B2B customers last year. Moreover, 56 percent of these SMEs faced working capital deficits due to unavailability of bank credit.
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