PayMe India raises USD 2 mn from Singaporean Angel Investors

Update: 2018-04-26 22:38 IST

New Delhi : Leading fintech company, PayMe India, on Thursday went official about raising USD 2 million from Singapore-based Angel Investors. The investment round included the line of credit from multiple non-banking financial companies (NBFCs) and fresh cash in the equity round.

Spearheaded by founders Mahesh Shukla and Sandeep Singh, PayMe India is bagging a ton of clients with quick loan approval, processing, and repayments services.

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For making the massive disbursal and evaluation processes easy to manage, the company is adapting to high-tech machine learning and artificial intelligence.

"We have the right blend of business and technical expertise and we are self-sufficient in meeting the demands of the business which is growing by leaps and bounds. Our operational procedure is very much technical-intensive and where hybrid technology plays the key role to build our mobile app; the one single app supports Android as well as iOS listings. This funding round will help us to foster both capacity and market expansion for PayMe India," said Mahesh Shukla, founder of PayMe India.

"India is on the verge of a financial revolution and I am very excited to be a part of PayMe's journey towards financial inclusion and independence for millions of unbanked professionals. Mahesh and his team have leveraged technology creating a platform aptly suited for the GenX professional," said Rishi Bhasin, associate director with Darashaw and Company and an active Angel Investor.

PayMe India offers lending support to corporate individuals (salaried employees) on short-term as well as long-term basis.

Unlike others, the company willingly offers the loans at a reasonable rate of interest and approves the loan in a fraction of minutes.

As of now, the company relies on alternative data and information based on social media and mobile data for credit underwriting.

PayMe India also claims to have built a proprietary underwing credit evaluation model to keep fraudulent applications and risk potential at the wayside.

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