Cash for crunch: Start-up you can borrow from to tide over your month

EarlySalary app offers instant short-term loans. In little over a year, the start-up has approved short-term loans to the tune of Rs 45 crore and disbursed Rs 37.5 crore.

Written by Priyanka Sahoo | Mumbai | Published: July 31, 2017 4:35:29 am
startup news, india news, indian express news, latest news The app runs on an algorithm that sifts through the applicant’s data and checks it with the credit bureau data. (representational image)

Young, urban salaried employees who find themselves broke at the end of the month and wish their salaries lasted a little longer now have a solution in a Pune-based start-up, which offers instant short-term loans at the click of a button. EarlySalary, an app-based lending start-up, was born as a solution to the ‘urban poor’ phenomenon — the financial burden of keeping up the appearance of a fine lifestyle. An increasingly large section of upwardly mobile millennials, who assign great importance to dressing well, eating out and driving a car, has led to the success of EarlySalary, say its promoters.

The app, launched by a non-banking financial company in Pune, has been downloaded over 6 lakh times since its launch in February last year. In little over a year, the start-up has approved loans to the tune of Rs 45 crore and disbursed Rs 37.5 crore.

Almost 39 per cent of these loans were availed by people in the age group of 26 and 30 years. The loan amount ranges from Rs 8,000 to a Rs 1 lakh and is usually availed for anything ranging from a movie ticket to a dinner party, an EMI, a rent advance or even hospital bills.

“The idea was born out of the need for a solution to the end-of-month cash crunch that most people face,” said Akshay Mehrotra, one of the co-founders and the chief executive officer of EarlySalary. “We offer ultra short term loans at a rational rate of interest,” he said, adding that the rate is as low as Rs 9 per day per
Rs 10,000 borrowed.

Mehrotra claimed that EarlySalary was at least 40 per cent cheaper than a credit card and hence, had gained acceptance from consumers in 10 cities across the country, including Jaipur and Ahmedabad.

Yet another feature of the app is its swiftness. For most customers, it takes a maximum of 10 minutes to get a short-term loan approved and credited to the account. “If the customer is KYC enabled, the loan is transferred within a minute,” said Mehrotra.

The app runs on an algorithm that sifts through the applicant’s data and checks it with the credit bureau data. A social media profiling of the applicant helps check for his/ her spending habits. Within minutes, the algorithm can decide whether the applicant should be granted the loan.

The robust checks have helped EarlySalary restrict its defaulter ratio to below 1 per cent, said Mehrotra. “The technology itself is reinvented frequently and our database, too, is growing. This helps us improve or checks and balances,” he said.

Over 100 corporate firms have tied up with EarlySalary as a salary advance partner. The app offers an interest discount to employees of these firms. “Most of our employees are young who relocate from smaller towns to big cities. They have specific time-bound needs. While we do not encourage a credit ecosystem, we have given our employees an option to avail smaller short-term loans,” said Vaishali Vaid, Vice President, Head – Global HR, KPIT Technologies Limited.

Now, there are a host of plans to scale up the solution, such as integrating shopping spaces with EarlySalary. A tie-up with e-commerce platform Amazon is in the offing, where EarlySalary users will get an interest-free month for shopping. “We are also planning to expand our book size and introduce three-month EMIs,” said Mehrotra.

EarlySalary was started by Mehrotra, Ashish Goyal, Vimal Saboo and Vivek Jain, all former bankers, in October 2015 with a seed investment of USD 1.5 million by Ashok Agarwal of Transcop Group. In May this year, the FinTech start-up raised a Series A funding of USD 4 Million. This will now be used to build products, expand skill in machine learning and grow the customer base.

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