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For India’s millennials, this startup gives loans for gadgets
March 10, 2016

Big data is not always evil. In fact, depending on what it’s used for, it can benefit communities.

Count Finomena among the guys aiming to do good with big data. A startup that lends small amounts of money to students and other millennials to make online purchases, it collects over 20,000 pieces of information – everything from public information on social networks to buying patterns on phone top-up websites – to figure out eligibility, interest rates, and the size of a loan.

“Never before in the history of the world has there been such an explosion of information about a single place,” says Riddhi Mittal, the co-founder of Finomena. “We believe that this data can be used to help those that have been financially excluded in the country.”

Riddhi and her co-founder Abhishek Garg were not two people you’d call “financially excluded”. Riddhi is a Stanford graduate who has worked at Facebook and Microsoft, and Abhishek is a graduate of one of India’s elite universities, IIT Delhi, and spent years working with Boston Consulting Group.

And yet, when Abhishek applied for a loan, he was rejected. “I had a salary of over US$150,000 with a credit score of 785,” he says. “That was when the realization hit me: if I couldn’t get a loan, how about everyone else?”

This thought spurred the two to find out more about the country’s buying behaviors, and together, they launched Finomena. “If you know how to analyze big data correctly, you can figure so much out about India,” says Riddhi.

It’s a bit early to say whether the startup will be successful, but just today it received a dose of confidence with an undisclosed amount of funding money. The round was led by Matrix Partners and ten angel investors, including Abhay Singhal, the co-founder of InMobi and Kaushal Aggarwal, the managing director of Avendus Capital.

More data, less problems

Once a potential borrower registers their phone number with Finomena, they can key in links of items they want to buy with a loan. Snapdeal, Amazon, or Flipkart – India’s three major ecommerce players – are supported. Users can then figure out the size of their down payment, how much they want to pay each month, and how long they’d like to pay for.

“We provide buyers with an end-to-end service,” says Riddhi. “Borrowers really don’t want to see the complexities that go behind figuring out a loan, and our technology makes it easy for them to get what they want.”

On the other end, Finomena scans the information that it has about the borrower to figure out how risky it is to give them a loan and, depending on that, how big it should be. Then, it sends info to one of its partner banks who then verifies and provides the loan.

Its algorithm operates off of three sources of data: direct, which is information that a potential borrower provides, indirect data, which comes from public domains like Google, and derived data, an analysis of larger trends from both of these sources.

“Imagine this: a design student is asking for a loan, so we go online and check out her Behance profile in order to understand her personality better.”

“This type of information helps us figure out behavior,” Abhishek adds. “Is someone using Coursera more likely to pay back their loan? How about someone who tops up their phone at the same time each month? Or someone who diligently walks five miles a day?”

And, because the demographic they’re choosing to work with is college students and young professionals, it’s nearly impossible for a potential borrower not to have data online.

“More than fifty percent of the country is less than 25 and all over the internet,” says Abhishek. “At this point, we almost have too much data to work with.”

Loans make the world go ‘round

From one angle, the Finomena model is built to help people understand how to be responsible with their money. Loans can only be used on specific, pre-approved items like laptops, cameras, and hard drives, and Riddhi explains that it’s their way of contributing to the financial inclusion movement.

“We’ve seen startups focusing on shoes and perfume and that sort of thing,” says Abhishek. “All that’ll do is build a bad credit score and create bad spending habits. It’ll also pull down our country’s market. We’re trying to strengthen it.”

The more loans that are successfully taken out and paid back, the more robust a country’s economy is.

“See, credit scores work well in the United States because a good part of the population has a credit card,” explains Abhishek. “There’s enough data for that to be a real system. In India, barely 25 percent of the country has a credit score.”

“In 2002, there was a big tech slump, where ICICI Bank was going berserk giving out credit cards like crazy to students that were asking for it,” adds Ridhi. “They were excited that this was an untapped population, but most of these kids just couldn’t pay it back. This is horrible for the economy.”

Lending startups galore

The new funding will be used to build out Finomena’s credit and risk technology team, as well as work on its machine learning capabilities.

Investing in a loan startup is a big move of confidence from US-based private equity firm Matrix Partners because its other investments have all supported growing startup trends in India, including Ola, healthcare firm Practo, and classifieds site Quikr. It’s made other bets in fintech, including ItzCash, a startup that produces prepaid cash cards, and Razorpay, a startup that helps merchants get payments from credit cards and mobile wallets.

Earlier this year, similar startup Buddy raised US$500,000 from the likes of Blume Ventures and Tracxn Labs. Unlike Finomena, however, Buddy has no restrictions on what borrowers can buy, focuses mostly on college students, and does not claim to have a deep affiliation to big data.

Microfinance is another method that people have used to try to get the country’s underserved into the loan system, but the money it provides is often too small, the interest rates too high, and the scale too small to matter.

“When Prime Minister Modi talks about financial inclusion, this is what he means,” Riddhi says. “It’s rational, it’s careful, and it’s getting people buying more things.”

 

This article was originally published techinasia.com and can be viewed in full here

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