Online lending platform MoneyTap has announced that it has raised ₹500 crore (~$70 million) in a new funding round, which is a mix of equity and debut. The round was led by Aquiline Technology Growth, RTP Global and Sequoia India, along with a few other South Korean and Japanese investors.

Existing investors of the company, Prime Venture Partners and MegaDelta also participated in the round. The company has revealed that debt funding is secured from Vivriti Capital, Credit Saison and others in the form of co-lending and credit lines.

The startup says that it will use this newly raised capital to scale up operations to over 200 cities, innovate with data-backed lending models and for hiring talent. The debt raised will also be used to kickstart operations related to the NBFC licence that the company secured from the RBI in September last year.

Along with investing in technology and data science, the company is also planning to grow its load book to ₹5,000 crore in the next 12-18 months. Currently, it claims to have a loan book of ₹1,000 crore. It  targets customers in the 29-31 years age group with average income of ₹30,000-₹40,000 a month.

MoneyTap was founded in 2015 with an aim to offer an easy access to credit via a mobile app and is largely aimed at working professionals. The app offers instant loans starting from 3,000 to 5 lakh, charging 15-19% interest per annum.

The platform works on a largely unexplored but potentially huge micro credit model. Users looking for personal loans can get an approved limit of upto 5 lakh. However, they will only be charged on the amount that they use from this limit. The minimum withdrawal is fixed at 3000. A user’s credit limit is recharged as he/she repays his/her borrowed amount giving the flexibility to withdraw multiple times.

Instead of depending on credit scores provided by credit bureaus to underwrite loan applications, MoneyTap collects customer data such as bank statements, salary slips, information such as text messages and contacts stored in a smartphone, and location data to underwrite potential borrowers.