The lender acquisition process includes self-sign-up, adding users and defining roles, customizing the policies as per need, and creating business rules enabling lenders to scale their operations faster and more efficiently, shared Sudipta K Ghosh, Co-founder, Roopya in an exclusive interaction with Srajan Agarwal of Elets News Network (ENN).
How is Roopya pushing Financial Inclusion and ensuring underserved masses get access to quality credit?
In India, more than 300Mn borrowers are underserved because these 1000+ lenders do not have access to the latest data and analytics-based origination and underwriting tools which are accessible to only the top 1 per cent of lenders. Considering this disparity in data and insights, RBI in 2022 came out with a regulation of Specified User where an Indian Fintech company can get access to credit data, run analytics on the same and help the small and mid-sized lenders to originate, underwrite and monitor early warning signals of its loan portfolio.
In Sep’22, Roopya became the 1st Indian Fintech company to get access to credit data in all forms which will help enable hundreds of lenders in India who are currently deprived of quality analytics and scorecards for loan origination and underwriting. Roopya built a data and insights infrastructure platform from the ground up where a Lender simply signs up and gets access to advanced analytics for loan origination and underwriting. As a result, the cost of customer acquisition and NPA is coming down for these lenders. In turn, the benefit is being passed to the borrowers. This will be India’s first automated Data and Analytics based Fintech platform in the form of a SaaS delivery model. It has a decision-making engine and automated loan origination platform, providing lenders access to run pre-approval, scorecard, KYC, and BRE on a large pool of borrowers almost instantly on a self-service platform.
How are Lenders using Roopya platform?
- Lender acquisition process includes self-sign-up, adding users and defining roles, customising the policies as per need, and creating business rules enabling lenders to scale their operations faster and more efficiently. Roopya aims to drastically reduce customer acquisition costs for financial institutions by improving their conversion rates.
- Sign up and in 5 minutes, and get access to Lending Analytics on Demand
- The SaaS platform enables loan origination and underwriting support on a single platform combined with a workflow module, decision engine, and scorecard to manage millions of customers.
- Lenders consume Early Warning Signals monitor loan portfolio.
How lending analytics helps in reducing cost of origination for lenders?
Roopya propensity score helps Lenders shortlist potential borrowers from a larger pool. Propensity modeling and predictive analysis are methods of assessing whether a customer is likely to take particular loan product or a credit card. This can help a lender to identify “trigger” events likely to nudge a prospective loan customer or even for cross sell. For example, historical data indicates that when a person gets married, they typically buy a house within three years or whenever a home loan is taken, 50 – 70 per cent chance the person will take a gold loan in the next 6 months. Other triggers might be a high FOIR, continuous credit card o/s, refinancing enquiries etc. Propensity modeling and predictive analytics can help lenders to identify potential warm leads and then market to them directly.
Roopya is the first Indian Fintech to create a data and analytics infrastructure, specifically for Lenders. How exactly will it help lenders at large?
Digital lenders, though Specified Users get access to vast amounts of consumer data gathered in structured and unstructured forms. The abundance of data does not only benefit the lenders at large in decision-making but also creates a data-driven system. Specified Users leverage AI and ML technologies to determine the organisation’s risk appetite. It establishes a framework that supports lenders in weeding out problematic instances in much earlier stages.
Working with a Specified User help lenders develop a digitally strong credit underwriting process. By using ML techniques, Specified User fintech companies can transform large data sets into useful insights and build a reservoir of important credit information required to build a secure end-to-end loan distribution model. Furthermore, it facilitates lenders with a powerful early warning system that boosts the rate of collection, and loss reductions and creates a win-win for borrowers, lenders, and collectors.
What is the impact of recent FLDG guidelines on Roopya and for the lenders?
Due to the latest FLDG guidelines, Loan Service Provides (or LSP) can not only originate but also will part underwrite loans on behalf of the Lenders depending on the agreement between them. LSPs are also now signing up on Roopya platform to access the loan origination analytics. LSPs are also running the policies of the Lenders on the same Roopya platform.
Tell us more about your vision for the next 5 years
Roopya operates in the lending analytics as a service space in India, which has seen exponential growth with lenders working to digitize underwriting/onboarding, while the distribution network remains largely untapped. In India, 2Bn loan transactions were processed in FY22 by 1000+ NBFCs/RRBs/Cooperative Banks/MFIs. 95 per cent of these lenders originated 40 per cent of retail loan applications, but they don’t have access to the latest analytics tools or platforms. Roopya’s platform offers a platform and analytics as a service to these lenders, through a SaaS-based lending infrastructure, empowering these NBFCs, MFIs, RRBs, cooperatives, and fintech companies to provide credit to over 400 million retail customers. The Global Digital Banking platform market is valued at $3.95B in 2019 and is expected to grow to $10.8B by 2027.
