Indian customers across Retail and SME segments, who are unable to get loans from banks, are willing to pay high interest and fees to get credit from Digital Lenders. In the last 5 years, hundreds of Digital Lenders have tried to build a business and very few have been able to scale profitably. Despite massive investments, India is yet to see any Fintech Unicorn in the Lending business.
What are the key challenges in setting up Lending Business?
Unlike Payment Business, which can scale with deep technology and inherent engagement frameworks like Payment gateway or POS, Scaling lending business needs:
- Capital as raw material
- Deep industry knowledge across Credit and Collections
- Technology platforms for Onboarding, Underwriting, Loan Management, Early Warning, Collections
- Partnerships for sourcing customers
We have seen lenders erring on one or many of these areas because of the sheer complexity and enormity of the work required to set up and scale lending business.
Key challenges faced by lenders are:
- Acquiring customers at low cost: Customer acquisition cost has remained a deterrent and makes it harder than it appears. With customer acquisition costs running into thousands of Rupees, it is nearly impossible to make it profitable in just one cycle of lending.
- Customer Engagement: Customers do not have a need to engage with lenders post disbursement. This results in complete disengagement with lenders, wherein lenders can just track the repayments by the customers. Most lenders have tried to offer apps and complimentary services, very few have been successful in this endeavor. With low customer engagement, it is even more difficult to get into the second cycle of lending.
- Lack of Continuous flow of Capital: We have seen this as the starting point for major breakdowns of digital lenders in the last couple of years. This is amongst the hardest part and many lenders have now focused on partnering with other lenders for sourcing their business through FLDG based risk-sharing or co-lending.
- As business starts and stops due to capital, with the availability of funds, we have seen a sudden rush to disburse funds without enough focus on risk management. “We have 2 million USD to be disbursed in the next 60 days and we already incurring the cost of funding”
- Lack of Collection and Credit Skills: Despite everyone knowing that the hardest part in lending is getting the money back, many digital lenders start with a strong customer onboarding platform with a quick disbursement focus. Credit and collections take the back seat initially with no one in senior leadership from these backgrounds. With time and an increase in NPAs, many of these lenders tend to fix these areas. While it may work for some, it may be too late in most cases.
- Partnerships for Sourcing Customers: We have seen most customer platforms including Edutechs, E-Commerce, Taxi Aggregators, etc helping their customers in getting credit. It is critical for digital lenders to partner with these platforms for servicing the credit need of the customers. This not only reduces the customer onboarding costs, it also helps the lenders in getting deeper insights on the customer based on proprietary data of the platform.
- Disjointed / Weak Technology: While many have “Proprietary Algo for Underwriting and 5 min Disbursement” in their tagline, rare are the Digital Lenders, who have done this well. To build and / or implement end to end technology platforms, digital lenders need very strong technology leadership.
Lenders need to invest optimally in
- Customer Onboarding Platforms: Directly on their own web or mobile or chat platforms or through partnerships with customer sourcing companies.
- Data Aggregation: Getting access to customer data from external sources to help in credit underwriting as well as for early warning. We have seen the availability of multiple startups in this segment offering newer sources of data at lower costs. Lenders should always be scanning the ecosystem for the changes and plan for deploying incremental sources at a fast pace. To ensure that there is no dependence on one source to avoid blackouts, lenders should work with multiple data aggregators.
- Loan Origination System (LOS): This is where the customer is managed from the lead to the conversion stage. This platform integrates the entire customer journey until disbursement from the Loan Management System. We have seen leaky LOS platforms creating friction, thereby reducing efficiencies by as much as 50%. We have seen most legacy LOS platforms not supporting the expected level of APIs and flexibility.
- Underwriting Platform: This is the heart of the entire lending business and lenders should have a disproportionate focus on this platform. While they may start with the usual Rule Engine, they must look at AI-based decision engine either by partnering or by building on their own.
- Loan Management System (LMS): This is where the customer loan is housed and serviced from the disbursement stage to the collection stage. This platform should be flexible in handling different products, services, repayment methods, accounting, and NPA management. This should support flexible APIs for integration with one or multiple LOS platforms/systems. We have seen most legacy LMS platforms not supporting newer financial products and repayment schedules.
- Early Warning System: This platform helps the lenders in tracking the real status (financial and / or intent) of customers before they default on their payments. This was originally expected to be done by the relationship manager of the customer. With the availability of data in the ecosystem, this can now be done on real-time basis.
- Collections: This is the hardest part of the lending process, as lenders try to get the money back from defaulting customers (with or without the intent of default). Robust communication frameworks with insightful employee apps with real-time collection facility are key to reducing defaults.
We think that in the next 3 years India will have at least 5 lending unicorns which will grow profitably by focusing on each of the areas detailed above.