While we have inhouse and partner expertise in SME lending, loans at the ticket size, volume, and interest-rate spreads we provide, has been a thoroughly unprofitable venture (to our knowledge). To properly serve social enterprises at scale with the interest rate spreads we offer, a new approach towards due diligence and loan management is necessary. We have leveraged on technology adapted to local contexts to lower costs, improve efficiency and reduce risks.
We have developed our own internal systems that aid in 3 areas: customer outreach, loan management and risk mitigation. The system uses data analytics, chatbots and various other technologies to form an end-to-end system that handles the volume of loans we’ve come to expect. It improves transparency and resource allocation by providing a platform that our stakeholders (partners, social enterprises and funders) can trust.
More importantly, this system is uniquely designed for our target markets, with their cultures and behavioural habits in mind. Let’s take outreach as an example. With many of our social entrepreneurs using smartphones as their primary device, adopting a mobile-first approach in the design of our system was essential. Working on the ground in India, we learnt that outreach methods such as email or even SMS were inefficient methods to reach our entrepreneurs. Instead, what worked best was WhatsApp and phone calls. With 400 million users of WhatsApp in India, it emerged the obvious choice for our primary outreach system. We created a WhatsApp chatbot which acts as our primary touchpoint with our social entrepreneurs, improving and automating due diligence processes. It also keeps us up-to-date with our social entrepreneurs, and would eventually allow us to provide services such as mobile repayments and tutorial videos to them.
This outreach system is one example of how our loan management platform goes beyond traditional systems to cater to the local and specific needs of our beneficiaries.
Photo credits: Photo by Priscilla Du Preez on Unsplash
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