This Can Really End the Problems of Money Lenders and Borrowers Here's how the latest technology can be applied to ease the burden of non-payers for lenders

By Madan Srinivasan

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It's a great time to be a borrower in India. Retail lending is undergoing a Cambrian explosion of sorts and the upstarts, young banks and NBFCs, are slugging it out with the larger banking giants. The grand prize – The Indian Borrower's affections.

The burgeoning loan pools of banks come with attendant issues of loan defaults. And while technology in underwriting loans has evolved, its use in "Collections' i.e. getting borrowers to repay their loans on time, is coming of age as well. Here are three areas where the latest technology can be applied to ease the burden of non-payers for lenders.

Ending the Myth of Predestined Default

Loan defaults are not inevitable. Only about 5%-10% of defaulters are willful ones - the rest are victims of adverse circumstance. Whether borrowers default depends to large extent on their ability to foresee bad situations and conquer them.

Consider now a lender who provides the borrower access to a simple tool with every loan. The tool assesses the borrower's extant Credit and Financial Knowledge and helps him upgrade this knowledge over the period of his loan. Done right, this can keep borrowers engaged and give them a ready "helper' in times of financial duress. Couple this approach with micro-rewards to keep the borrower motivated to maintain financial discipline and you've created a fascinating "Game' for Borrowers to play. A game that not only helps borrowers navigate choppy financial waters, but by giving them the right crisis management tools, also reduces default rates for lenders significantly.

Non-Invasive Intervention

Today lenders follow a simple formula when someone misses a payment (or two). You start by sending mild reminder messages, that become louder as time passes. Tied to this is a call center where someone has the unenviable task of repeatedly chasing the borrower to address his slippage.

What is lost here, is the time and intent to empathize with the customer and his situation. Often this ends up aggravating the problem rather than solving it. Customers feel aggrieved at being hounded around the clock and refuse to engage – triggering still more aggressive approaches from the lender and so on.

Contrast this with a technology led, non-invasive approach. By using Smart Chatbots, lenders can provide a neutral, controlled environment for customers to "discuss' their situation and explore resolution opportunities with certain remedial measures baked into the bot itself. Given the finite range of issues within which customers tend to lie, programming the bots for efficiency is quite possible. Over time, the interactions on the bots will serve as a template for learning to make the process more effective – leading to higher resolution rates and lower costs.

Re-engagement and Rehabilitation

Despite all efforts, some borrowers will be unable to prevent the slide into eventual default. Lenders often lose touch with borrowers at this stage and resolution becomes a complicated issue. Lenders need to trace customer whereabouts, estimate how much they can pay back and then negotiate a settlement. Given that this is largely a manual process, it is expensive, confrontational and most importantly, it doesn't scale.

Instead, lenders can adopt a three- pronged digital approach. First, machine intelligence can analyse customer profile data and tell lenders what message will resonate most with the borrower to bring him out of his shell. Second, social media tools such as Facebook Custom Audience can non-intrusively target the borrower with this messaging without any need to contact him physically. Third once the customer responds to the messaging, a digital negotiation platform can guide the borrower to resolution without any need for human intervention. The interplay between the three elements is key here - with multiple automated cycles of messaging and digital interaction leading to a resolution. Put together, all three to create a cheaper, more effective and scalable borrower resolution mechanism.

Future advancements in AI and Machine learning will give these solutions greater elegance and may even create a situation where lenders can focus fully on underwriting and acquisition with the entire collection effort being automated. However, to prepare for such a future, lenders must start to invest in systems that can make the transition seamless and it is as good a time as any to start.

Madan Srinivasan

Co-founder, Creditas

Madan is the Co-Founder of Creditas Solutions, an innovative FinTech startup that utilizes Machine Learning and technology to help Banks, FIs, and NBFCs better reach out and connect with customers, while optimizing a host of processes like Customer Acquisition, Cross-Sell, Delinquency Detection, Financial Literacy, and Debt Recovery. An Operations expert, Madan has over a decade-long experience in setting up and scaling high performance teams.

An alumnus of the Indian School of Business, Hyderabad, Madan has spent over 15 years in managing techno-functional setups for tech giants and financial start-ups.

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