Borrower-focused loan recovery models most efficient: Credgenics

The Reserve Bank of India (RBI) recently issued guidelines to banks and Non-Banking Financial Companies (NBFCs) regarding loan recovery practices. With reports of harassment and intimidation by debt collection agents on the rise, the latest guidelines are a welcome move for borrowers and consumers.

But why has the loan recovery process always remained full of challenges?

Loan recovery has traditionally been a low-tech operation. The uptake of loans spiraled during and after the pandemic, exerting massive pressure of the recovery mechanism. With millions of accounts – from credit cards to home loans – processing the borrower data manually is a mammoth task.

According to some banking professionals, when it comes to product innovation only the loan products see innovation; the recovery is usually slow, manual and inefficient. Lenders would not want to invest more in recovery since it makes lending less viable.

However, technology is changing the rules of the game, and for the better.

According to Rishabh Goel, CEO and Co-Founder, Credgenics, a digital debt collections platform, “Debt collections remains a manual process, resulting in lost recoveries, an increase in human error, and time-consuming operations. Typically, standard collections approaches are applied in bulk without a focused, personalized, and segmented approach, which leads to inefficiencies.”

The collections space in developed markets like the US and UK is more evolved with banks and large financial institutions showcasing extensive capabilities to manage delinquent debt internally as far as 90 (Days-Past-Due) DPD or more. The debt managed must comply with strict requirements set by the regulators for customer reach out and engagement.

But Asia and India are catching up.

Goel said, “In recent years, Asia has been delivering game-changing growth and innovations, especially in banking and financial services. With proper employment of technology and with the help of Machine learning, Artificial Intelligence, and Automation, a data-driven approach helps lenders analyze the underlying patterns of consumer segments, fine-tune existing strategies to address individual consumer behavior, and predict the probability of recovering loans from a customer by laying down a framework of actions required. Research shows that such a data-driven approach in loan collections increases loan recovery while decreasing the cost of collections.”

Taking a customer-focused approach to loan collections works well for both the industry and to improve the credibility of the finance and fin-tech industry. The new guidelines will help the industry’s growth in the long-run. Goel added, “The current progress in India, in governing the collections processes to avoid customer harassment, is a move in the right direction. Keeping the borrower at the centre and forming policies for fair treatment of genuine defaulters is the need of the hour. A robust mechanism to create awareness around maintaining credit profiles with timely payments and avoiding defaults will go a long way in boosting compliance.”