AI moving in to help solve ‘human issues’ around loan recovery

Vinson Kurian Banks in India can ill-afford to slacken recovery/collection efforts, given the country’s status as the fifth-largest holder of non-performing assets (NPAs) globally and the highest among BRICS nations.

Broadly, there are two kinds of defaults: one, where the customer does not pay in time, and two, where the customer has no intent or ability to pay.

In the case of the former, banks work with collection agencies to diligently follow up on schedules and collect.

Challenging process

In the second, banks and agencies have to figure out creative ways to induce intent in customers. It is an extremely challenging process. Collection agents have been subject to acid attacks in some cases. At the very least, it involves tremendous patience and hardship. Hence, collection is a less preferred vocation among those who work in the financial sector. Banks are now turning to cutting-edge start-ups, which help solve the ‘human issues’ around recovery/collections with automation and artificial intelligence (AI).

Vymo, a Bengaluru-based start-up, works with four of the five largest banks in India and a host of new NBFCs. Its AI-enabled enterprise assistant automatically detects activities of agents and suggests next best actions, optimised for best outcomes. For one of the large banks that signed up a little over two quarters ago, Vymo has been able to improve the ‘time to win’ by over 10x, says Yamini Bhat, Co-Founder.

Managers have to often take their agents’ word at face value when they say that a customer has been called or met multiple times, she told BusinessLine .

But with Vymo, calls and meetings are automatically detected through integration with the native phone dialler and geo location. “So, managers can instead focus on how to optimise the agents’ efforts. It reduces a huge amount of stress.”

With one of its recent customers, Vymo was able to demonstrate a 35 per cent increase in average meetings completed per day by agents.

‘Positively reflected’

When approached, bankers are reluctant to come on record but concede that these have ‘positively reflected’ in their balance sheets. After all, any revenue collected after the mandatory 180 days is a bonus.

Another point of relevance is that the variability between the top quartile reps and bottom quartile reps in organisations is sufficiently large, implying that the scope for improvement is significant.

Vymo actively learns from the behaviour of most successful agents. Their activities are correlated to outcomes to understand ‘good behaviour’ that is conveyed to all agents.

For instance, days, times and locations of successful collection activities are mapped against customer profile types to nudge the ‘best time of day’ for outreach.

Also, agents are nudged to make unscheduled pick-ups in their location to identify the intent of customers whose payment commitment is doubtful.

With increased efficiency, banks do not have to resort to dubious tactics and risk their brand capital, says Bhat.

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