Though the banking sector can be blamed for the same as well, it cannot be denied that uncertain circumstances too, had played a role. The banking sector is ardently called as the contributor to such an NPA problem as the focus of its primary function has not been on inclusive collection of funds for growth and selective lending which was riddled with biases and imperfections of selectivity.
Another reason that vehemently contributes to the problem is the fact that technology has not been leveraged for effective conclusive collection of funds by the banking sector.
Today customers interact with banks in different ways. Customers of all ages, including SMEs, are increasingly using digital channels to manage their finances.
This follows on from the fact that AI is a game-changer in the banking business. The use of AI has outpaced the institutions' credit-granting decisions. To make credit decisions more efficient and less likely to be deemed a bad loan, AI has effectively and significantly replaced gender or specific character-based lending with algorithms.
The consumer is king in the economy, and its experience must be valued for profit margins. Thus, omnichannel customer experience has become the foundation of successful CX strategy. Currently, 9 out of 10 clients want an omnichannel experience.
Smartphones have drastically changed customers' lifestyles and shifted lender-consumer interactions online. Majority consumers prefer to connect using messenger apps like SMS, WhatsApp. Despite this enormous shift in customer behaviour, outbound call centre collections dominate consumer credit collections, with poor optimization across alternative channels.
Due to the widespread usage of mobile numbers by telemarketers and scammers, borrowers are increasingly preferring not to pick collection phone calls. Consumers generally ignore calls from banned or unknown numbers.
Having put in place the necessary channels, lenders need to embed intelligence into collections processes to ensure that accounts are routed along the optimal path, using the best contact strategy and presenting the best possible treatment options to the customer. In an ideal world, lenders would manage their portfolios proactively in order to prevent accounts from entering collection in the first place.
Lenders can use these more sophisticated models to reliably identify high-risk customers early on and to proactively minimise risk exposure by modifying credit limits and optimizing authorization and pricing tactics.
To acheive this, lenders will need to implement a suite of customised treatments throughout the portfolio, depending on the risk-reward profile and susceptibility to stress.
Customers and collections cases should be segmented by exposure, risk, and behavioural characteristics, as well as capacity and willingness to pay, preferred contact mode, and preferred channels of interaction. This more diversified and personalised strategy will guarantee that resources are distributed in the most efficient manner possible, resulting in significant savings for the bank.
Lenders who improve their collection capacities ahead of the next economic crisis will avoid dealing with growing delinquencies when the economy recovers. As a result, lenders will see larger recoveries, lower expenses, and better returns in the future. Lenders must develop digital omni-channel collection capabilities. This will assure adequate capacity, reasonable prices, and satisfied and loyal customers.
Nitin Purswani is CEO, Medius AI-bank debt collection solution powered by artificial intelligence. Views are personal.)
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