Big Idea: Removing Aggression From Debt Collection Equation Could Reduce Banks’ NPAs – Times of India | Vette Leader

According to RBI Financial Stability Report, released December 2021, banks’ gross non-performing assets (GNPAs) may rise from 6.9 percent in September 2021 to 8.1 percent by September 2022 in the baseline scenario, while in the severe stress scenario they could rise to 9.5 percent. While the NPAs may not reach extreme levels due to the actions taken by stakeholders and the recovering economy, they would still be at levels where comprehensive action would be needed.

Reasons for higher NPAs include poor credit risk assessmentexcessive exposure to non-creditworthy segments, deficiencies in tracking portfolio health, lack of analysis of default patterns, push for priority lending, impulsive borrower decisions, inefficient early warning systems, improper documentation, poor data management, erratic communication with borrowers, flawed credit risk management, and more.

Borrowers who are unaware of the impact of loan defaults

In many cases borrowers are unaware of the serious consequences of defaulting on loan repayments – a factor that reduces their chances of easily obtaining credit in the future. It is important for banks and other non-bank financial organizations to consider a holistic approach to mitigating and resolving NPAs.

According to KPMG reportThe digital lending sector will be the sector with the highest penetration of digital channels in India by 2023 with a growth rate of 48 percent and a valuation of USD 350 billion compared to USD 110 billion in 2019. Pandemic, the preference for digital banking and digital communication channels will continue raise.

The rapid rise of the FinTech ecosystem and digitization initiatives in banking point to a holistic push for digitization. What is to be seen, however, is the willingness of the banking and non-banking financial ecosystem in India to capitalize on the growing momentum for digitization when it comes to loan collections and debt recovery.

Does the traditional collection approach work?

The traditional collections approach includes a heavy reliance on manual intervention, crude tactics to force customers to pay, outsourcing recoveries to agencies with questionable credentials, relentlessly calling customers, and intimidating customers with strong messages. However, today’s customers are more mature and sensitive. They have experienced and embraced the superior customer service of other industries that are at the forefront of innovation and transformation. In fact, the slow pace of digital transformation in traditional banking and increasing customer demand for change have been some of the key catalysts behind the FinTech revolution and the emergence of disruptive banking models.

Artificial intelligence makes debt collection more human

AI-powered technology platforms offer the answer to a more humane approach to debt collection. They combine the power of intelligence, automation, digitization and data analysis, which can be a long-term solution for banks to adopt a nudge-based approach. AI can help banks understand customer preferences, align collections strategies accordingly, improve customer experience, and reduce NPAs in the process. It has been observed that more than 50% of personal loan recoveries can be successfully completed digitally and automatically. This potential has not yet been exhausted.

Evolved customer segmentation helps classify borrowers into multiple groups, which can then be targeted differently for better results and greater efficiency. For example, borrowers in the prepayment phase may just need a gentle reminder or nudge of their upcoming payments due. Automating those reminders and adding customer-specific information, leveraging digital channels and routing them according to customer preferences can make a world of difference. Similarly, digital lenders, FinTechs and the BNPL segment, where credit card sizes are small but volumes are high, require a bespoke digital collections strategy that is fully focused on the customer category.

Strategic optimizations in communication with customers make a big difference

Communication channels today have evolved extensively in terms of reach, intelligence, embeddability, customizability, and flexibility. Using a comprehensive approach to communication across all channels including WhatsApp, SMS, voicebots, chatbots, IVRs and email can be a good start. After customer segmentation, the communication should be personalized with appropriate information and examined for adaptation to the vernacular. It is important to also consider the borrower’s preferences in terms of time, place, receptivity and mode of communication in order to achieve better response and conversion.

AI-powered conversational voicebots can reach customers, streamline payments, and automate reminder communications without human intervention. Pre-programmed and intelligent voicebot calls are much better as they give borrowers the power to choose when and how to repay loans. Customer response to the call can automatically trigger the text messages with digital payment links and the bot stays on the call to help them complete the transaction successfully.

Big data analytics helps determine behavioral patterns and identify the most appropriate communication strategies. In fact, the entire communication journey can be pre-planned and pre-programmed like a matrix, where all possible reactions are considered and the next phase is automatically triggered based on the customer’s reaction to the previous phase. Communication becomes completely human-free, automated, meaningful and intelligent.

Poke, don’t push; Empathy instead of aggression

The AI ​​engine can continuously optimize the communication strategy based on the results and refine the actions accordingly. Supported by AI and data science with a focus on behavior analysis, prediction models, Improving segmentation efforts and enabling tailored communications with customers can help make collections strategies more effective. Lenders can use relevant data to identify red flags of likely delinquency and delinquency, predict non-payment situations and provide tailored solutions.

Postponing digital transformation in collections and embracing digitalization in other banking functions can leave significant gaps in a comprehensive and effective digital strategy. The experiences that customers take with them when they pick up items are lasting and make a significant contribution to customer loyalty. Therefore, it is important that banks and other non-bank lenders begin to work on a future collection conversion roadmap. The seamless combination of financial services and new collections technologies will help build a resilient digital economy, drive the holistic transformation of the banking industry and set new standards for customer experience.



The views expressed above are the author’s own.


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