How Data Analytics Can Help Financial Institutions Combat NPAs

The Indian economy has witnessed a remarkable transformation in recent years, with digital innovation permeating various sectors and revolutionising traditional business models. This wave of technological disruption has opened new avenues for the growth of Indian banking and finance companies and presented a unique opportunity to address the issue of delinquencies and non-performing assets (NPAs) in retail lending. 

For quite some time, India’s financial institutions have grappled with the burden of delinquencies and NPAs, which have impeded economic growth, strained banking systems, and hampered the flow of credit. There are several reasons for NPAs in the Indian banking sector, including high exposure in priority sector lending, poor economic decisions by borrowers, inadequate credit appraisal and due diligence, deficient security, a lack of oversight of the loans and fraud by borrowers.

The Indian government has taken several measures to reduce the burden of delinquencies and NPAs, with banks not far behind. Indian financial institutions have devised effective strategies to mitigate this challenge and minimise their losses. In fact, it is projected that the gross NPAs of Indian banks will plummet to an impressive low of 4% by the close of the fiscal year 2023-24, while the retail segment gross NPAs are also expected to be range bound at 1.8 – 2% over the medium term.

Central to this success is the adoption of advanced technology and the integration of robust data analysis capabilities offered by new-age technology platforms that identify potential delinquencies early for corrective actions and also assist in identifying, managing, and mitigating NPAs.

Harnessing Technology To Optimise Collections Efforts

The digital prowess of borrowers has compelled banks and other financial institutions to recognise the undeniable importance of digital engagement in retail loan collections. The days of mindlessly bombarding borrowers with repetitive follow-ups are long gone, as they have proven ineffective. Instead, the focus has shifted towards harnessing the power of digital nudges, timely reminders, and user-friendly payment methods to optimise collection efforts. This paradigm shift has paved the way for a thriving digital lending market in India, projected to experience a staggering growth rate of 48% by 2023.

The ubiquity of smartphones and the emergence of app-based finance have made self-servicing a crucial aspect of collections. Lenders must now offer multiple communication channels, such as WhatsApp, chatbots, voice bots and other platforms, to provide a personalised approach. This reduces costs, minimises delinquencies and elevates the borrower’s experience by ensuring timely and relevant communication. 

Enhancing Debt Collections With Data-Driven Insights

Debt collection is a critical component of a lender’s business, and data-driven insights can significantly enhance this process. Advanced debt collection software that utilises predictive analytics, artificial intelligence and machine learning can provide lenders with accurate and data-based actionable insights. 

Using this data, lenders can segment borrowers, build tailored strategies that cater to borrowers’ needs, streamline the collection process and improve customer engagement. Real-time tracking of the performance of collections strategies and tweaking them for optimal outcomes go a long way toward boosting recoveries at a lower cost. Additionally, data-driven insights are critical in the early identification of potential delinquencies to trigger corrective actions, ultimately reducing bad debt write-offs and mitigating the risk of non-performing assets (NPAs).

Moreover, incorporating advanced analytics models can result in savings of over 30% with no loss in operational performance, leading to more focused actions and better outcomes throughout the collections lifecycle. From pre-due to legal stages, lenders can leverage the power of data-driven insights to enhance their debt collection processes, resulting in improved efficiency, reduced bad debt write-offs, and ultimately, a better bottom line.

How Is AI & Behavioural Segmentation Changing The Game?

For years, debt collection has been a dreaded and overwhelming process for borrowers, involving aggressive tactics such as endless calls, intimidating messages and confrontational agents. Fortunately, technology has ushered in a new era of debt collection through AI-powered platforms, enabling banks to provide a more personalised and empathetic approach.

Using behavioural segmentation, banks can divide borrowers into various segments and curate a personalised approach that ensures borrowers receive friendly reminders about their upcoming payments through digital channels. Notably, leading banks using behavioural segmentation have reported significant improvements of up to 30% in the amounts collected and the number of loans written off. The emphasis needs to be more on understanding the borrower’s situation and providing a tailored approach to resolve the debt as soon as possible.

The Bottom Line

As India aims to become a $5 Tn economy by 2029, banking institutions must proactively address the challenge of NPAs by leveraging cutting-edge technology and data-driven analytics. Advanced algorithms and predictive models are used to quickly detect signs of potential defaults and enable timely corrective actions.

Furthermore, AI and data-driven analytics have made it possible to recover over 50% of loans without human intervention, demonstrating the significant value of technology in optimising the debt recovery process. With a more personalised approach, borrowers can enjoy a stress-free experience, while banks can build long-lasting relationships with their clients and ensure the financial health of their institutions.


The post How Data Analytics Can Help Financial Institutions Combat NPAs appeared first on Inc42 Media.


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