Banking in 2021: NPAs, bad banks and technology breakthroughs Looking back at the year gone by for India’s banking sector

Jaya Vaidhyanathan

2021 has been a year of surprising resilience and innovation in fintech. Cornered by pandemic-induced lockdowns and confronted with lagging economic prospects, some of India’s leading banks heightened their focus on across-the-board digitalization. All functions – from the customer frontline to internal processes, like credit monitoring and audits – were exposed to the benefits of technology. The year’s events also triggered the entry of smaller, nimbler fintech players, with unconventional models that enabled credit growth in new segments.

Without a doubt, the biggest financial development of the year has been the unexpected bounce back of the Indian banking system from the clutches of poor asset quality. Non-Performing Assets or NPAs are viewed as the most important metric in gauging an economy’s performance. This stems from the Credit-to-GDP ratio, which is the ratio of formal bank credit to the GDP of the country. While there is no perfect number, the figure for India is less than 60%, as compared to 100% or above for many other economies. As credit fuels economic growth, a higher Credit/GDP ratio is desirable. Unhealthy asset quality deters banks from lending more, either due to capital constraints or due to the fear of new loans going bad.

Still, when compared to the doomsday predictions from not so long ago, this was a pleasant surprise.

While absolute NPA levels remain high and are expected to be so until March 2022, the worst seems to be over. Compared to the gross NPA (GNPA) figure of 7.5% of gross assets as of March 21, the Indian Scheduled Commercial Banking system is expected to post GNPA figures of 9.8% by March 22 as per the RBI (Financial Stability Report dated Jul’21).

What do the numbers imply? While Indian banks continue to struggle from the effects of past NPAs, fresh additions have definitely slowed down. The annual slippage ratios of the Scheduled Commercial Banks fell to 2.5% of standard advances in FY21. This means that while legacy issues may take time to resolve, banks are probably beginning to manage credit better.

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A heartening fact is that the one-time restructuring facility given by the RBI to help borrowers tide over the crisis has not significantly dented banks. As of March 21, restructured assets amounted to only 0.9% of total assets, with the figure at 1.7% for the worst affected segment, namely MSMEs. Furthermore, write-offs as a percentage of GNPA at the beginning of the year fell sharply as compared to 2019-20.

Despite evident signs of progress, India is still one of the majorly affected economies in terms of banking asset quality. But, enabling and amending regulations, such as The Insolvency and Bankruptcy Code (Amendment) Ordinance, 2021 (IBC), have translated into a sharp drop in NPA write-offs (20.5% of GNPAs written off in FY21, compared to over 30% in the preceding two years).

Regulatory authorities have been taking further remediating measures as well, especially in the wake of the pandemic. One such measure is the implementation of bad banks.

Decoding India’s bad banks

As a bank’s asset quality degrades, the profitability of the institution is negatively impacted via higher provisions. Furthermore, it affects its future health, as lenders are reluctant to extend new loans because of fears of loan defaults and capital depletion. In this regard, the Indian Banking Association had suggested the idea of the “bad bank” to the government, which would take up the bad assets and turn them around, freeing up the banks for lending activities.

The promoters of the idea take comfort in the fact that the concept has worked to a large extent in many countries – the US, Ireland, Germany, Indonesia, and so on. It has also shown results in India, albeit in a smaller measure when the bad assets of the erstwhile IDBI Ltd. were transferred to a Stressed Asset Stabilization Fund in 2004. The Yes Bank crisis of 2021 and its resolution further demonstrated that our banking system is capable of cooperating while competing. In a similar fashion, a bad bank with participation from existing banks in terms of ownership or professional skills can ensure that the banks have skin in the game. A higher recovery rate by the bad bank would translate to higher profits to the owners – the banks themselves.

The bad bank set-up proposed by the government is to have the following two-tiered structure:

● An Asset Reconstruction Company (National Asset Reconstruction Company Limited – NARCL) in whose books the NPAs shall be transferred,
● An Asset Management Company (India Debt Management Company – IDMCL) consisting of professionals that would strive to recover NPAs through turnaround measures

India’s bad banks framework holds great potential for the banking industry:

● The ₹30,600 crore government guarantee for security receipts issued by NARCL will be vital towards improving recoverability
● With NARCL as one of the bidders, individual ARCs will be urged to bid for loans at competitive rates, faster, curbing low buyouts and delays
● Being owned by a joint PSB-private partnership, NARCL raises expectations of speedy recovery
● With the involvement of IDMCL, it is expected that the entire process of asset resolution will be hastened and value-added

Of course, the concept has detractors who have opined that

● In practice, the whole process is just basic accounting, shifting assets from one entity to another – the banking system still has NPAs
● Having a bad bank will encourage banks to lend recklessly, knowing the bad bank will absorb non-performing assets if any
● Bad banks buy commercial bank loans at a discounted rate, and a well-established price discovery mechanism does not exist for this process

The concerns raised by the naysayers carry merit. Ultimately, the successful implementation of the proposed bad bank would hinge on the effective mitigation of these risks through a wide range of factors:

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● The credit monitoring processes at banks need to be reformed summarily. Having the right technology backing in place leaves lesser room for subjectivity. For example, rules-driven, Early Warning Systems can be instrumental in forewarning bankers of stress or potential fraud in borrower accounts
● Pricing of bad loans is to be done through competitive bidding. This puts relative objectivity into the discount on the asset value while it is being sold to the ARC
● Lastly, the bad bank ought to put in place a process to accurately assess assets before choosing between liquidation or revival. Certain assets become bad debts because of extraneous issues. In such cases, liquidation can be counterproductive, with a good asset being forcefully sold off cheaply, whereas revival would benefit all parties involved

Conclusion: Ensuring asset quality the right way

It is well understood that prevention is better than cure. The best way to work around the NPA problem is to nip it at the bud. Tackling asset quality challenges effectively at the core calls for a two-pronged approach:

● Technology intervention: Fintech players need to utilize the cutting-edge technology available at their disposal for improving lending practices and customer experience. This includes Open APIs, microservices, cloud infrastructure, big data, and AI/ML, to improve operational, predictive, and prescriptive efficiencies
● Regulatory involvement: Authorities need to put in place regulatory mechanisms to secure the process of lending and credit monitoring, including stringent data privacy laws

With a fair share of assistance from regulators, technology is already enabling banks, financial institutions and fintechs to overcome typical challenges and build new revenue models.

● Lenders are adopting precision techniques to study borrowers instead of relying on past stereotypes. For instance, rural lending in segments such as farming, relied solely on rains in the past. A good monsoon implied good money in the hands of the farmer and a bad monsoon meant bad loans. Today, lenders study the borrowers’ markets to the extent of analysing the quantity of rainfall and exact crop performance per location, and consequently take better credit decisions
● Lenders are learning to identify their core strengths and maximize their performance in that area, instead of spreading themselves thin across super diversified loan products and customer segments. Credit monitoring will be fine-tuned to the extent that this becomes a competitive advantage – one lender keeps getting the best customers repeatedly due tosuperior modeling capabilities
● Credit origination is seeing innovation. The pandemic saw even the most traditional of banks go online to service existing customers. However, savvy new-age fintechs went one step further and used technology to acquire new customers. This year will see both these players come together, with technology helping upstarts source customers, and hand them over to established lenders for a fee. This way, the fintechs get to monetize their analytical skills while the banks get to improve their asset quality – a win-win situation!

Also Read: The Indian Banking Opportunity – Transforming the Business of Banking

We are living in a world where the baseline for digitalization is rapidly changing. Financial institutions need to either embrace new technology or risk being left behind in the age of fintech. The digital revolution is here, so why not jump onboard? The banking industry, like many other industries, is experiencing changes. It has become increasingly difficult for banks to keep up with the pace of innovation that customers desire as well as the kind of efficiencies they themselves pursue, like better credit, minimal risks and optimal asset quality. In this context, technology has become a key ally allowing banks and financial institutions to chase excellence at an accelerated pace and on sure footing.

Views expressed in this article are the personal opinion of Jaya Vaidhyanathan, CEO, BCT Digital.

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