The issue of Non-Performing Assets (NPAs) in the Indian banking sector has become the subject of much discussion and scrutiny. The Standing Committee on Finance recently released a report on the banking sector in India, where it observed that banks’ capacity to lend has been severely affected because of mounting NPAs. The Estimates Committee of Lok Sabha is also currently examining the performance of public sector banks with respect to their burgeoning problem of NPAs, and loan recovery mechanisms available.

Additionally, guidelines for banks released by the Reserve Bank of India (RBI) in February 2018 regarding timely resolution of stressed assets have come under scrutiny, with multiple cases being filed in courts against the same. In this context, we examine the recent rise of NPAs in the country, some of their underlying causes, and steps taken so far to address the issue.

What is the extent and effect of the NPA problem in India?

Banks give loans and advances to borrowers. Based on the performance of the loan, it may be categorized as: (i) a standard asset (a loan where the borrower is making regular repayments), or (ii) a non-performing asset. NPAs are loans and advances where the borrower has stopped making interest or principal repayments for over 90 days.

As of March 31, 2018, provisional estimates suggest that the total volume of gross NPAs in the economy stands at Rs 10.35 lakh crore. About 85% of these NPAs are from loans and advances of public sector banks. For instance, NPAs in the State Bank of India are worth Rs 2.23 lakh crore.

In the last few years, gross NPAs of banks (as a percentage of total loans) have increased from 2.3% of total loans in 2008 to 9.3% in 2017 (Figure 1). This indicates that an increasing proportion of a bank’s assets have ceased to generate income for the bank, lowering the bank’s profitability and its ability to grant further credit.

Escalating NPAs require a bank to make higher provisions for losses in their books. The banks set aside more funds to pay for anticipated future losses; and this, along with several structural issues, leads to low profitability. Profitability of a bank is measured by its Return on Assets (RoA), which is the ratio of the bank’s net profits to its net assets. Banks have witnessed a decline in their profitability in the last few years (Figure 2), making them vulnerable to adverse economic shocks and consequently putting consumer deposits at risk.

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What led to the rise in NPAs?

Some of the factors leading to the increased occurrence of NPAs are external, such as decreases in global commodity prices leading to slower exports. Some are more intrinsic to the Indian banking sector.

A lot of the loans currently classified as NPAs originated in the mid-2000s, at a time when the economy was booming and business outlook was very positive. Large corporations were granted loans for projects based on extrapolation of their recent growth and performance. With loans being available more easily than before, corporations grew highly leveraged, implying that most financing was through external borrowings rather than internal promoter equity. But as economic growth stagnated following the global financial crisis of 2008, the repayment capability of these corporations decreased. This contributed to what is now known as India’s Twin Balance Sheet problem, where both the banking sector (that gives loans) and the corporate sector (that takes and has to repay these loans) have come under financial stress.

When the project for which the loan was taken started underperforming, borrowers lost their capability of paying back the bank. The banks at this time took to the practice of ‘evergreening’, where fresh loans were given to some promoters to enable them to pay off their interest. This effectively pushed the recognition of these loans as non-performing to a later date, but did not address the root causes of their unprofitability.

Further, recently there have also been frauds of high magnitude that have contributed to rising NPAs. Although the size of frauds relative to the total volume of NPAs is relatively small, these frauds have been increasing, and there have been no instances of high profile fraudsters being penalised.

What is being done to address the problem of growing NPAs?

The measures taken to resolve and prevent NPAs can broadly be classified into two kinds – first, regulatory means of resolving NPAs per various laws (like the Insolvency and Bankruptcy Code), and second, remedial measures for banks prescribed and regulated by the RBI for internal restructuring of stressed assets.

The Insolvency and Bankruptcy Code (IBC) was enacted in May 2016 to provide a time-bound 180-day recovery process for insolvent accounts (where the borrowers are unable to pay their dues). Under the IBC, the creditors of these insolvent accounts, presided over by an insolvency professional, decide whether to restructure the loan, or to sell the defaulter’s assets to recover the outstanding amount. If a timely decision is not arrived at, the defaulter’s assets are liquidated. Proceedings under the IBC are adjudicated by the Debt Recovery Tribunal for personal insolvencies, and the National Company Law Tribunal (NCLT) for corporate insolvencies. 701 cases have been registered and 176 cases have been resolved as of March 2018 under the IBC.

What changed recently in the RBI’s guidelines to banks?

Over the years, the RBI has issued various guidelines aimed at the resolution of stressed assets of banks. These included introduction of certain schemes such as: (i) Strategic Debt Restructuring (which allowed banks to change the management of the defaulting company), and (ii) Joint Lenders’ Forum (where lenders evolved a resolution plan and voted on its implementation). In line with the enactment of the IBC, the RBI, through a circular in February 2018, substituted all the specific pre-existing guidelines with a simplified, generic, time-bound framework for the resolution of stressed assets.

In the revised framework which replaced the earlier schemes, the RBI put in place a strict deadline of 180 days during which a resolution plan must be implemented, failing which stressed assets must be referred to the NCLT under IBC within 15 days. The framework also introduced a provision for monitoring of one-day defaults, where incipient stress is identified and flagged immediately when repayments are overdue by a day.

Borrowers whose loans were tagged as NPAs before the release of the circular recently crossed the 180-day deadline for internal resolution by banks. Some of these borrowers, including various power producers and sugar mills, had appealed against the RBI guidelines in various High Courts. A two-judge bench of the Allahabad High Court had recently ruled in favour of the RBI’s powers to issue these guidelines, and refused to grant interim relief to power producers from being taken to the NCLT for bankruptcy. All lawsuits against the circular have currently been transferred to the Supreme Court, which has now issued an order to maintain status quo on the same. This means that these cases cannot be referred to the NCLT until the Supreme Court’s decision on the circular, although the RBI’s 180-day deadline has passed. This effectively provides interim relief to the errant borrowers who had moved to court till the next hearing of the apex court on this matter, which is scheduled for November 2018.

Recently, the Supreme Court collegium reiterated its recommendations for the appointment of 11 judges to certain High Courts.  It had first recommended these names earlier this year and in August last year, but these appointments were not made.  The Indian judiciary faces high vacancies across all levels (the Supreme Court, High Courts, and subordinate courts).  Vacancy of judges in courts is one of the reasons for delays and a rising number of pending cases, as there are not enough judges to hear and decide cases.  As of today, more than four crore cases are pending across all courts in India.   In this blog post, we discuss vacancies across courts over the years, delays in appointment of judges, and methods to determine the adequate judge strength required to handle the caseload courts face.

High vacancy of judges across courts

Vacancies in courts keep on arising periodically due to retirement, resignation, demise, or elevation of judges.  Over the years, the sanctioned strength of judges in both High Courts and subordinate courts has been increased gradually.  However, vacancies persist due to insufficient appointments (see Figures 1 and 2).  Between 2010 and 2020, vacancies increased from 18% to 21% across all levels of courts (from 6% to 12% in the Supreme Court, from 33% to 38% in High Courts, and from 18% to 20% in subordinate courts). 

Figure 1: Vacancy of judges in High Courts

Figure 2: Vacancy of judges in subordinate courts

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Sources: Court News 2010-2018; Vacancy Statement, and Rajya Sabha replies, Part I, Budget Session (2021), Department of Justice; PRS.

As on November 1, 2021, the Supreme Court had a vacancy of one judge (out of a sanctioned strength of 34).  Vacancy in High Courts stood at 37% (406 posts vacant out of a sanctioned strength of 1,098).  Since May, 2021, the Supreme Court collegium has recommended more than 130 names for appointment as High Court judges.  In three High Courts (Telangana, Patna, and Calcutta), at least half of the posts are vacant (see Figure 3).  The Standing Committee on Personnel, Public Grievances, Law and Justice (2020) noted that every year, 35-40% of posts of High Court judges remain unfilled. 

Figure 3: Vacancy of judges across High Courts (in %) (as on November 1, 2021)

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Source: Vacancy Statement, Department of Justice; PRS.

 

 

 

 

 

 

 

 

 

Appointments of High Court judges are guided by a memorandum of procedure.  As per this memorandum, the appointment process is to be initiated by the concerned High Court at least six months before a vacancy occurs.  However, the Standing Committee (2021) noted that this timeline is rarely adhered to by High Courts.  Further, in the final stage of the process, after receiving recommendations from the Supreme Court collegium, the executive appoints judges to the High Court.  No timeline is prescribed for this stage of the appointment process.  In 2018 and 2019, the average time taken to appoint High Court judges after receiving the collegium’s recommendations was five to seven months.

As of today, over 3.6 crore cases are pending before subordinate courts in India.  As on February 20, 2020, 21% posts for judges were vacant (5,146 posts out of the sanctioned strength of 24,018) in subordinate courts.  Subordinate courts in Bihar, Haryana, and Jharkhand (among the states with high population) had a high proportion of vacancies of judges (see Figure 4).  Note that the Supreme Court is monitoring the procedure for appointment of judges to subordinate courts.

For an analysis of the data on pendency and vacancies in the Indian judiciary, see here.

Figure 4: Vacancy of judges across subordinate courts (in %) (as on February 20, 2020)

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Source: Report No. 101, Standing Committee on Personnel, Public Grievances, Law and Justice (2020); PRS.

 

How many judges do we need?

The Law Commission of India (1987) had noted the importance of manpower planning for the judiciary.  Lack of adequate number of judges means a greater workload per judge.  Thus, it becomes essential to arrive at an optimal judge strength to deal with pending and new cases in courts.  Over the years, different methods of calculating the required judge strength for subordinate courts (where the backlog of cases in the Indian judiciary is concentrated) have been recommended (see Table 1). 

Table 1: Methods recommended for calculating the required number of judges for subordinate courts

Method of calculation

Recommendation and its status

Judge-to-population ratio: optimum number of judges per million population

The Law Commission of India (1987) had recommended increasing this ratio to 50 judges per million people.  This was reiterated by the Supreme Court (2001) and the Standing Committee on Home Affairs (2002).  For 2020, the judge-to-population ratio was 21 judges per million population.     Note that this figure is calculated based on the sanctioned strength of judges in the Supreme Court, High Courts and subordinate courts.

Rate of disposal: number of additional judges required (to clear the existing backlog of cases and ensure that new backlog is not created) based on the average number of cases disposed per judge

The Law Commission of India (2014) proposed this method.  It rejected the judge-to-population ratio method, observing that filing of cases per capita varies substantially across geographic units depending on socio-economic conditions.

Weighted case load method: calculating judge strength based on the disposal by judges, taking into account the nature and complexity of cases in local conditions

The National Court Management Systems Committee (NCMS) (2016) critiqued the rate of disposal method.     It proposed, as an interim measure, the weighted case load method, which addresses the existing backlog of cases as well as the new flow of cases every year in subordinate courts.     In 2017, the Supreme Court accepted this model.

Time-based weighted case load method: calculating the required judge strength taking into account the actual time spent by judges in different types of cases at varying stages based on an empirical study

Used widely in the United States, this was the long-term method recommended by the NCMS (2016) to assess the required judge strength for subordinate courts.  It involves determining the total number of ‘judicial hours’ required for disposing of the case load of each court.  The Delhi High Court used this approach in a pilot project (January 2017- December 2018) to calculate the ideal judge strength for disposing of pending cases in certain courts in Delhi.

Sources: Reports No. 120 (1987) and 245 (2014), Law Commission of India; Report No. 85, Standing Committee on Home Affairs (2002); Note for Calculating Required Judge Strength for Subordinate Courts, National Court Management Systems Committee (NCMS) (2016); Imtiyaz Ahmad vs. State of Uttar Pradesh, Supreme Court (2017); PRS.