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COVID-19 and non-performing loans


COVID-19 and non-performing loans


As a result of the COVID-19 pandemic, the economy has come to a sudden halt. This is likely to bring about high levels of non-performing loans (NPLs), i.e. loans that are in (or close to) default. High NPLs are problematic because they impair bank balance sheets, depress credit growth, and delay economic recovery (Aiyar et al. 2015, Kalemli-Ozcan et al. 2015). Persistently high NPL ratios were a concern in several European countries after the 2008-2012 crisis, and the COVID-19 pandemic could cause a re-emergence of the NPL problem.

High NPLs are a common feature of banking crises and tend to be studied around such events. Data presented in an existing report by Laeven and Valencia (2013) shows that NPL levels peak during crises, but more data are needed to understand how NPLs evolve and are resolved. Our recent ECB working paper (Ari et al., 2020) bridges this gap by presenting a new dataset on yearly NPL evolution during 88 banking crises since 1990. The dataset covers major regional and global crises (including the Nordic crisis, the Asian financial crisis, the Global Financial Crisis) and many standalone crises in developing, transition, and low-income economies. For each crisis, we report NPLs over an 11-year window around the crisis. What do we learn from these data?

Most banking crises lead to high NPLs

During crises, NPLs typically follow an inverse U-shaped pattern. They start at modest levels, rise rapidly around the start of the crisis, and peak some years afterwards, before stabilising and declining. Looking at all crises, we see that NPL levels peak at about 20% of total loans on average, but the variance is large (especially in developing countries, where NPLs can exceed 50% of total loans). Only less than a fifth of banking crises avoid high NPLs, which we define as NPLs exceeding 7% of total loans.

Anticipating future levels of NPLs is key for formulating NPL resolution strategies. It is tempting to use pre-crisis NPLs to anchor such forecasts. Yet, pre-crisis NPL levels are not a good indicator of post-crisis NPL problems. After a crisis, NPLs increase to three times their pre-crisis values on average, and over ten times in extreme cases (Figure 1).  

Figure 1 Peak non-performing loans during banking crises

a) Peak NPLs, percent

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b) Peak NPLs, multiples of pre-crisis

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Note: Reproduced from Ari, Chen, and Ratnovski (2020), Figure 4. The chart shows peak NPLs for 88 banking crises since 1990. The left panel shows peak NPLs expressed as percent of total loans; the right panel shows peak NPL ratio (i.e. NPLs/total loans) expressed as a multiple of the pre-crisis NPL ratio. Crises that did not have high NPLs (with NPLs under 7% of total loans) are shown in light blue in the left panel.

Timely NPL resolution is difficult, but essential for economic recovery

Countries can facilitate the resolution of high NPLs using a mix of policy measures, such as:

  • Asset quality reviews, to identify loans that are nonperforming and need restructuring
  • Separating good and bad assets of banks (so-called ‘good bank’-‘bad bank’ resolution). This makes the financial conditions of good banks more transparent, steadies their market access, and lets them focus on extending new lending. Bad banks, often structured as asset management companies, proceed to extracting value from bad assets
  • Recapitalising ‘good banks’, to ensure their lending capacity

More details on NPL resolution methods are provided in Balgova et al. (2016), Beck (2017), Brei et al. (2020), and in ECB Financial Stability Reviews by Grodzicki et al. (2015) and Fell et al. (2016 and 2017).

Despite the economic benefits of NPL reduction and the variety of methods available, the data paint a sobering picture of historic NPL resolution. While some countries resolve NPLs rapidly, a third of countries are saddled with NPLs for over seven years after a crisis. The NPL reduction outcomes after the Global Crisis are direr still: two-thirds of the countries that experienced high NPLs could not resolve those within seven years of the crisis (Figure 2). Strikingly, this also implies that while advanced economies tend to have lower post-crisis NPLs, they also take longer on average to resolve.

Figure 2 Mixed success in resolving non-performing loans after crises

a) Years required for NPL resolution

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b) Were NPLs resolved within 7 years?

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Note: Reproduced from Ari, Chen, and Ratnovski (2020), Figure 6. The left panel shows the number of countries that resolved NPLs (with NPL ratios to under 7%) in each year after the crisis. The right panel compares the number of counties that resolved and don’t resolve NPLs with 7 years. The colours distinguish the crisis waves and types.

In the paper, we use the ‘local projections’ method to assess the link between NPL resolution and post-crisis output dynamics, while controlling for their co-dependence. The results underscore that NPL resolution is critical for economic recovery. High and unresolved NPLs are associated with deeper recessions and slower recoveries. Six years after a banking crisis, output in countries that experience high NPLs is 6.5 percentage points lower in countries that don’t. Of the countries that have high NPLs, output in countries that do not resolve NPLs are more than ten percentage points lower than in countries that do (Figure 3).

Figure 3 Non-performing loans and economic recovery

a) The difference in GDP after the crisis between the countries that resolve high NPLs compared to those that don’t

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b) The difference in GDP after the crisis between the countries that experience high NPLs (within 7 years) compared to those that don’t

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Note: Reproduced from Ari, Chen, and Ratnovski (2020), Figure 6. The charts report the differences in output paths (expressed as percent of deviation from pre-crisis output between countries that, following a banking crisis, experience NPLs exceeding 7% compared to those that have NPLs under 7% (left panel), between countries that, having experienced NPLs exceeding 7%, manage to resolve them compared to those that do not (right panel).

NPL resolution in Europe after the 2008-2012 crisis

Further, we use a model selection approach to assess which pre-crisis indicators predict the dynamics of NPLs in banking crises. We document that peak NPLs are higher in countries with lower GDP per capita, after a credit boom, under fixed exchange rates, with less profitable banks, or banks with more fragile corporate balance sheets. NPL resolution is more protracted in similar circumstances, as well as in countries with high public debt and more sophisticated banking sectors. Interestingly, these high-level indicators have good predictive power (the average (pseudo) adjusted R-squared across the specifications is 0.24).

These results shed light on the factors behind the high, and persistent, NPLs in some European countries after the 2008-2012 crisis. In the paper, we compare actual NPL dynamics in seven European countries (Greece, Ireland, Italy, Portugal, Spain, Hungary, and Slovenia) with what could have been anticipated based on historical patterns. It turns out that high NPL levels in Europe in 2010s were hard to anticipate: the crisis was extraordinarily severe for advanced economies. By contrast, protracted NPL resolution was in line with historical patterns: it is common for crises that follow a credit boom (Figure 4). Indeed, the long-term negative consequences of credit booms are well-documented in the literature (Caballero et al. 2008). They are related to the difficulties in resolving the debt of non-viable ‘zombie’ firms and households that are ‘underwater’ on their housing assets.

Figure 4 Predicted versus actual non-performing loans in Europe

a) Peak NPLs, %

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b) Time to resolve NPLs, years

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Note: Reproduced from Ari, Chen, and Ratnovski (2020), Figure 7. The chart shows NPL metrics: actual (in green) and out-of-sample predicted (in blue), on average for a sample of European countries affected by the 2008-2012 crisis. The metrics of NPLs are: peak NPLs as percent of total loans (left panel) and the duration of NPL resolution in years (right panel).

What does this mean for NPL resolution after COVID-19?

Even though our paper studies NPLs in the context of banking crises, and therefore cannot be mapped perfectly to the COVID-19 events, it provides valuable insights into impending NPL challenges. Our results highlight forces that can make NPL resolution after the COVID-19 events different from the situation after the 2008-2012 crisis. Some forces are enabling of NPL resolution. For example, the COVID-19 pandemic is not a credit boom-induced crisis. If the economic downturn proves temporary, many post-COVID-19 NPLs may relate to viable illiquid firms, rather than unviable zombie firms. European banks have entered the COVID-19 pandemic with (on average) higher capital ratios compared to the 2008 crisis. The recently introduced IFRS-9 accounting standards may induce faster NPL recognition, and hence resolution, thanks to their forward-looking nature (although a ‘too fast’ NPL recognition may also constrain bank lending during downturns). Other forces point to challenges in NPL resolution. Compared to 2008, most European countries have substantially higher public debt, less profitable banks, and often weaker corporate sector conditions (the factors that historically have complicated NPL resolution). Moreover, if the economic recovery from the pandemic is slow and protracted, credit losses from corporate distress will rise and could overwhelm banks, further complicating NPL resolution. 

Given the importance of NPL reduction for economic recovery, and many countries’ historical difficulties in implementing effective NPL-related interventions, designing effective NPL resolution policies for the post-COVID-19 world is a key forward-looking financial policy issue for Europe today.

Editors’ note: This column first appeared as a Research Bulletin of the European Central Bank, and it is based on a paper entitled “The Dynamics of Non-Performing Loans During Banking Crises: A New Database”. The authors gratefully acknowledge the comments of Luc Laeven and Alberto Martin. The views expressed here are those of the authors and do not necessarily represent the views of the European Central Bank, the Eurosystem, or the IMF.


Aiyar, S, W Bergthaler, J M Garrido, A Ilyina, A Jobst, K Kang, D Kovtun, Y Liu, D Monaghan and M Moretti (2015), “A strategy for resolving Europe’s problem loans,” IMF Staff Discussion Note 15/19.

Ari, A, S Chen and L Ratnovski (2020), “The dynamics of non-performing loans during banking crises: a new database,” ECB Working Paper 2395

Balgova, M, M Nies and A Plekhanov (2016), “The economic impact of reducing non-performing loans,” EBRD Working Paper 193.

Beck, T (2017), “An asset management company for the Eurozone: Time to revive an old idea,” VoxEU.org, 24 April. 

Brei, M, L Gambacorta, M Lucchetta and B M Parigi (2020), “Bad bank resolutions and bank lending”, BIS Working Paper 837.

Caballero, R J, T Hoshi and A K Kashyap (2008), “Zombie lending and depressed restructuring in Japan”, American Economic Review 98(5): 1943-1977.

Grodzicki, M, D Laliotis, M Leber, R Martin, E O’Brien and P Zboromirsk (2015), “Resolving the legacy of non-performing exposures in euro area banks,” ECB Financial Stability Review, May.

Fell, J, M Grodzicki, R Martin and E O’Brien (2016), “Addressing market failures in the resolution of nonperforming loans in the euro area”, ECB Financial Stability Review, November.

Fell, J, C Moldovan and E O’Brien (2017), “Resolving non-performing loans: a role for securitisation and other financial structures?”, ECB Financial Stability Review, May.

Kalemli-Ozcan, S, L Laeven and D Moreno (2015), “Debt overhang, rollover risk and investment in Europe”, mimeo.

Laeven, L and F V Valencia (2013), “Systemic banking crises database,” IMF Economic Review 61(2): 225-270.

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