Z-ing in the right direction? A closer look at the European banking system's stability

If there is one measure that we can trust to give us an overall risk situation of the banking operations, arguably it’d be the z-score. Primarily, it is because its calculation reflects profit and equity rather than just loan book items. In this short blog, we will try to cover the basic premise of the concept at the micro level. Can it give us a larger picture of an economy’s banking system? And finally, what insights can we obtain by observing the z-score of European banks before and after the global pandemic?

So let’s dive in!

At its core, a z-score predicts the probability of bankruptcy, where a high score generally means fewer chances of being insolvent. Prof. Altman published it in his famous paper in 1968. Since then, z-score has been used extensively not only by academics; but also by practitioners, analysts, and regulators. In his recent paper, Prof. Altman has defined some of the applications given in the table below ¹:

As far as banks are concerned, we use a slightly modified version of the original z-score.

where \(ROA\) is the return on assets, \(LR\) is the leverage ratio measured as a fraction of equity and assets, and \(\sigma(ROA)\) is the standard deviation of return on assets. Just by looking at the formula, we can develop intuition. A z-score objectively measures the bank’s ability to counter risk by using a ratio of its profits and equity to every unit of volatility. Therefore, the greater the number, the higher is resistance toward risk shocks.

Moving on to our next objective, which is to define what z-score could mean at the macro level. At the risk of overgeneralizing, if we take aggregate values of equity, assets, and profits, we can easily end up with a z-score of an industry or in our case, banking systems. What risks do we have in doing so? We might mask the variations present within a country’s banking system. For example, the ratios of small banks may differ from those of big banks in magnitude. That means a higher ratio may be misleading. Since it does not reveal what kind of risks encompass a particular group of banks within an economy. But to obtain a wide perspective and see what aggregation entails, let’s ignore these issues for a moment. This may lead us towards benchmarking for comparison of different states.

If we were to take the formula above, we can easily translate its meaning to the macro level. A commercial banking system’s z-score, as per World Bank’s definition, “captures the probability of default of a country’s banking system. Z-score compares the buffer of a country’s banking system (capitalization and returns) with the volatility of those returns.”

Even though it is quite difficult to objectively measure the true impact of the global pandemic on financial institutions, we can safely assume that banks had their work cut out as well. Be it digital payments, bailouts, or facilitation of day-to-day operations. In addition, reduced economic activity and higher credit risk for loans did not make their life easy. If we take the z-score as our parameter, we can observe an interesting fact from the graph below.

Note: Code for the above graph can be found at my Github repository. Data has been taken from Global Financial Database

Apart from Turkey and Poland, we do not observe any significant fall in the score after the worst crisis our financial markets have seen in the last 100 years. Even in the case of these two countries, the score is still above the benchmark, thus not raising any alarms. We can also observe that economies were able to improve their score. Let us now compare these scores with those of the US and the UK. We can see a similar trend. The US achieved a z-score of 31.1 in 2021 from 30.3 in 2020, whereas the UK had 18.1 in 2021, versus 17.6 in 2020.

But how were scores improved even though our financial markets faced a once-in-a-lifetime crisis? We can attribute this to several factors: governments, central banks, and/or decent coordination among financial institutions, supportive regulatory measures, strong capital levels, and good asset quality. Similarly, the decline could be attributed to the lack of these elements.

This blog was just an attempt to provide some instincts. For analyzing a commercial banking system, we cannot just rely on an overall z-score. Instead, we have to take it in conjunction with other risk measures and variables such as service structure, digitalization, ease of access, etc. In addition, even though financial markets in most European economies have weathered the storm in terms of navigating the crisis, financial stability needs constant monitoring from all sides.

We all know the advantage the EU region has over other economies in terms of having connected markets. But, there is always some risk involved in such systems, as the financial crisis in one country can have ripple effects throughout the region.

Disclaimer: All views are personal and do not represent those of any institution.