Environmental disclosure practice in the Serbian banking sector

This paper aims to: a) analyse the environmental disclosure practice in the Serbian banking sector, b) determine whether the degree of disclosure is higher in the case of big, i.e. systemically important banks, and c) examine if there is a positive relationship between the banks' CSR practice and their financial performance. The environmental disclosure index (EDI) based on 15 variables was employed to measure environmental disclosure performance for the Serbian banking industry. The data were generated through content analysis of the annual and sustainability reports of a total of 10 banks, five of which were classified as systemically important banks for the period 2015-2019. The sample was determined by the availability of reports for the analysed period and the bank establishment year. The results show that the majority of Serbian banks discloses their environmental policy (74%), the undertaken environmental activities with the local community (51%), and the utilization efficiency of water, energy, and paper (48%). Although the findings indicate that the environmental disclosure practice among all banks in Serbia is growing, the reports are not standardized. In addition, the systemically important banks in Serbia do not have a better disclosure practice. The econometric analysis implies that the bank's status does not influence the level of environmental disclosure and that there is no positive relationship between financial performance (ROA and ROE) and EDI. This study has implications for policymakers and accounting bodies in Serbia in standardizing non-financial reporting and creating certain green and sustainable banking guidelines.

Empirical results for expected credit losses of G-SIBs during COVID-19. The proof of the pudding is in the eating

This study examines the provision for credit losses and its disclosures for Global Systemically Important Banks (G-SIBs) in connection to the COVID-19 crisis. We find a profound difference in the increase of the provision for credit losses between banks that report under IFRS and US GAAP. For banks that report under US GAAP, the provision for credit losses more than doubles, while it increases by only 32 percent for banks that report under IFRS. This difference becomes even more striking when considering that the increase for IFRS-reporting banks is partly attributable to increased lending activities. This study further finds that European auditors are more likely to issue a Key Audit Matter (KAM), than auditors of US banks, and that these KAMs specifically relate to COVID-19 in the financial year 2020. Furthermore, IFRS-reporting banks disclose more information on expected credit losses than banks that report under US GAAP. Moreover, we find that European banks disclose relatively more information regarding the impact of COVID-19 than banks reporting under US GAAP.

Large US bank takeovers in 2008: performance and implications

PurposeBecause systemically important banks' takeovers in the US were expected to contain the 2008 global financial crisis (GFC) but were found to have imposed large cost on shareholders, this paper examines the effectiveness of these acquisitions during the GFC and investigates what went wrong with the market for corporate control of large banks.Design/methodology/approachThis paper presents a model of the disciplinary takeover based on the efficient market hypothesis which provides appropriate measures for it to examine the financial performance of acquiring banks after takeover.FindingsThe results indicate that the takeover market for large banks was ineffective in two aspects: the market did not distinguish strong banks from weak banks before the crisis and acquirers performed worse after takeover. Such ineffectiveness reflects the fundamental deficiencies of large bank takeovers arising from some key distinguishing characteristics of large banks.Research limitations/implicationsThe sample size of systemically important banks' takeovers is small so large-sample standard statistical inferences cannot be used.Practical implicationsThe deficiencies of large bank takeovers need to be rectified in order to aid in resolving future crises.Originality/valueThis paper provides rare and detailed insight based on case studies of large US bank takeovers during the GFC.

THE IMPACT OF BASEL III ON THE RUSSIAN BANKING SYSTEM

Currently, the issue of banking regulation is one of the most urgent due to the fact that the destabilization of this area can threaten the financial stability of the entire country. The Basel Agreements use common approaches to the capital of banks in different countries, they are formulated taking into account possible risks and the presence of systemically important banks. The article analyzes the impact of the Basel III standards on the banking system and assesses the impact of these standards on the development of the banking system.

Exploring the sources of loan default clustering using survival analysis with frailty

This paper investigates whether three microeconomic loan characteristics are sources of loan default clustering in the Mexican banking sector by employing survival analysis with frailty. Using a large sample of bank loan level data granted to micro, small and medium sized firms from January 2010 to 2018, we test whether classifying loans by the bank's systemic importance, industry or at individual firm level enhances the predictions of loans defaults. Our results show that loans granted by Domestic Systemically Important Banks contribute to the default clustering in micro and small firm loans. This is due to aggregate default rate levels and clusters that are large for these firms loans compared with loans provided to medium-sized firms. These findings have important implications for bank's expected loss management related to the correlated loan default risk

Research on Financial Systemic Risk in ASEAN Region

The research of financial systemic risk is an important issue, however the research on the financial systemic risk in ASEAN region lacks. This paper uses the minimum density method to calculate the interbank network of ASEAN countries and uses the node centrality to judge the systemically important banks of various countries. Then the DebtRank algorithm is constructed to calculate the systemic risk value based on the interbank network. By comparing the systemic risk values obtained through the initial impact on the system important banks and non-important banks, we find that the systemic risk tends to reach the peak in the case of the initial impact on the system important banks. Furthermore, it is found that countries with high intermediary centrality and closeness centrality have higher systemic risk. It suggests that the regulatory authorities should implement legal supervision, strict supervision, and comprehensive supervision for key risk areas and weak links.

Systemic risk measurement: bucketing global systemically important banks

The general consensus on the need to enhance the resilience of the financial system has led to the imposition of higher capital requirements for certain institutions, supposedly based on their contribution to systemic risk. Global Systemically Important Banks (G-SIBs) are divided into buckets based on their required additional capital buffers ranging from 1% to 3.5%. We measure the marginal contribution to systemic risk of 26 G-SIBs using the Distressed Insurance Premium methodology proposed by Huang et al. (J Bank Financ 33:2036–2049, 2009) and examine ranking consistency with that using the SRISK of Acharya et al. (Am Econ Rev 102:59–64, 2012). We then compare the bucketing using the two academic approaches and supervisory buckets. Because it leads to capital surcharges, bucketing should be consistent, irrespective of methodology. Instead, discrepancies in the allocation between buckets emerge and this suggests the complementary use of other methodologies.

Identification of systemically important banks in India using SRISK

Purpose Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019. Design/methodology/approach In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk. Findings This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank. Originality/value Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.