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This paper aims to examine the relationship between board structure and risk-taking, exploring how this association is influenced by advanced technologies in the banking sector.

This study uses a panel sample of 22 Pakistani banks from 2011 to 2018. To test the authors’ hypothesis, the authors use regression analysis with two-way cluster robust standard errors. Further, the authors also check the robustness of the authors’ findings using alternate proxies of board structure and bank risk-taking behavior. To address endogeneity concerns, the authors use the two-stage least square technique.

In the era of the Fourth Industrial Revolution, Pakistani banks’ digitalization is modeled by the presence of Temenos-T24/Oracle as their core banking system (software providing end-to-end operational integration). Its interactional effect with corporate governance is evaluated to implicate informed risk-taking by the board as a result of improved information access and analysis. The authors find that board size has a positive association with risk-taking, and the use of modern technology reshapes this association in the banking sector.

The contribution of this paper is twofold. First, the impact of board structure on bank risk-taking has not been extensively researched in Pakistan – a highly volatile and unpredictable economy. Second, the evaluation of the role of technology on bank risk is being researched for the very first time – a uniqueness of this paper.

Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between savers and borrowers, these institutions operate in a dynamic and complex environment characterised by various risk factors that can significantly impact their profitability and overall stability. Understanding the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability is crucial for effective risk management strategies and the development of appropriate regulatory frameworks.

Purpose: Commercial banks play a critical role in the global economy by facilitating economic growth and providing financial services. This study examines the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability in commercial banking.

Methodology: The sample consists of licenced scheduled commercial banks on the Bombay Stock Exchange (BSE) from 2015 to 2022. Using the Smart PLS-SEM 3.0 path analysis technique, the study evaluates the combined influence of these risk factors on profitability and provides evidence-based recommendations for risk management strategies.

Findings: The findings can assist banks in enhancing their risk management practices, and regulators in developing appropriate regulatory frameworks. By understanding the key risk factors and their impact on profitability, banks and regulators can mitigate risks, enhance transparency, and promote stability within the banking sector.

Significance/value: The value of this study lies in its focus on the interconnectedness of risk factors, profitability, and the potential implications for decision-making, risk management strategies, regulatory frameworks, and the overall stability of the commercial banking sector.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.