Financial Risk Management in Banking

Evidence from Asia Pacific

Shahsuzan Zakaria, Sardar Islam

• Publisher: Routledge
• Year: 2019
• ISBN:
  9780429758645
• Edition: 1
• Topic: Economics
• Subtopic: Banks & Banking
• Index: Economics

As risk-taking is an essential part of the banking industry, banks must practise efficient risk management to ensure survival in uncertain financial climates. Banking operations are specifically affected by fluctuations in interest rates which cause financial imbalance; thus banks are now required to put in place an effective management structure that incorporates risk management efficiency measures that help mitigate the wide range of risks they face.

In this book, the authors have developed a new modelling approach to determine banks' financial risk management by offering detailed insights into the integrated approach of dollar-offset ratio and Data Envelopment Analysis (DEA), based on derivatives usage. It further analyses the efficiency measurement under stochastic DEA approaches, namely (i) Bootstrap DEA (BDEA), (ii) Sensitivity Analysis and (iii) Chance-Constrained DEA (CCDEA). As demonstrated in the modelling exercise, this integrated approach can be applied to other cases that require risk management efficiency measurement strategies.

Additionally, this is the first book to comprehensively review the derivative markets of both the developed and developing countries in the Asia-Pacific region, by examining the differences of risk management efficiency of the banking institutions in these countries.

Based on this measurement approach, strategies are provided for banks to improve their strategic risk management practices, as well as to reduce the impacts from external risks, such as changes in interest rates and exchange rates. Furthermore, this book will help banks to keep abreast of recent developments in the field of efficiency studies in management accounting, specifically in relation to hedge accounting, used by banks in the Asia-Pacific region.

1 Introduction

1.1 Background of the study

Firms and businesses operate in a constantly changing and risky environment that is unpredictable, volatile and complex. Efficient risk management strategies that are effective in terms of costs and resources are becoming increasingly important to the success of any business (Lam 2014; Power 2004), with the measurement and analysis of risk management efficiency being crucial for the survival of all business activities, both domestically and internationally. In spite of the availability of guidelines for firms to make financial decisions, Scholtens and Wensveen (2000) maintain that the most important rationale for financial risk management is to protect company balance sheets against severe monetary losses. These include operational cash flows against serious financial market uncertainties such as credit risks-and interest, as well as exchange rate fluctuations. For instance, in the United States of America (USA), the traditional business of banks has declined dramatically, and commercial banks have turned their main activities to fee-producing businesses, with the charging of fees as their main source of profit (Li and Yu 2010; Allen and Santomero 2001).

This new direction in the financial market has led firms to materialise various risk management strategies including insurance, derivative usage and diversification. These strategies are designed to achieve effective corporate risk management. Nowadays, derivatives, as a risk hedging tool, have become prominent particularly in financial institutions. Technological advances in financial innovation together with the creation of financial derivatives have served as risk reduction tools for managers of financial institutions in many developed countries. These scenarios encourage firms to position their businesses and improve their efficiency in risk management. Hence, the quantification of efficiency in risk management will assist in value creation and prevent the occurrence of any adverse events that might not have been properly considered in the relevant business scenario. In times of uncertainty and global economic turmoil, the role of risk management as a leverage for business management and operations becomes more crucial (Grote 2015; Schroeck 2002). The context of risk management, with clearly defined objectives by corporate management, becomes a key tool for supporting decision-making processes at strategic and tactical levels. The same concept applies to banking operations where risk arises from inaccurate business decisions. Therefore, appropriate risk management efficiency measurements in banks can substantially contribute to the implementation of activities, which are aimed at reducing possible future liabilities. Pastor (1999) points out that risk management efficiency measures are important for avoiding poor risk management and increased competition in financial markets. Thus, as far as the risk management of a firm is concerned, it is essential to develop a new method for measuring risk management efficiency. This implies the necessity of having robust measurements of risk management in financial institutions.

Furthermore, the findings of limited studies have demonstrated the impact of derivatives usage in risk management efficiency of financial institutions using a good measurement approach. For example, Rivas et al. (2006) found no clear implications of derivative items on the efficiency of banks’ risk management. In addition, their discussions on the use of a Data Envelopment Analysis (DEA) approach failed to examine the technical aspects and roles of derivatives in controlling market risk and measuring risk management efficiency using derivatives-based inputs and outputs. These two points are of particular interest in commercial banks in relation to the efficiency of risk management in developing and emerging market economies (EMEs), particularly in the Asia-Pacific region (Au Yong et al. 2009). More importantly, when firms or banks are tied up with a derivative instrument transaction, they cannot escape from the concept of hedge accounting and hedge effectiveness. Therefore, an investigation into a hedge effectiveness test used in hedge accounting for risk management efficiency is needed. Furthermore, the assessment of financial risk in banks from fluctuations in interest rates through hedging by accounting treatment has implications whereby an accounting risk can create unreliable information.

This study fills the above research gap through an empirical investigation and analysis of banks’ risk management efficiency based on the usage of derivative instruments in developed and developing financial markets in the Asia-Pacific region. The measurement and development of a model for financial risk management efficiency measures in banks was carried out using an integration of dollar-offset ratio and DEA approach. Other hedging effectiveness tests were not included, as these methods may have added difficulties in appropriately matching with the fundamental concept of a DEA approach. Moreover, as the use of a six-year data test would yield a better and more accurate dataset, the measurement of relative risk management efficiency involved 21 commercial banks covering the period from 2007 to 2012. The 21 banks selected are from Asia-Pacific countries, of which 6 are developed countries (Australia, Hong Kong, Japan, New Zealand, Singapore and Taiwan) and 3 are developing countries (Malaysia, the Philippines and Thailand). The period from 2007 to 2012 will also reflect a fair view of the institutions’ overall performance during the financial crisis. In particular, this study seeks to address the following questions:

1. What is the need and significance of risk management efficiency measures and analysis?
2. How can the impact of derivatives be shown through hedge effectiveness in order to measure the efficiency of risk management in banks?
3. How can risk management efficiency be operationalised using a DEA that incorporates hedge accounting based on a hedge effectiveness test?
4. Are derivatives more efficient in managing risk in developed countries in comparison with developing countries in the Asia-Pacific region?
5. Does modelling risk (uncertainty or risk in modelling) in the measurement of risk management efficiency influence banks’ risk management efficiency and its measurements? If yes, how and why?
6. How do deterministic and stochastic efficiency scores influence banks’ risk management and derivative policies in developed and developing countries?

This chapter is structured as follows: Section 1.2 presents the general concept of risk in the banking environment. Section 1.3 presents the overview of the general risk management perspective, and Section 1.4 discusses efficiency in risk management and its measurement. It explains the hedge accounting used to measure efficiency in risk management via hedge effectiveness analysis, and compares the dollar-offset ratio with other tests. In this section, the integrated approach used in this book to measure banks’ risk management efficiency incorporating DEA method in hedge accounting is presented. Section 1.5 emphasises the relationship between derivatives usage and risk management in commercial banks. Section 1.6 reviews the use of derivative instruments in emerging (developing) markets. Section 1.7 discusses the limitations of existing literature and the motivations for this study. The objectives of this study are stated in Section 1.8, while Section 1.9 presents the research design and planning which consists of the conceptual framework, methodology and empirical framework in the research approach, methodologies of efficiency evaluation, research phase and the proposed DEA approach to hedge accounting. Section 1.10 highlights the contribution and significance of the study (in both academic and practical applications), and lastly, Section 1.11 outlines the organisation of this book.

1.2 Risk

Risk in banking organisations refers to uncertainties resulting in adverse impacts on profitability that can lead to outright losses. According to Omar et al. (2014), McNeil et al. (2010) and Bessis (2002), the concept of risk in a banking environment has shifted from the traditional qualitative risk assessment to quantitative management. Evolution of risk practices, supervisory systems and regulatory incentives have changed the definition of risk. Due to the uncertainties of global market forces and financial movements, there is now an increased potential for an adverse effect on banks’ profitability. Therefore, the ability of banks to manage risk directly impacts on their financial performance. For instance, due to the outbreak of the Asian financial crisis, lending growth had been curtailed and tight credit standards imposed. These actions had been taken in order to avoid debt crises that could reduce banks’ profits.

As shown by Bessis (2002), credit and interest rates are the two main risks faced by banks. Both types of risk are potentially major sources of losses, and either one may cause clients to fail to comply with their obligations to repay debts and interest charged. Other types of risk faced by banks include liquidity, operational, foreign exchange (FX) and the country in which the banks operate. Because banks understand the adverse impact of risk and the importance of downsizing risk, they tend to focus risk management and strategies by identifying the key drivers that determine and control risk, particularly in terms of financial loss (Kupper 2000).

1.3 Risk management

In most financial institutions, risks are actively managed, and by utilising a variety of financial instruments, traders and risk managers are capable of protecting asset value and firms’ financial performance (Ong 2006). Gup and Kolari (2005) noted that futures, options and swaps are the three most common financial instruments used by multinational transaction companies to reduce market risks. The use of these instruments guides banks in the effective and efficient management of risk at all levels in uncertain markets.

1.4 Efficiency in risk management and its measurement

Measurement of a financial risk management tool is essential to ensure its efficiency in contributing to risk management for corporate resilience. According to Fernando and Nimal (2014), efficiency and risk management are basic requirements for measuring risk management efficiency of banks as a decision-making unit (DMU). Despite increasing global market uncertainties, both strategic and operational practices need risk management efficiency measurements to achieve efficiency levels.

1.4.1 Hedge accounting used to measure efficiency in risk management via hedge effectiveness analysis – comparison of dollar-offset ratio with other effectiveness tests

In accordance with International Accounting Standards (IAS 39), companies should perform retrospective and prospective assessments to ensure that as in the past reporting periods, the relationship between hedging instruments and hedged items will remain effective in the future as well. Hedge effectiveness is usually measured by using a number of specific methods including critical analysis (critical terms), correlation analysis and dollar-offset (ratio analysis). Under retrospective hedge effectiveness, Charnes et al. (2003) agree that the dollar-offset ratio is the most effective measure for hedge effectiveness testing. Here, the degree of confidence for hedge effectiveness (highly effective) is considered to be within the range of 80–125%. The effectiveness range shows a direct comparison between the hedging instrument and hedged item, and if the measure falls outside this range, companies should reconsider their derivative hedge strategy.

Compared to the application of other hedge effectiveness tests (Chapter 3, Section 3.3.1), the assessment of hedge effectiveness using dollar-offset ratio is much simpler (Hailer and Rump 2005; Finnerty and Grant 2003). This is because regression and statistical analyses require appropriate interpretations and understandings of statistical inferences, whereas the dollar-offset ratio allows a more direct analysis of price levels rather than changes in prices where both are exhibiting highly correlated price changes.¹ In this case, the dollar-offset method is significantly capable of measuring the effectiveness of a hedging instrument and hedged item, and hence can be used as a basis for testing a firm’s risk management efficiency. The dollar-offset ratio is also preferable to regression analysis (Kawaller 2002), another method commonly used to determine the behaviour of the hedging relationship based on historical market rates through the linear equation.

Using the dollar-offset ratio approach, hedge effectiveness is able to determine whether changes in the fair value of the hedging instrument and hedged items attributable to a particular risk (e.g. interest rate risk or FX risk) have been highly correlated in the past, thus helping to ascertain whether the relationship will have a high degree of correlation in the future. Conversely, by using the more lengthy regression analysis, the R-squared value is lowered, with the likelihood of failure in the effectiveness test on hedging being increased due to the value of R-squared not being reliable. For this reason, further analysis using F-statistic and t-statistic is needed to determine whether the regression is statistically significant or otherwise, in determining the level of hedging effectiveness.

Another test is the volatility risk reduction (VRR) method² used to analyse effectiveness of the hedge structure by comparing the position of the hedging instrument and hedged item with the risk of the hedged item. Ramirez (2007, 25) documents that VRR approach comparatively investigates “how small the combined position of risk is relative to the hedged item risk”. However, Finnerty and Grant (2003) warn that firms using the VRR method need to be aware that this test statistic is highly sensitive to observations and reflects overly small changes in value.

In comparing the dollar-offset ratio with other available methods, despite the superiority of the former, McCarroll and Khatri (2014) and Bunea-Bontaş (2012) argue that it is inappropriate due to its limited range of 80–125%, which fails to show adequate relationships between risk management and firm performance. As a result, they found that there have been many arbitrary discontinuations in hedging. In addition, many investors have had difficulties in understanding the outcome of effectiveness testing, particularly due to the unpredictable results when using the limited percentage range as a requirement of effectiveness assessment. This is because investment decisions are difficult when these measurements have been unable to prove the effectiveness of using hedging instruments to reduce the presence of risk in the hedged item. Referring to the IFRS (International Financial Reporting Standards) Financial Instruments (replacement of IAS 39) Phase III, the Hedge Accounting Exposure Draft and Comment Letters of February 2010, Seerden (2010) highlights the difficulty of determining relationships between hedge effectiveness and risk management. He recommends that hedging principles need to be developed based on the effectiveness assessments, but with closer relationships to risk management activities in order to achieve an offsetting concept in fair value that fits accounting purposes.

1.4.2 Integrated approach using hedge accounting and DEA

In measuring banks’ risk management efficiency, this study proposes to integrate the dollar-offset ratio hedge accounting concept with the non-parametric approach (DEA) that has been used extensively to measure firm performance (efficiency). Due to the limitations of the simple ratio analysis applied in the dollar-offset ratio, DEA is incorporated to accomplish an advanced analysis of the impact of hedging instrument usage on the hedged item. This approach is particularly seen in the banking sector where performance takes into account the hedging instrument (interest rate swap) and the hedged item implication.

The dollar-offset ratio has been chosen as the most suitable method for the hedge effectiveness test in this book due to its theoretical links with the evaluation of efficiency when using a DEA approach that considers multiple outputs to the input ratio. This method is expected to be extremely useful in adequately measuring the risk profile of the traditional performance of banks in the Asia-Pacific region (Greuning and Bratanovic 1999), particularly when the ratio analysis is used with a large number of different units of analysis. In this way, DEA will be able to assign mathematical weights to all inputs and outputs in which “ratio analysis relies on the preferences of policy makers in assigning weights” (Nyhan and Martin 1999, 354), while making simultaneous comparisons of multiple dependent performance measures including output, outcome and quality.

1.5 Derivatives and its relationship with risk management in commercial banks

The use of financial instruments or derivatives as risk management weapons to draw inference on the current situation warrants that firms achieve competitive advantage (Triantis 2000; Clarke and Varma 1999).

As derivatives are extensively traded in developed marke...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• List of figures
• List of tables
• List of abbreviations
• Preface and summary
• Acknowledgements
• 1 Introduction
• 2 Literature review – relationship between derivatives and risk management and the concept of risk management efficiency and its measurement
• 3 Risk management efficiency measurement and analysis – an alternative measure based on hedge accounting
• 4 An alternative methodology for risk management efficiency measurement and analysis using DEA approach with ratio analysis based on hedge accounting
• 5 Risk management efficiency measurement and analysis under uncertainty
• 6 Research summary and conclusion
• References
• Index