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Quality comes cheap: Evidence from auditing in Islamic banks

Quality comes cheap: Evidence from auditing in Islamic banks In this paper, we examine the audit market in Islamic banks, focusing on the pricing of audit services. To our knowledge, academic research has not yet examined the role of external auditors in Islamic banking. We argue that significant differences between Islamic and conventional banks, most notably in terms of activities allowed, corporate governance structure and ethical aspects of the business model, may lead to different audit outcomes. We find a fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. This result is in line with the view that the risks borne by auditors are lower in Islamic banks than in conventional banks. In addition, we document that the fee discount for Islamic banks is lower if auditors have higher expertise in Islamic banking. On the other hand, we do not observe significant differences in audit quality between Islamic and conventional banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost for the quality of audit services. Electronic copy available at: https://ssrn.com/abstract=3845365 1. Introduction Islamic banking is an important feature of the Gulf Cooperation Council (GCC), the South- East Asian and the Middle East regions, wherein it enhances financial development and economic welfare (Abedifar et al., 2016). On a global scale, it is estimated at $2.44 trillion of total assets under management (IFSB, 2020), while in certain countries it accounts for over one-third of the total banking assets. Sustained year-on-year double-digit growth rates have been largely unaffected by a series of economic events including the 2008 global financial crisis, geopolitical tensions, the 2015 oil price drop and depreciations of local currencies to the US dollar (IFSB, 2020). The economic and financial implications pertaining to the Covid-19 pandemic may take years to unfold fully. Yet with recent forecasts suggesting that the impact will be harsher on the advanced economies compared to the emerging markets and developing economies (-8.0% vs -3.0% real GDP growth rate), it may be expected that the Islamic banking would weather this crisis (IMF, 2020). The ethical character of Islamic banks is rooted in the religious underpinnings that govern their business model. Working within strict rules of allowable financial products and practices, Islamic banks have prioritised social values long before conventional banks shifted from a “shareholders only” approach towards embracing corporate social responsibility doctrines (Platonova et al., 2018). Debt interest payments, complex derivatives, short-selling and speculation, although highly desirable for shareholder value maximisation have been linked to social injustice and economic instability and are thus precluded from Islamic banking practices. Likewise, Islamic banks refrain from investments in largely deemed unethical businesses using business type and financial criteria (e.g., tobacco, alcohol, leverage, tangibility); a meritorious practice that predates the recent rise of ethical, environmental, sustainable, faith-based as well as social and responsible investments (EUROSIF, 2014) in light of financial crises (e.g., dotcom bubble, 2008 global financial crisis) and accounting scandals Electronic copy available at: https://ssrn.com/abstract=3845365 (e.g., Enron). To mobilise funds, Islamic banks promote the concept of risk-sharing, which inspires responsible behaviour and mitigates moral hazard (Al-Suhaibani & Naifar, 2014; Baele et al., 2014). Most countries with Islamic banks operate a dual-banking system with the ultimate choice falling to the investor. The expectation is that investors in Muslim dominated countries would show a higher propensity to the former; indeed, investors in Saudi Arabia welcome the use of Islamic bank financing by listed firms (Almansour & Ongena, 2018). The growth and the resilience of the sector have spurred interest from academics and practitioners, with a sizeable literature on the comparative performance across a multitude of aspects, such as financial risk, profitability and efficiency to name but a few (see Section 2 for a focused review). However, and to the best of our knowledge, academic research has not yet examined the audit market in Islamic banking, despite the importance of auditing in resource allocation and contracting efficiency (DeFond & Zhang, 2014). Besides, it is important to investigate auditing in Islamic banks because of their prominent status in many countries, and their significant differences in terms of financial products and practices, corporate governance structure and ethical considerations. Our paper examines the audit market in Islamic banks. We focus on the pricing and the quality of audit services. First, we examine whether Islamic banks are charged different audit fees compared to their conventional counterparts. Second, we test whether the expertise of auditors in Islamic banking affects the fees that are charged to their clients. Third, we test whether the audit fee differences may be driven by reductions in audit quality, instead of reflecting a differentiated risk profile between banks. We use hand-collected audit data from annual reports for a total of 71 banks operating in Malaysia over the 2010-2017 period. We opt for a single country case study to eliminate heterogeneity in Islamic banking operations that is typical in cross-country designs as argued Electronic copy available at: https://ssrn.com/abstract=3845365 in Alexakis et al. 2019. This heterogeneity may be attributed to differences within the Islamic banking model itself (e.g., permissibility of particular financial products and lines of businesses) or regulatory/supervisory differences manifested across countries (Song & Oosthuizen, 2014). We opt for Malaysia because it is perhaps the most active in promoting Islamic finance, while consistently being one of the big four players therein (alongside Saudi Arabia, UAE and Kuwait) (IFSB, 2020). Our main empirical model is in line with the audit fee literature in the financial industry, see Cullen et al. (2018) and Fields et al. (2004). For robustness purposes we also adopt an alternative model that considers the well-documented differences between the two bank types, most notably financial stability (proxied by the z- score) and technical efficiency (estimated via a stochastic frontier analysis). We find that audit fees are substantially lower in Islamic banks than in conventional banks. Specifically, we document a fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. In addition, our results show that the fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. The results are in line with the view that auditors bear lower risk in Islamic banks than in conventional banks. Lower audit risk can be explained by lower credit and default risk; lower audit risk can also be due to the presence of an additional control on managers, which is imposed by the Shariah Supervisory Board. Although fees are lower in Islamic than in conventional banks, we find no significant differences in audit quality, which we measure through the discretionary loan loss provision, the likelihood of meeting or Single country studies within the Islamic and conventional banking comparative literature are not scarce (Abdul- Majid et al., 2011; Asmild et al., 2019; El-Gamal & Inanoglu, 2005). In particular, the Malaysian Securities Exchange Commission (SEC) has allowed higher percentages of non- permissible income for Islamic investments, in an attempt to boost the investible universe of Shariah -compliant stocks. Additionally, Islamic banks operating in Malaysia adopt financial instruments, whose Shariah conformity has been challenged in the Middle-East and as a consequence these are not valid for use therein. For example, Bai Bithaman Ajil (BBA) that is utilised as a buy-sale property instrument, are not considered Shariah-compliant in the Middle-East (Usmani, 2002). Electronic copy available at: https://ssrn.com/abstract=3845365 beating earnings benchmarks and restatements, between the two types of banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost in the quality of audit services. We contribute to the literature in two ways. First, in contribution to the Islamic/conventional comparative literature (Abedifar et al., 2013; Baele et al., 2014; Izzeldin et al., 2021; Quttainah et al., 2013), we offer the first study to examine the audit market – in particular, the pricing and quality of audit services – between these two bank types. Second, in contribution to the banking audit literature we compare the audit market dynamics across different banking models. Further, we investigate how the expertise of auditors in Islamic banking affects the audit outcomes. Extant research (Cullen et al., 2018; Doogar et al., 2015; Ettredge et al., 2014; Fields et al., 2004; Kanagaretnam et al., 2010, 2011; Masli et al., 2018) has largely focused on the commercial banking model, with alternative banking models (i.e., Islamic banks, community banks) being under researched. The rest of the paper is structured as follows. Section 2 discusses the motivation of the analysis; Section 3 presents the data and methods used; Section 4 comments on the results; Section 5 concludes. 2. Background information and hypothesis development Background information Islamic banking refers to these financial institutions where practices emanating from the Islamic law (Shariah) are accommodated into the business model (Haniffa & Hudaib, 2007). The prohibition of interest and speculative activities, the shunning of investments in industries that are considered unlawful – alcohol, gambling and tobacco to name but a few – as well as investments in complex derivative products, debt instruments and short-selling are some of the Relatedly, general surveys of the literature on the determinants of audit quality and audit fees are contained in DeFond and Zhang (2014) and Hay et al. (2006), respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 most acknowledged restrictions. Consequently, Islamic banks use two types of financial products: equity/participation type and fee-based services. Mudarabah is a commonly used equity/participation type of contract where an investor (usually an Islamic bank) and an entrepreneur (individual or institutional) enter a joint venture with the bank providing the necessary funds, the entrepreneur the know-how, and they agree to share the profits on a pre- determined ratio. Fee-based services include the widely used contracts of Murabahah and Ijarah. Murabahah is in essence a cost-plus-profit sale. The bank arranges to sell a good to a customer at a premium which incorporates risks, costs and a profit margin. Ijarah is a lease contract where the bank leases an asset to an investor (or consumer) and the latter pays fees for utilising the asset. Nevertheless, Islamic banking is itself a topic of great ambiguity. Proponents argue that its unique features and restrictions create a new financial paradigm and enhance ethical investing. Critics argue that the differences between the theoretically envisaged Islamic banking model, and what is typically practiced are substantial; thus Islamic finance is simply conventional finance with Arabic names (Khan, 2010). To their defence they posit that the cornerstone of Islamic finance is equity participation, with profits and losses shared between the contracted parties according to some pre-determined ratio (Usmani, 2002). Yet, equity financing constitutes a small percentage of a typical Islamic bank’s asset portfolio (El-Gamal, 2006; Khan, 2010). Instead, fee-based financial products are the norm, where an “implicit” interest rate is charged that is often highly correlated with the “explicit” interest rate observed in the conventional banking sector. Documented evidence suggest that Islamic banking activities are influenced by the prevailing interest rate in Turkey and Malaysia but not in the GCC countries (Cevik & Charap, 2015; Ergeç & Arslan, 2013; Yusof et al., 2015). Moreover, recent evidence suggests a convergence between the two banking paradigms, notably in countries with high financial development (Izzeldin et al., 2021). Electronic copy available at: https://ssrn.com/abstract=3845365 Despite their restrictions and business model peculiarities, Islamic banks are considered more profitable (Alqahtani et al., 2017; Hasan & Dridi, 2011), featuring superior asset quality and capitalisation (Beck et al., 2013), exhibiting lower risk compared to their conventional counterparts (Abedifar et al., 2013; Baele et al., 2014; Čihák & Hesse, 2010; Pappas et al., 2017), and of higher technical efficiency (Johnes et al., 2014; Mobarek & Kalonov, 2014). This distinct profile is of particular relevance to investors, who can enjoy important diversification benefits, particularly during periods of economic and financial turmoil (Alexakis, Pappas, et al., 2017; Erragragui et al., 2018; Rizvi et al., 2015; Sensoy, 2016; Sorwar et al., 2016); albeit these benefits may depend on cross-country religious restrictions on conventional stock trading (Alhomaidi & Kabir Hassan, 2017). In terms of ownership structure, Islamic banks are typically local, unlisted, featuring a small number of shareholders that are often linked to royal families that are a common feature in these countries. For these reasons it may be plausible that Islamic banks have not been particularly transparent, although in recent years significant steps to revert this tendency have been taken (Ariffin et al., 2007). In terms of corporate governance, Islamic banks maintain a Shariah Supervisory Board (SSB) that works alongside the Board of Directors, but is considered the “Supra Authority” in an Islamic bank (Choudhury & Hoque, 2006). The SSB ensures that products and practices are consistent with the religious guidelines, and ensures that Islamic banks adhere to their societal commitments (Mallin et al., 2014). Thus, the SSB represents an additional internal control mechanism on management relative to conventional banks. Related research has found that a large and independent SSB is beneficial to the financial performance and stability (Farag et al., 2017; Mollah & Zaman, 2015). In particular, the SSB operates as a protective cushion that allows Islamic banks to take higher risk and achieve better For generic recent surveys on Islamic finance literature we direct you to Abedifar et al., (2015), Alzahrani and Megginson (2017), Narayan et al., (2019). For focused recent litetarute reviews on Islamic capital markets and Islamic banking respectively, we direct you to Delle Foglie and Panetta (2020) and Hassan and Aliyu (2018). Electronic copy available at: https://ssrn.com/abstract=3845365 performance (Mollah, Skully, et al., 2017; Uddin et al., 2017). On the one hand a large and active SSB reduces Shariah non-compliance risk (Basiruddin & Ahmed, 2017), but on the other hand it has been linked with a lower bank performance (Nawaz, 2019). Islamic banks have higher board of directors independence, which is documented to be positively linked to capitalisation and to a prudent risk-taking behaviour (Mollah, Hassan, et al., 2017; Vallascas et al., 2017). Hayat and Kabir Hassan (2017) examine the link between higher capitalisation and good governance (Jeitschko & Jeung, 2005), for Islamic and non-Islamic firms and find that the former score higher on well-reputed governance indicator scores. The price that Islamic banks have to pay for the dual-board structure is reflected in their cost efficiency (Uddin et al., 2017), particularly through the increased number of board committees (Alexakis, Al-Yahyaee, et al., 2017). Even though Islamic banks operating in dual- banking countries appear to be unaffected by competition from conventional banks with respect to deposit rate setting (Meslier et al., 2017), it is unknown if this extends to other financial aspects, including profitability and financial stability; or depends on the Islamicity of the country’s population (Rehman & Askari, 2010); or is related to how particular aspects of Islamic banking vary, such as the Zakat implementation (Choudhury & Limodio, 2017). Financial reporting in Islamic banks There is scant research around on financial reporting in Islamic banks, without any contribution, to the best of our knowledge, on auditing. Within the realm of normative research on financial reporting, Abdel Karim (1995) discusses the role of the Financial Accounting Organization for Islamic Banks and Financial Institutions (now Accounting and Auditing Organization for Islamic Financial Institutions), while Baydoun and Willett (2000) and Karim (2001) emphasize the need to adapt and harmonize financial statements to match with the Islamic banks are susceptible to Shariah compliance risk in regard to the conformity of financial products to the Shariah, see Ullah et al. (2018) for an investigation. Electronic copy available at: https://ssrn.com/abstract=3845365 ethical considerations of Islamic banks. Oldon and Zoubi (2008) compare a set of financial ratios of Islamic and conventional banks. Empirical research has mostly focused on earnings management in a comparative setting (Abdelsalam et al., 2016; Elnahass et al., 2018; Lassoued et al., 2018; Quttainah et al., 6 7 2013). Examining the abnormal loan loss provision and loss avoidance, these studies find that Islamic banks exhibit lower propensity to engage in earnings management. In part, this has been attributed to the role of the SSB (Quttainah et al., 2013), as well as the more conservative accounting sentiment (Abdelsalam et al., 2016) inherent in Islamic banks. Islamic banks were early adopters of the expected loss model for loan loss provisions, which is regarded as more proactive than the incurred loss model considering the economic cycle expectations; thus, more appropriate for the equity/participation type of contracts in use by these banks. Relatedly, the study of Elnahass et al. (2018) finds that because of the different loan loss provisioning systems, Islamic banks do not use the loan loss provision for capital or earnings management. Closely related to the literature, a handful of papers also examine the role of religiosity and financial reporting. Besides, it has been documented that religious investors are more risk- averse in general; more so during periods of pronounced religious importance, such as the month of Ramadan (Białkowski et al., 2012; Hilary & Hui, 2009; Taap et al., 2011). Focused in the US, Dyreng et al. (2012) and McGuire et al. (2012) document that earnings management and financial reporting irregularities have lower propensities for firms located in counties with high religious adherence. A different angle is taken by Mallin et al. (2014), who examine CSR activities in Islamic banks. They find that Islamic banks generally engage in a broad range of social activities. Importantly, there is a positive association between CSR disclosure and corporate financial performance. The loan loss provision is one of the key accounting policies for Islamic banks. Accordingly, Elnahass et al. (2014) investigate the value relevance of the loan loss provision in Islamic vs. commercial banks, in a cross- country study. They document that the loan loss provision is value relevant in both Islamic and conventional banks. The discretionary component of the loan loss provision has lower value relevance in Islamic banks than in conventional banks. Electronic copy available at: https://ssrn.com/abstract=3845365 Hypotheses development On the one hand, we expect that audit fees should be lower in Islamic banks than in conventional banks for two reasons. First, audit risk is expected to be lower in Islamic banks than in conventional banks because the former have been shown to exhibit lower credit risk and default risk (Abedifar et al., 2013; Baele et al., 2014; Ongena & Şendeniz-Yüncü, 2011; Pappas et al., 2017; Sorwar et al., 2016). Second, Islamic banks have a dual-board structure with a Shariah Supervisory Board (SSB) working alongside the Board of Directors. Although the primary role of the SSB is to opine on the conformity of the offered products to the Islamic law, it is considered as the “Supra Authority” (Choudhury & Hoque, 2006). The presence and the well-functioning of the SSB in an Islamic bank has been linked to enhanced financial performance (Farag et al., 2017; Mollah & Zaman, 2015) and superior financial stability (Mollah, Hassan, et al., 2017; Mollah, Skully, et al., 2017; Pappas et al., 2017; Uddin et al., 2017). Overall, the existence of the SSB may have a beneficiary impact on audit fees, either indirectly (e.g., through lower financial risk of the institution) or directly (e.g., by acting as an additional layer of control and, hence, reducing audit risk). On the other hand, audit fees might be higher in Islamic than in conventional banks for three, partly related with each other, reasons. First, Islamic banks use specialized financial products, which bear little or no resemblance to conventional products. Some of these products (typically the equity-based ones) are custom made to projects and/or individuals, which may render the auditing process lengthier and more complex. Second, and strictly related to the In particular, Abedifar et al. (2013) find that Islamic banks have lower credit risk than conventional banks. The results are stronger for small, leveraged banks as well as for those operating in countries with more a Muslim population higher than 90%. They also find that the insolvency risk of small Islamic banks is lower than that of small conventional banks, as the former are more capitalized. Relatedly, Baele et al. (2014) document that the default rate of Islamic loans is less than half than that of conventional loans. In line with the view that the clients of Islamic banks have relatively low risk of default, Ongena and Şendeniz-Yüncü (2011) find that Islamic banks mainly have corporate clients that are young, transparent, industry-focused, and have multiple-bank relationships. Using market-based indicators of risk, Sorwar et al. (2016) document a lower market risk for Islamic banks, in particular during the financial crisis. Based on the results of a survival analysis, Pappas et al. (2017) find that Islamic banks are more stable than conventional banks. Electronic copy available at: https://ssrn.com/abstract=3845365 previous point, auditors in Islamic banks may require some additional training and familiarity with the Islamic finance terminology and the contract specifics. This may amount to an additional cost, particularly during the first years of auditing in an Islamic bank and assuming no prior expertise on the auditor’s behalf. It may be expected however, that over time the auditor would have become accustomed to the specifics of Islamic finance, hence any higher audit fees are expected to be only in the short run. Third, the ownership structure of Islamic banks, which are typically owned by a small number of shareholders who are often related to the government and/or royal families, implies a greater opaqueness of the information environment and increases audit risk. Because of the competing arguments, we formulate a nondirectional hypothesis regarding the relationship between Islamic banking and audit fees. HYPOTHESIS 1. Audit fees charged to Islamic banks are not different than audit fees charged to conventional banks. Next, we examine whether the expertise of the auditors in Islamic banking affects the fees which are charged to bank clients. We expect that Islamic banks will be willing to pay more for the services of auditors with higher expertise in Islamic banking, because they are perceived as being more competent. In addition, auditors with higher expertise in Islamic banking are likely to charge higher fees to their Islamic bank clients as a compensation for the time and resources spent on their specialized training. Accordingly, we hypothesise that the audit fees charged to Islamic banks increase as the Islamic banking expertise of the auditors increases. These arguments are in line with those of a branch of research which examines the effects of auditor industry expertise on the audit outcomes. Specifically, many archival and experimental studies document a positive association between industry expertise and audit fees Electronic copy available at: https://ssrn.com/abstract=3845365 (Cahan et al., 2011; Carson, 2009; Casterella et al., 2004; Craswell et al., 1995; DeFond et al., 2000; Ferguson et al., 2003; Francis et al., 2005; Mayhew & Wilkins, 2003). HYPOTHESIS 2. Audit fees charged to Islamic banks increase as the auditor expertise in Islamic banking increases. After having tested whether audit pricing for Islamic banks is different than for conventional banks, we investigate the quality of auditing. To examine audit quality, we focus on the discretionary loan loss provision, the likelihood of meeting or beating earnings benchmarks and restatements. On the one hand, we expect audit quality to be lower for Islamic banks than for conventional banks because, as mentioned when developing H1, the complexity of the audit process is potentially greater for Islamic than conventional banks. This is due to the existence of highly specialized financial products, to the necessity to acquire new skills and to a less transparent information environment. This greater complexity of the audit process may lead to a lower quality of auditing. On the other hand, in Islamic banks there is an additional layer of control on managers, relative to conventional banks. Specifically, the presence of a Shariah Board, which has also been discussed in the development of H1, although its focus is not on financial reporting, may help prevent opportunistic reporting by managers. Since there are competing arguments, we formulate a nondirectional hypothesis regarding the relationship between Islamic banking and audit quality. HYPOTHESIS 3. Audit quality in Islamic banks is not different from conventional banks. It is important to note, however, that other papers do not find a positive association between auditor industry expertise and audit fees (Ferguson et al., 2003; Mayhew & Wilkins, 2003; Minutti-Meza, 2013). Electronic copy available at: https://ssrn.com/abstract=3845365 3. Data and methods Data Our dataset covers the period 2010-2017 and features 14 Islamic and 57 conventional banks that operate in Malaysia. This sample corresponds to all the banks with data available in FitchConnect. Islamic banks represent around 20% of our sample that is consistent with similar studies (Beck et al., 2013; Izzeldin et al., 2021). Financial and accounting data are obtained from the FitchConnect database. Data on audit fees are hand-collected from the annual reports. Methods Main analysis We first examine the Islamic banking effect on audit fees (H1). Hence, we regress the natural logarithm of audit fees, LAF, on an Islamic bank binary dummy. We include a full set of control variables and year fixed effects. For our choice of control variables we are guided by the extant literature on audit fees in the banking industry, in particular the seminal papers of Cullen et al. (2018) and Fields et al. (2004), and data availability. In particular, and to examine audit fees, we estimate the following model: LAF = β + β ΙΒ + β IBCONC + β IBCONC × ΙΒ + γΧ (1) ijt 0 1 it 2 3 jt it it + ε ijt where 𝑖 , 𝑗 , 𝑡 index banks, auditors and years respectively, 𝐹𝐿𝐴 is the natural log of audit fees, 𝐼𝐵 is a binary variable that takes the value one for Islamic banks, zero otherwise; the control variables (𝑋 ) are defined in the Appendix. We base our inference on cluster-adjusted standard errors. The Appendix contains the definitions of the variables used in the empirical models. Electronic copy available at: https://ssrn.com/abstract=3845365 To test H2, we build a measure of expertise in Islamic banking. Expertise is unobservable; therefore, in line with prior auditing research on industry specialization, we calculate a measure of expertise which is based on the fees received from Islamic banks relative to the sum of the fees received from all the bank clients. Specifically, we focus on the variable IBCONC, which is defined at the auditor level as the sum of audit fees from Islamic banks to the total audit fees in a given year. To test whether auditor expertise affects the relation between Islamic banking and audit fees, we include, in equation [1], the interaction term between IBCONC and IB. We also investigate whether differences in audit fees reflect differences in audit quality (H3), which we measure using the discretionary loan loss provision, the likelihood of meeting or beating earnings benchmarks and restatements. First, we examine the discretionary loan loss provision, DLLP, calculated following Kanagaretnam et al. (2010). The discretionary loan loss provision is obtained as the residuals of the equation [2], which relates the loan loss provision scaled by total assets, LLP, to a set of control variables and year fixed effects. Because the loan loss provision can be used to manage the reported performance by banks, the common interpretation in the literature is that the higher the discretionary loan loss provision the lower the quality of auditing. LLP = α + 𝛼 BEGLLA + α LCO + α CHLOANS + α LOANS (2) it 0 1 it 2 it 3 it 4 it + α NPL + α DNPL + ε 5 it 6 it it where BEGLLA is the ratio of the beginning of the period loan loss allowance to beginning of the period total assets; LCO is the ratio of net charge-offs to total assets; change in loans, scaled Alternative measures of audit quality are based on qualified audit opinions. We manually inspected the audit reports of all the observations and we did not find any report in which the auditor state that they have doubts ont he ability of the firm to continue as a “going concern”. Electronic copy available at: https://ssrn.com/abstract=3845365 by total assets, from year t-1 to year t; NPL is the ratio of nonperforming loans to total assets; DNPL is the change in NPL from year t-1 to year t. Our second measure of audit quality is the likelihood of meeting or beating earnings benchmarks by a small amount. We focus on the variable MBE, which is a dummy variable taking value one if the ratio of operating profit to total assets is included in the interval (0;0.005). In untabulated tests we consider an alternative measure of the likelihood of meeting or beating earnings benchmark and obtained similar results. The alternative measure is a dummy variable taking value one if the change in the ratio of operating profit to total assets is included in the interval (0;0.0025). It has been widely documented that managers have incentives to manage earnings to avoid missing earnings benchmarks. Accordingly, the common interpretation is that as the likelihood of (just) meeting or beating earnings benchmarks increases, audit quality decreases. As a third measure of audit quality, we use restatements. We obtain the list of restatements in our sample from FitchConnect and manually inspect the annual reports which contain details on the restatements. We focus on a dummy variable (REST) which indicates whether the restatements which have an effect on the statement of comprehensive income; the results are similar if we include all the restatements in the analysis. Restatements are meant to capture audit failures and they are commonly considered as a direct measure of audit quality (DeFond and Zhang, 2014). We then relate our measures of audit quality (AQ) to the IB dummy, a set of control variables (𝐹 ) and year fixed effects, as shown in equation [3]. AQ = b + b IB + gF + u (3) it 0 1 it it it In further untabulated tests we also included the boundaries of the interval (for both measures) and inference about the coefficient on IB is unchanged. Electronic copy available at: https://ssrn.com/abstract=3845365 The definition of the control variables, which are chosen in a similar way to Kanagaretnam et al. (2010), is contained in the Appendix. Equation (3) is estimated using OLS when the dependent variable is DLLP and using a Probit when the dependent variable is MBE. With both models we use bank cluster-adjusted standard errors. An extended specification For robustness, we use an extended specification to equation [1], which is in line with the banking literature and further accounts for financial stability, technical efficiency, and loan portfolio differences. Our motivation for controlling for these factors is that Islamic banking has been purported to be fundamentally different to conventional practices, with a large strand of the banking literature documenting significant differences in respect to financial risk profile, efficiency, and business model practices. To control for financial stability of the bank we use the popular z-score indicator (Boyd & Runkle, 1993; Laeven & Levine, 2009). The z-score is defined as: ROA + E /TA (4) it it it z − score = it σ(ROA ) it For the calculation of the z-score, ROA is the return on assets, E/TA is the equity to total assets ratio, and σ(ROA) is the standard deviation of ROA computed based on the full dataset. As the z-score is highly skewed we take the natural log. Higher values of the z-score indicate higher financial stability. Technical efficiency is associated with the bank’s ability to obtain maximum output with a given set of inputs. Efficiency can be measured either by using traditional financial ratio analysis (FRA) or by frontier estimation methods. A drawback of financial ratios is that they do not take into consideration the input prices and the output mix and weights of the ratios are selected subjectively (Berger & Humphrey, 1992). Here we estimate the technical efficiency Electronic copy available at: https://ssrn.com/abstract=3845365 (EFF) of each bank using a stochastic frontier approach. We assume the banks act as intermediaries between fund surplus and deficit units, as introduced by Sealey and Lindley (1977) and in line with Casu and Girardone (2010). Hence banks are assumed to produce Loans (y1), Securities (y2) and Other Earning Assets (y3) that constitute the outputs. The input variables are Deposits (x1), Personnel Expenses (x2), Fixed Assets (x3) and Equity (x4), in line with Izzeldin et al. (2021). All monetary variables have been deflated using the GDP deflator. We use the following translog function: M−1 M−1 M−1 (5) y 1 y y mit mit nit ln y = α + ∑ α ln( ) + ∑ ∑ α ln ( ) ln ( ) Mit 0 m mn y 2 y y Mit Mit Mit m=1 m=1 n=1 K K K + ∑ β ln x + ∑ ∑ β ln x ln x k kit kl kit lit k=1 k=1 l=1 K M−1 mit + ∑ ∑ δ lnx ln( ) + ε km kit it Mit k=1 m=1 where the error term 𝜀 is split into two components, i.e. 𝜀 = 𝑣 − 𝑢 where 𝑣 represents 𝑖𝑡 𝑖𝑡 𝑖𝑡 𝑖𝑡 𝑖𝑡 statistical noise, i.e., 𝑣 ~𝑁 (0, 𝜎 ), and 𝑢 represents the efficiency of bank 𝑖 in time period 𝑖𝑡 𝑣 𝑖𝑡 + 2 13 𝑡 and is distributed as half-normal i.e. 𝑢 ~𝑁 (𝜇 , 𝜎 ), following Aigner et al. (1977). 𝑖𝑡 To capture the diversity in the activities of each bank, we use the income diversity (ID) that is defined as: Net interest income− Noninterest income (6) ID = 1 − | | it Total income Higher values show a more diversified stream of income. In addition, banks may have different specialisation in their loan portfolios, which typically comprise of credit card loans, manufacturing loans, loans to small & medium enterprises, corporate loans, property The average efficiency for Islamic banks is 0.752 and for conventional banks is 0.627, a statistically significant difference. Islamic banks do not charge/receive interest; in their case the “interest rate” is reflective of the profit share ratios used in the asset and liability side of their balance sheet. Electronic copy available at: https://ssrn.com/abstract=3845365 development loans, agricultural loans, commercial property loans and mortgages. We extract two common factors (F1 and F2) within the loan portfolio using Principal Component Analysis (PCA). 4. Results Descriptive statistics Table 1 summarizes the main descriptive statistics for the key variables in our analysis for Islamic and conventional banks. A first inspection of the table suggests notable differences between the two bank types with regards to bank size, capitalisation, funding mode and operations, profitability and cost efficiency. In particular, Islamic banks appear to be smaller on average in terms of total assets compared to conventional banks ($8.52 bil. vs $14.13 bil.), of lower capitalization ratio (CAPRATIO: 12.77 vs 25.14), engage less in securities (SECURITIES: 0.18 vs 0.26), less profitable (EBTP: 1.51 vs 7.82), of lower liquidity despite their business model restrictions on use of debt instruments (LIQUIDITY: 8.14 vs 10.64) and with higher cost efficiency ratios (COSTTOINCOME: 49.24 vs 55.00). Most of both Islamic and conventional banks are audited by BIG4 audit firms. In addition, average fees are lower in Islamic than in conventional banks ($0.68 mil. vs $0.75 mil.); the measures of audit quality (DLLP, MBE, REST) are similar in the two subsamples. [Table 1 around here] Table 2 presents the Pearson correlations for the main variables used in the audit fee model. Interestingly, the correlation between audit fees and the dummy for Islamic banking is negative and significant (9.6%). The correlations for the control variables used in the audit quality model are untabulated. It is worthwhile to note the correlation between each of our audit The two retained factors account for around 26.4% of the variance and are reasonably reflective of return (F1) and risk (F2). These results are omitted for brevity and are available upon request. Electronic copy available at: https://ssrn.com/abstract=3845365 quality measures (discretionary loan loss provision, DLLP; likelihood of meeting or beating earning benchmarks, MBE; restatements, REST) and the dummy for Islamic banking is insignificantly different from zero. [Table 2 around here] Islamic banking, audit fees and audit quality The results of our main model on audit fees are reported in Table 3. The coefficient on the dummy for Islamic banks is negative and highly significant, suggesting that there is a fee discount for Islamic banks. H1, which is formulated in nondirectional form, is not confirmed. This result is consistent the view that audit risk is lower in Islamic banks than in conventional banks. Lower audit risk can be explained by lower credit and default risk; lower audit risk can also be due to a lower probability of fraud or accounting misstatements because of the greater emphasis on ethical considerations. The economic magnitude of the effect is of Islamic banking on audit fees is strong. Specifically, the results imply that, after controlling for the determinants of audit fees, there is a fee discount for Islamic banks of approximately 50%. [Table 3 around here] Next, we investigate whether the expertise of the auditors in Islamic banking affects the pricing of auditing services. The last column of Table 3 show that the coefficient on the interaction terms between IB and our measure of expertise in Islamic banking, IBCONC, is positive and highly significant. These findings suggest that, consistent with H2, fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. The results are in line with the view that auditors with higher expertise in Islamic banking are perceived as being more competent by Islamic bank clients; therefore, they can charge higher We also calculated an alternative measure of Islamic banking expertise, which is based on the total assets of the clients. The alternative measure is defined as: (Total assets of Islamic bank clients)/ (Total assets of all bank clients). The results, which are untabulated, are qualitatively unchanged relative to those obtained with IBCONC. Electronic copy available at: https://ssrn.com/abstract=3845365 fees to these clients. The results are also consistent with the branch of auditing literature which documents a positive association between industry expertise and audit fees. We also examine whether differences in audit prices reflect differences in audit quality, which we measure using the discretionary loan loss provision (DLLP), the likelihood of meeting or beating earnings benchmarks (MBE) and restatements (REST). The results of our audit quality models are reported in Tables 4 and 5. We note that, similar to Kanagaretnam et al. (2010), the control variables in Table 4 are different from those used in Table 5. In Table 4, we examine DLLP. Both when using all the values of DLLP (column 2) and when positive values of DLLP (column 5), the coefficient on the dummy for Islamic banking is positive, but it is not significantly different from zero. In Table 5, we present the results for MBE (columns 2) and REST (column 5). These results are in line with those observed in Table 4. H3, which is formulated in nondirectional form, is confirmed: after controlling for its cross-sectional determinants, audit quality does not differ between Islamic and conventional banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost for the quality of audit services. [Table 4 around here] [Table 5 around here] The insignificant difference in audit quality is in line with the view that the two competing effects of Islamic banking offset each other. Specifically, on the one hand, the complexity of the audit process is potentially greater for Islamic than conventional banks. This As a further alternative proxy for industry expertise, we also defined, for each year, the Islamic banking industry leader as the auditor with the highest amount of fees received from Islamic banks during the year. Accordingly, we built the dummy variable IBLEAD, which takes value one for Islamic banks which are audited by the industry leader. We replicated the analysis in the last column of Table 3 using IBLEAD instead of IBCONC. The results, which are untabulated, show that the coefficients on IBLEAD and on the interaction term between IBLEAD and IB are insignificantly different from zero. We also replicated the analysis interacting IB with all the control variables. Inference regarding the IB dummy variable is unchanged. Electronic copy available at: https://ssrn.com/abstract=3845365 is due to the existence of highly specialized financial products, to the necessity to acquire new skills and to a less transparent information environment. The higher complexity may lead to lower audit quality for Islamic banks. On the other hand, the presence of an additional layer of control on managers, which is represented by the Shariah Board, may help to constrain managers’ reporting choices and to increase audit quality. In the columns (3) and (6) of Tables 4 and 5, we examine the effect of Islamic banking expertise on audit quality. We find that the coefficient on the interaction terms between IB and our measure of Islamic banking expertise is insignificantly different from zero. Therefore, the effect of IB on audit quality is not affected by the expertise of the auditors in Islamic banking. It is also interesting to notice that, in column (6) of Table 5, the coefficient on IBCONC is significant and negative. This indicates that restatements are (weakly) negatively associated with auditor expertise in Islamic banking. Additional analyses on audit pricing We run two additional analyses on audit pricing. First, we examine the results in selected subsamples. Second, we estimate an extended model for audit fees (as described in Section 3.2.2.). Table 6, panels A-E presents the results on sample splits. We re-estimate the main audit fee model using median sample splits on five variables: size, which is measured as total assets; and four variables used in the extended audit fee model, financial stability, technical efficiency and the two principal components of the loan portfolio. The purpose of these tests is to examine the cross-sectional variation of our results and investigate the robustness of our conclusions. Electronic copy available at: https://ssrn.com/abstract=3845365 The models contain the full set of control variables, but, for brevity, in the table we only report the estimated IB coefficient and robust t-statistic in brackets. [Table 6 around here] A cursory inspection of the results shows that the negative coefficient on the IB dummy corroborates the main conclusions from the paper, whereby Islamic banks exhibit lower audit fees. The differences in the coefficient on IB across the subsamples are not significantly different from zero. Overall, these findings corroborate the main results. In Table 7 we present the results of the extended audit fee model. The results confirm the audit fee discount for Islamic banks of the main part of the paper. The additional control variables appear to be only weakly related to audit fees. Specifically, F1 and F2 have insignificant coefficients. The ZSCORE, our proxy for financial instability has a positive and significant coefficient in the second column. A positive coefficient is consistent with the interpretation that higher fees are required if the risk of insolvency increases. In addition, EFF, our measure of technical efficiency has a negative and significant coefficient in the first column. A negative coefficient is in line with the view that auditors perceive less efficient banks as riskier. The results in the last column also confirm those presented in the main analysis. Specifically, the fee discount for Islamic banks is lower as the Islamic banking expertise of the auditors increases. [Table 7 around here] We note that the number of observations in the High and Low portfolios are different because of different availability of some of the control variables in the two subsamples. In further untabulated tests we also replicated the analysis excluding the conventional banks which are listed, and the results are similar to the main analysis. Electronic copy available at: https://ssrn.com/abstract=3845365 5. Conclusions In this paper, we investigate the audit market in Islamic banks. Despite the increasing importance of Islamic banking in the global finance industry, only scant research examines financial reporting of Islamic banks. To our knowledge, academic research has not yet examined the role of auditors in Islamic banking. We find an audit fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. Our results also show that the fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. We interpret these results as evidence that auditors bear lower risks in Islamic banks than in conventional banks. This lower audit risk in Islamic banks can be explained by lower credit and default risk; it can also be due to the presence of an additional layer of control on managers, which is represented by the Shariah Supervisory Board. Although fees are lower in Islamic than in conventional banks, we find no significant differences in audit quality, which we measure through the discretionary loan loss provision and the likelihood of meeting or beating earnings benchmarks, between the two types of banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost in the quality of audit services. Our analysis contributes to the comparative literature between Islamic and conventional banks. In addition, it adds to the stream of research which examines the determinants of audit fees and audit quality in the banking industry. Electronic copy available at: https://ssrn.com/abstract=3845365 References Abdel Karim, R. A. (1995). The nature and rationale of a conceptual framework for financial reporting by Islamic banks. Accounting and Business Research, 25(100), 285–300. Abdelsalam, O., Dimitropoulos, P., Elnahass, M., & Leventis, S. (2016). 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TRANSDEP The ratio of transaction accounts (deposits minus saving and term deposits) to total deposits SECURITIES The ratio of investment security assets to total assets COMMLOAN The ratio of commercial loans to total loans MTGLOAN The ratio of loans secured by a mortgage to total loans INTANG The ratio of intangible assets to total assets CHGOFF The ratio of net charge-offs to total loans IMPLOAN The ratio of impaired loans to total loans COSTTOINCOME The ratio of total expenses divided by total income BIG4 An indicator variable, 1 = the auditor is one of the BIG4; zero otherwise INTDERIV The ratio of the notional value of interest rate derivatives to total assets LISTED An indicator variable, 1 = Listed bank; zero otherwise Electronic copy available at: https://ssrn.com/abstract=3845365 B. Audit quality model LLP The ratio of the loan loss provision to total assets BEGLLA The ratio of the beginning of the period loan loss allowance to beginning of the period total assets. LCO The ratio of net charge-offs to total assets CHLOANS The change in LOANS from year t-1 to year t LOANS The ratio of loans to total assets NPL The ratio of nonperforming loans to total assets DNPL The change in NPL from year t-1 to year t DLLP Discretionary loan loss provision (see Section 3.2.1) MBE An indicator variable, 1 = (Operating profit)/ (Total assets) in the interval (0;0.005); zero otherwise. REST An indicator variable, 1 = The accounts have been restated (and the restatement has an effect on the statement of comprehensive income); zero otherwise IB An indicator variable, 1 = Islamic bank; zero otherwise BIG4 An indicator variable, 1 = the auditor is one of the BIG4 LTA Natural logarithm of total assets GROWTH The change in total assets from year t-1 to year t, divided by total assets in year t-1. PASTLLP The LLP in year t-1 ALLOW The ratio of loan loss allowance to beginning of the period total assets CF The change in the ratio earnings before taxes and loan loss provisions to beginning of the period total assets from year t-1 to year t EBTP The ratio earnings before taxes and loan loss provisions to beginning of the period total assets LISTED An indicator variable, 1 = Listed bank; zero otherwise C. Additional variables IB An indicator variable, 1 = Islamic bank; zero otherwise IBCONC An auditor/year specific variable, which is obtained as: (Audit fees from Islamic banks)/ (Total fees from bank clients) EQUITY The ratio of equity to total assets LIQUID The ratio of liquid assets to total assets ZSCORE An indicator of financial stability (see Section 3.2.2) EFF An indicator of technical efficiency (see Section 3.2.2) F1, F2 First two principal components for loan portfolio specialization (see Section 3.3.2) Notes: All data, except audit fees (which are hand-collected), are sourced from FitchConnect. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 1 Descriptive statistics All banks Conventional Islamic Mean SD Mean SD Mean SD LAF -0.3092 1.0532 -0.2884 1.1484 -0.3793 0.6357 LTA 9.4609 1.8046 9.5564 1.9595 9.0505 0.8659 LOSS 0.0372 0.1894 0.0456 0.2088 0.0090 0.0949 FOREIGN 0.2500 0.4335 0.2788 0.4490 0.1532 0.3618 CAPRATIO 22.7002 35.1716 25.1482 38.7705 12.7751 6.2163 TRANSDEP 0.2754 0.2813 0.2833 0.2885 0.2499 0.2560 SECURITIES 0.2467 0.2078 0.2653 0.2263 0.1831 0.1040 COMMLOAN 0.0110 0.0536 0.0091 0.0408 0.0171 0.0820 MTGLOAN 0.1990 0.2272 0.1821 0.2381 0.2528 0.1789 INTANG 0.0068 0.0153 0.0082 0.0169 0.0019 0.0050 CHGOFF 0.4383 1.2386 0.4269 1.3530 0.4847 0.5802 IMPLOANS 3.6472 8.1529 3.7517 8.9334 3.2958 4.6700 COSTTOINCOME 53.8618 29.0821 55.0009 31.1591 49.2433 17.7958 INTDERIV 0.0141 0.0366 0.0175 0.0408 0.0022 0.0053 LISTED 0.2190 0.4140 0.2842 0.4516 0.0000 0.0000 ZSCORE 36.3477 34.7540 36.6515 34.5981 35.1159 35.5441 EFF 0.6534 0.2109 0.6223 0.2168 0.7607 0.1453 F1 -0.0618 0.7949 -0.0791 0.8431 -0.0067 0.6173 F2 -0.0547 0.7239 -0.0152 0.7404 -0.1805 0.6560 DLLP 0.0000 0.0031 -0.0001 0.0030 0.0003 0.0033 MBE 0.0744 0.2627 0.0697 0.2550 0.0901 0.2876 REST 0.0909 0.2878 0.0831 0.2764 0.1171 0.3230 BIG4 0.8988 0.3020 0.9008 0.2993 0.8919 0.3119 GROWTH 0.1068 1.0279 0.1312 1.1649 0.0230 0.1290 PASTLLP 0.0020 0.0037 0.0016 0.0035 0.0032 0.0040 CF -0.0020 0.0844 -0.0023 0.0964 -0.0010 0.0066 ALLOW 0.0123 0.0175 0.0112 0.0168 0.0165 0.0195 EBTP 0.0634 0.0977 0.0782 0.1072 0.0151 0.0108 LIQUID 10.0725 12.1670 10.6453 13.1186 8.1478 7.9472 EQUITY 21.9288 23.0365 24.7261 24.4120 10.5875 10.3723 IB 0.2293 0.4208 0.0000 0.0000 1.0000 0.0000 IBCONC 0.1350 0.1054 0.1245 0.1015 0.1704 0.1111 Notes: The table reports descriptive statistics for the main variables in the analysis. Monetary values are expressed in USD millions. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 2 Cross-correlations 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 2 0.604 3 -0.100 -0.287 4 -0.171 -0.224 0.039 5 -0.221 -0.486 0.346 0.112 6 -0.066 -0.078 0.062 0.270 -0.015 7 -0.128 -0.150 -0.078 -0.220 0.246 -0.090 8 0.071 0.046 0.014 -0.053 -0.069 -0.079 -0.078 9 0.297 0.475 -0.156 -0.046 -0.243 -0.081 -0.256 0.168 10 0.010 0.031 0.041 -0.282 0.037 -0.200 0.230 0.004 -0.153 11 0.004 0.078 0.054 -0.039 -0.145 0.081 -0.032 -0.016 -0.001 -0.035 12 -0.020 -0.180 0.164 -0.139 0.136 -0.061 0.243 -0.005 -0.225 0.027 0.178 13 -0.206 -0.464 0.368 0.107 0.476 0.073 0.029 -0.044 -0.213 0.206 -0.021 0.025 14 0.062 -0.061 0.088 -0.213 0.147 -0.111 0.084 0.101 0.031 0.228 0.120 0.169 0.049 15 0.020 -0.122 -0.020 0.246 -0.022 0.413 0.071 -0.072 -0.125 -0.128 -0.009 -0.124 0.087 -0.062 16 0.179 0.434 -0.043 -0.329 -0.181 -0.195 0.017 0.023 0.148 0.233 0.045 -0.093 -0.090 0.024 -0.146 17 -0.096 0.092 -0.085 -0.165 -0.188 -0.051 -0.197 0.073 0.137 -0.196 0.046 -0.032 -0.107 0.013 -0.197 -0.286 18 0.019 0.054 -0.020 0.240 -0.010 0.103 -0.104 -0.062 -0.112 -0.181 -0.015 0.092 -0.067 -0.305 -0.070 -0.207 0.190 19 -0.081 -0.120 0.217 0.120 0.060 0.077 -0.155 -0.016 -0.034 -0.031 -0.109 -0.040 -0.006 -0.133 0.070 -0.035 0.081 0.120 20 -0.140 -0.240 -0.062 0.148 0.016 0.122 -0.029 0.013 -0.133 0.059 0.005 -0.066 0.243 0.041 0.160 -0.082 0.038 0.084 0.161 21 0.028 0.100 -0.069 -0.112 -0.031 -0.144 0.096 -0.046 -0.073 0.115 0.077 0.088 -0.007 0.093 -0.034 0.093 0.006 0.018 0.002 0.000 Notes: This table reports Pearson correlations for selected variables. Definition of variables: (1) LAF; (2) LOSS; (3) LTA; (4) FOREIGN; (5) CAPRATIO; (6) TRANSDEP; (7) SECURITIES; (8) COMMLOAN; (9) MTGLOAN; (10) INTANG; (11) CHGOFF; (12) IMPLOANS; (13) COSTTOINCOME; (14) BIG4; (15) INTDERIV; (16) LISTED; (17) IB; (18) IBCONC; (19) DLLP; (20) MBE; (21) REST. We report in bold the coefficients which are significant at the 10%. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 3 Audit fees and Islamic banking (1) (2) (3) *** *** *** LTA 0.473 0.498 0.493 [5.91] [6.83] [6.61] LOSS 0.184 0.143 0.149 [1.30] [0.88] [0.92] *** *** FOREIGN -0.140 -0.334 -0.332 [-1.07] [-2.91] [-3.06] CAPRATIO 0.002 0.001 0.001 [0.98] [0.37] [0.44] TRANSDEP -0.219 -0.224 -0.260 [-1.07] [-1.38] [-1.57] ** ** SECURITIES -0.495 -0.671 -0.776 [-1.51] [-2.18] [-2.48] COMMLOAN -0.347 -0.275 -0.282 [-0.72] [-0.66] [-0.70] MTGLOAN -0.122 -0.134 -0.109 [-0.27] [-0.33] [-0.28] INTANG -1.264 -4.607 -4.822 [-0.25] [-0.88] [-0.93] CHGOFF -0.047 -0.032 -0.034 [-1.09] [-0.92] [-0.96] ** * IMPLOANS 0.015 0.012 0.012 [2.23] [1.67] [1.64] * * COSTTOINCOME 0.004 0.005 0.004 [1.65] [1.89] [1.70] BIG4 0.163 0.185 0.240 [0.94] [1.11] [1.30] ** INTDERIV 3.298 1.659 1.792 [2.16] [1.22] [1.31] * * LISTED -0.306 -0.633 -0.647 [-0.93] [-1.88] [-1.90] *** *** IB -0.706 -1.069 [-4.42] [-4.50] IBCONC -0.373 [-0.45] ** IB X IBCONC 2.161 [2.26] *** *** *** CONSTANT -4.650 -4.479 -4.360 [-6.52] [-7.03] [-6.87] Year FE Yes Yes Yes Observations 382 382 382 Adjusted R-squared 0.456 0.515 0.522 *** ** * Notes: The dependent variable is LAF. Standard errors are clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 4. Audit quality and Islamic banking: discretionary loan loss provision + + + DLLP DLLP DLLP DLLP DLLP DLLP (1) (2) (3) (4) (5) (6) BIG4 0.000 0.000 0.000 0.000 0.000 0.000 [-0.17] [-0.17] [-0.07] [0.67] [0.50] [0.46] *** *** *** ** ** ** LTA -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 [-3.82] [-3.58] [-3.58] [-2.22] [-2.25] [-2.42] GROWTH 0.001 0.001 0.001 0.001 0.001 0.001 [1.16] [1.13] [1.18] [1.53] [1.50] [1.44] *** *** *** *** *** *** PASTLLP 0.330 0.327 0.318 0.248 0.230 0.210 [5.37] [5.30] [4.89] [3.69] [3.48] [2.85] * * * ** ** ** EBTP -0.003 -0.003 -0.003 -0.008 -0.008 -0.008 [-1.89] [-1.76] [-1.81] [-2.48] [-2.28] [-2.47] * * * LISTED 0.001 0.001 0.001 0.001 0.001 0.001 [1.71] [1.73] [1.83] [1.24] [1.41] [1.51] IB 0.000 0.000 0.001 0.002 [0.61] [0.64] [1.25] [1.58] IBCONC 0.001 0.003 [0.76] [1.22] IB X IBCONC -0.001 -0.007 [-0.42] [-1.61] * * ** ** *** CONSTANT 0.002 0.002 0.002 0.004 0.004 0.004 [1.71] [1.73] [1.62] [2.56] [2.59] [2.68] Year FE Yes Yes Yes Yes Yes Yes Observations 279 279 279 122 122 122 Adjusted R-squared 0.168 0.166 0.161 0.231 0.238 0.237 Notes: The dependent variable is DLLP (all values) in columns (1)-(3) and DLLP (positive values) in columns *** ** * (4)-(6). We include year fixed effects. Standard errors are clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 5 Audit quality and Islamic banking: Earnings benchmarks and restatements MBE MBE MBE REST REST REST ** ** ** BIG 0.104 -0.036 0.127 -2.624 -2.516 -2.701 [0.06] [-0.02] [0.08] [-2.39] [-2.43] [-2.37] *** *** *** LTA -1.259 -1.467 -1.448 0.228 0.169 0.150 [-3.00] [-2.78] [-2.66] [0.91] [0.61] [0.52] GROWTH 0.747 0.881 0.892 -0.957 -1.526 -1.998 [0.67] [0.75] [0.76] [-0.80] [-1.19] [-1.39] CF 0.356 0.315 0.155 -0.792 -1.182 -0.821 [0.20] [0.20] [0.09] [-0.23] [-0.39] [-0.29] ALLOW -50.003 -46.583 -49.040 3.276 11.748 14.468 [-1.36] [-1.33] [-1.26] [0.13] [0.62] [0.87] * * * LEV -0.065 -0.068 -0.065 0.003 -0.003 -0.007 [-1.73] [-1.91] [-1.85] [0.10] [-0.13] [-0.29] LOANS 1.452 0.647 0.464 -1.003 -2.023 -1.296 [0.99] [0.41] [0.26] [-0.71] [-1.28] [-0.75] *** *** *** EBTP -18.956 -15.696 -15.689 -23.813 -18.029 -18.757 [-1.57] [-1.32] [-1.34] [-2.90] [-2.65] [-2.69] * * LISTED -0.673 -0.440 -0.424 1.361 1.969 1.688 [-1.08] [-0.60] [-0.60] [1.65] [1.95] [1.36] IB 1.068 1.075 1.291 0.182 [0.85] [0.69] [1.52] [0.12] IBCONC 2.336 -6.580 [1.17] [-1.73] IBxIBCONC 0.148 7.140 [0.03] [1.26] *** ** ** CONSTANT 9.006 10.560 10.005 -1.248 -1.126 -0.309 [2.70] [2.57] [2.39] [-0.46] [-0.42] [-0.11] Year FE Yes Yes Yes Yes Yes Yes Observations 286 286 286 286 286 286 Pseudo R-sq. 0.257 0.267 0.274 0.220 0.239 0.258 Notes: The dependent variable is MBE (likelihood of meeting or beating earnings benchmarks) in columns (1)-(3) and REST (restatements) in columns (4)-(6). We include year fixed effects. Standard errors are *** ** * clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 6 Audit fees and Islamic banking: sample splits analysis High Low Panel A: Size ** ** IB -0.500 -0.521 [-2.08] [-2.66] Year FE Yes Yes Observations 223 158 Adj R-squared 0.510 0.463 Chi-sq stat 0.01 Panel B: Financial stability * *** IB -0.618 -0.728 [-1.95] [-4.95] Year FE Yes Yes Observations 195 186 Adj R-squared 0.649 0.571 Chi-sq stat 0.140 Panel C: Technical efficiency *** *** IB -0.891 -0.564 [-4.36] [-3.13] Year FE Yes Yes Observations 166 164 Adj R-squared 0.547 0.505 Chi-sq stat 1.880 Panel D: F1 *** ** IB -0.736 -0.504 [-3.78] [-2.05] Year FE Yes Yes Observations 207 175 Adj R-squared 0.494 0.413 Chi-sq stat 0.790 Panel E: F2 * *** IB -0.475 -0.749 [-2.00] [-3.62] Year FE Yes Yes Observations 200 182 Adj R-squared 0.506 0.550 Chi-sq stat 1.06 Notes: Median sample splits based on total assets (Panel A), financial stability (Panel B), technical efficiency (Panel C), and the two principal components of the loan portfolio (Panels D and E) are reported with the main and extended models of the main paper re-estimated. All control variables are included but are omitted from the table for brevity. The Chi-sq statistic is for the equality of the IB coefficient between the two sample splits. Standard errors are *** ** * clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 7 Audit fees and Islamic banking - extended model (1) (2) (3) *** *** *** LTA 0.518 0.512 0.498 [6.18] [6.78] [6.42] LOSS 0.033 -0.045 -0.021 [0.19] [-0.23] [-0.11] *** *** FOREIGN -0.162 -0.311 -0.313 [-1.23] [-2.66] [-2.74] CAPRATIO -0.001 -0.002 -0.002 [-0.23] [-0.56] [-0.54] TRANSDEP -0.138 -0.165 -0.180 [-0.63] [-0.97] [-1.05] SECURITIES -0.086 -0.536 -0.687 [-0.22] [-1.55] [-1.90] COMMLOAN -0.467 -0.057 -0.011 [-1.20] [-0.16] [-0.03] MTGLOAN 0.334 0.322 0.299 [0.46] [0.49] [0.46] INTANG -1.252 -4.765 -4.899 [-0.25] [-0.89] [-0.93] CHGOFF -0.072 -0.066 -0.067 [-1.46] [-1.60] [-1.61] ** ** ** IMPLOANS 0.016 0.015 0.015 [2.01] [2.01] [2.00] COSTTOINCOME 0.005 0.007 0.006 [1.37] [1.63] [1.35] BIG4 0.136 0.149 0.220 [0.83] [0.93] [1.21] INTERIV 2.291 1.468 1.700 [1.40] [1.00] [1.16] ** ** LISTED -0.430 -0.739 -0.757 [-1.24] [-2.07] [-2.11] * ** ZSCORE 0.005 0.005 0.006 [1.60] [1.99] [2.20] EFF -0.607 0.010 0.098 [-1.73] [0.03] [0.28] F1 -0.035 -0.068 -0.063 [-0.34] [-0.67] [-0.61] F2 0.153 0.112 0.092 [1.07] [0.86] [0.71] *** *** IB -0.730 -1.161 [-3.70] [-4.18] IBCONC -0.394 [-0.48] ** IB x IBCONC 2.486 [2.45] *** *** *** CONSTANT -5.374 -5.022 -4.858 [-6.78] [-7.29] [-7.08] Year FE Yes Yes Yes Observations 331 331 331 Adj R-squared 0.480 0.529 0.538 Notes: The table reports the results for the extended audit fee model see more details in section 3.2.2. The dependent variable is LAF. Standard errors are clustered by bank. *** ** * , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ARN Conferences & Meetings SSRN

Quality comes cheap: Evidence from auditing in Islamic banks

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Abstract

In this paper, we examine the audit market in Islamic banks, focusing on the pricing of audit services. To our knowledge, academic research has not yet examined the role of external auditors in Islamic banking. We argue that significant differences between Islamic and conventional banks, most notably in terms of activities allowed, corporate governance structure and ethical aspects of the business model, may lead to different audit outcomes. We find a fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. This result is in line with the view that the risks borne by auditors are lower in Islamic banks than in conventional banks. In addition, we document that the fee discount for Islamic banks is lower if auditors have higher expertise in Islamic banking. On the other hand, we do not observe significant differences in audit quality between Islamic and conventional banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost for the quality of audit services. Electronic copy available at: https://ssrn.com/abstract=3845365 1. Introduction Islamic banking is an important feature of the Gulf Cooperation Council (GCC), the South- East Asian and the Middle East regions, wherein it enhances financial development and economic welfare (Abedifar et al., 2016). On a global scale, it is estimated at $2.44 trillion of total assets under management (IFSB, 2020), while in certain countries it accounts for over one-third of the total banking assets. Sustained year-on-year double-digit growth rates have been largely unaffected by a series of economic events including the 2008 global financial crisis, geopolitical tensions, the 2015 oil price drop and depreciations of local currencies to the US dollar (IFSB, 2020). The economic and financial implications pertaining to the Covid-19 pandemic may take years to unfold fully. Yet with recent forecasts suggesting that the impact will be harsher on the advanced economies compared to the emerging markets and developing economies (-8.0% vs -3.0% real GDP growth rate), it may be expected that the Islamic banking would weather this crisis (IMF, 2020). The ethical character of Islamic banks is rooted in the religious underpinnings that govern their business model. Working within strict rules of allowable financial products and practices, Islamic banks have prioritised social values long before conventional banks shifted from a “shareholders only” approach towards embracing corporate social responsibility doctrines (Platonova et al., 2018). Debt interest payments, complex derivatives, short-selling and speculation, although highly desirable for shareholder value maximisation have been linked to social injustice and economic instability and are thus precluded from Islamic banking practices. Likewise, Islamic banks refrain from investments in largely deemed unethical businesses using business type and financial criteria (e.g., tobacco, alcohol, leverage, tangibility); a meritorious practice that predates the recent rise of ethical, environmental, sustainable, faith-based as well as social and responsible investments (EUROSIF, 2014) in light of financial crises (e.g., dotcom bubble, 2008 global financial crisis) and accounting scandals Electronic copy available at: https://ssrn.com/abstract=3845365 (e.g., Enron). To mobilise funds, Islamic banks promote the concept of risk-sharing, which inspires responsible behaviour and mitigates moral hazard (Al-Suhaibani & Naifar, 2014; Baele et al., 2014). Most countries with Islamic banks operate a dual-banking system with the ultimate choice falling to the investor. The expectation is that investors in Muslim dominated countries would show a higher propensity to the former; indeed, investors in Saudi Arabia welcome the use of Islamic bank financing by listed firms (Almansour & Ongena, 2018). The growth and the resilience of the sector have spurred interest from academics and practitioners, with a sizeable literature on the comparative performance across a multitude of aspects, such as financial risk, profitability and efficiency to name but a few (see Section 2 for a focused review). However, and to the best of our knowledge, academic research has not yet examined the audit market in Islamic banking, despite the importance of auditing in resource allocation and contracting efficiency (DeFond & Zhang, 2014). Besides, it is important to investigate auditing in Islamic banks because of their prominent status in many countries, and their significant differences in terms of financial products and practices, corporate governance structure and ethical considerations. Our paper examines the audit market in Islamic banks. We focus on the pricing and the quality of audit services. First, we examine whether Islamic banks are charged different audit fees compared to their conventional counterparts. Second, we test whether the expertise of auditors in Islamic banking affects the fees that are charged to their clients. Third, we test whether the audit fee differences may be driven by reductions in audit quality, instead of reflecting a differentiated risk profile between banks. We use hand-collected audit data from annual reports for a total of 71 banks operating in Malaysia over the 2010-2017 period. We opt for a single country case study to eliminate heterogeneity in Islamic banking operations that is typical in cross-country designs as argued Electronic copy available at: https://ssrn.com/abstract=3845365 in Alexakis et al. 2019. This heterogeneity may be attributed to differences within the Islamic banking model itself (e.g., permissibility of particular financial products and lines of businesses) or regulatory/supervisory differences manifested across countries (Song & Oosthuizen, 2014). We opt for Malaysia because it is perhaps the most active in promoting Islamic finance, while consistently being one of the big four players therein (alongside Saudi Arabia, UAE and Kuwait) (IFSB, 2020). Our main empirical model is in line with the audit fee literature in the financial industry, see Cullen et al. (2018) and Fields et al. (2004). For robustness purposes we also adopt an alternative model that considers the well-documented differences between the two bank types, most notably financial stability (proxied by the z- score) and technical efficiency (estimated via a stochastic frontier analysis). We find that audit fees are substantially lower in Islamic banks than in conventional banks. Specifically, we document a fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. In addition, our results show that the fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. The results are in line with the view that auditors bear lower risk in Islamic banks than in conventional banks. Lower audit risk can be explained by lower credit and default risk; lower audit risk can also be due to the presence of an additional control on managers, which is imposed by the Shariah Supervisory Board. Although fees are lower in Islamic than in conventional banks, we find no significant differences in audit quality, which we measure through the discretionary loan loss provision, the likelihood of meeting or Single country studies within the Islamic and conventional banking comparative literature are not scarce (Abdul- Majid et al., 2011; Asmild et al., 2019; El-Gamal & Inanoglu, 2005). In particular, the Malaysian Securities Exchange Commission (SEC) has allowed higher percentages of non- permissible income for Islamic investments, in an attempt to boost the investible universe of Shariah -compliant stocks. Additionally, Islamic banks operating in Malaysia adopt financial instruments, whose Shariah conformity has been challenged in the Middle-East and as a consequence these are not valid for use therein. For example, Bai Bithaman Ajil (BBA) that is utilised as a buy-sale property instrument, are not considered Shariah-compliant in the Middle-East (Usmani, 2002). Electronic copy available at: https://ssrn.com/abstract=3845365 beating earnings benchmarks and restatements, between the two types of banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost in the quality of audit services. We contribute to the literature in two ways. First, in contribution to the Islamic/conventional comparative literature (Abedifar et al., 2013; Baele et al., 2014; Izzeldin et al., 2021; Quttainah et al., 2013), we offer the first study to examine the audit market – in particular, the pricing and quality of audit services – between these two bank types. Second, in contribution to the banking audit literature we compare the audit market dynamics across different banking models. Further, we investigate how the expertise of auditors in Islamic banking affects the audit outcomes. Extant research (Cullen et al., 2018; Doogar et al., 2015; Ettredge et al., 2014; Fields et al., 2004; Kanagaretnam et al., 2010, 2011; Masli et al., 2018) has largely focused on the commercial banking model, with alternative banking models (i.e., Islamic banks, community banks) being under researched. The rest of the paper is structured as follows. Section 2 discusses the motivation of the analysis; Section 3 presents the data and methods used; Section 4 comments on the results; Section 5 concludes. 2. Background information and hypothesis development Background information Islamic banking refers to these financial institutions where practices emanating from the Islamic law (Shariah) are accommodated into the business model (Haniffa & Hudaib, 2007). The prohibition of interest and speculative activities, the shunning of investments in industries that are considered unlawful – alcohol, gambling and tobacco to name but a few – as well as investments in complex derivative products, debt instruments and short-selling are some of the Relatedly, general surveys of the literature on the determinants of audit quality and audit fees are contained in DeFond and Zhang (2014) and Hay et al. (2006), respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 most acknowledged restrictions. Consequently, Islamic banks use two types of financial products: equity/participation type and fee-based services. Mudarabah is a commonly used equity/participation type of contract where an investor (usually an Islamic bank) and an entrepreneur (individual or institutional) enter a joint venture with the bank providing the necessary funds, the entrepreneur the know-how, and they agree to share the profits on a pre- determined ratio. Fee-based services include the widely used contracts of Murabahah and Ijarah. Murabahah is in essence a cost-plus-profit sale. The bank arranges to sell a good to a customer at a premium which incorporates risks, costs and a profit margin. Ijarah is a lease contract where the bank leases an asset to an investor (or consumer) and the latter pays fees for utilising the asset. Nevertheless, Islamic banking is itself a topic of great ambiguity. Proponents argue that its unique features and restrictions create a new financial paradigm and enhance ethical investing. Critics argue that the differences between the theoretically envisaged Islamic banking model, and what is typically practiced are substantial; thus Islamic finance is simply conventional finance with Arabic names (Khan, 2010). To their defence they posit that the cornerstone of Islamic finance is equity participation, with profits and losses shared between the contracted parties according to some pre-determined ratio (Usmani, 2002). Yet, equity financing constitutes a small percentage of a typical Islamic bank’s asset portfolio (El-Gamal, 2006; Khan, 2010). Instead, fee-based financial products are the norm, where an “implicit” interest rate is charged that is often highly correlated with the “explicit” interest rate observed in the conventional banking sector. Documented evidence suggest that Islamic banking activities are influenced by the prevailing interest rate in Turkey and Malaysia but not in the GCC countries (Cevik & Charap, 2015; Ergeç & Arslan, 2013; Yusof et al., 2015). Moreover, recent evidence suggests a convergence between the two banking paradigms, notably in countries with high financial development (Izzeldin et al., 2021). Electronic copy available at: https://ssrn.com/abstract=3845365 Despite their restrictions and business model peculiarities, Islamic banks are considered more profitable (Alqahtani et al., 2017; Hasan & Dridi, 2011), featuring superior asset quality and capitalisation (Beck et al., 2013), exhibiting lower risk compared to their conventional counterparts (Abedifar et al., 2013; Baele et al., 2014; Čihák & Hesse, 2010; Pappas et al., 2017), and of higher technical efficiency (Johnes et al., 2014; Mobarek & Kalonov, 2014). This distinct profile is of particular relevance to investors, who can enjoy important diversification benefits, particularly during periods of economic and financial turmoil (Alexakis, Pappas, et al., 2017; Erragragui et al., 2018; Rizvi et al., 2015; Sensoy, 2016; Sorwar et al., 2016); albeit these benefits may depend on cross-country religious restrictions on conventional stock trading (Alhomaidi & Kabir Hassan, 2017). In terms of ownership structure, Islamic banks are typically local, unlisted, featuring a small number of shareholders that are often linked to royal families that are a common feature in these countries. For these reasons it may be plausible that Islamic banks have not been particularly transparent, although in recent years significant steps to revert this tendency have been taken (Ariffin et al., 2007). In terms of corporate governance, Islamic banks maintain a Shariah Supervisory Board (SSB) that works alongside the Board of Directors, but is considered the “Supra Authority” in an Islamic bank (Choudhury & Hoque, 2006). The SSB ensures that products and practices are consistent with the religious guidelines, and ensures that Islamic banks adhere to their societal commitments (Mallin et al., 2014). Thus, the SSB represents an additional internal control mechanism on management relative to conventional banks. Related research has found that a large and independent SSB is beneficial to the financial performance and stability (Farag et al., 2017; Mollah & Zaman, 2015). In particular, the SSB operates as a protective cushion that allows Islamic banks to take higher risk and achieve better For generic recent surveys on Islamic finance literature we direct you to Abedifar et al., (2015), Alzahrani and Megginson (2017), Narayan et al., (2019). For focused recent litetarute reviews on Islamic capital markets and Islamic banking respectively, we direct you to Delle Foglie and Panetta (2020) and Hassan and Aliyu (2018). Electronic copy available at: https://ssrn.com/abstract=3845365 performance (Mollah, Skully, et al., 2017; Uddin et al., 2017). On the one hand a large and active SSB reduces Shariah non-compliance risk (Basiruddin & Ahmed, 2017), but on the other hand it has been linked with a lower bank performance (Nawaz, 2019). Islamic banks have higher board of directors independence, which is documented to be positively linked to capitalisation and to a prudent risk-taking behaviour (Mollah, Hassan, et al., 2017; Vallascas et al., 2017). Hayat and Kabir Hassan (2017) examine the link between higher capitalisation and good governance (Jeitschko & Jeung, 2005), for Islamic and non-Islamic firms and find that the former score higher on well-reputed governance indicator scores. The price that Islamic banks have to pay for the dual-board structure is reflected in their cost efficiency (Uddin et al., 2017), particularly through the increased number of board committees (Alexakis, Al-Yahyaee, et al., 2017). Even though Islamic banks operating in dual- banking countries appear to be unaffected by competition from conventional banks with respect to deposit rate setting (Meslier et al., 2017), it is unknown if this extends to other financial aspects, including profitability and financial stability; or depends on the Islamicity of the country’s population (Rehman & Askari, 2010); or is related to how particular aspects of Islamic banking vary, such as the Zakat implementation (Choudhury & Limodio, 2017). Financial reporting in Islamic banks There is scant research around on financial reporting in Islamic banks, without any contribution, to the best of our knowledge, on auditing. Within the realm of normative research on financial reporting, Abdel Karim (1995) discusses the role of the Financial Accounting Organization for Islamic Banks and Financial Institutions (now Accounting and Auditing Organization for Islamic Financial Institutions), while Baydoun and Willett (2000) and Karim (2001) emphasize the need to adapt and harmonize financial statements to match with the Islamic banks are susceptible to Shariah compliance risk in regard to the conformity of financial products to the Shariah, see Ullah et al. (2018) for an investigation. Electronic copy available at: https://ssrn.com/abstract=3845365 ethical considerations of Islamic banks. Oldon and Zoubi (2008) compare a set of financial ratios of Islamic and conventional banks. Empirical research has mostly focused on earnings management in a comparative setting (Abdelsalam et al., 2016; Elnahass et al., 2018; Lassoued et al., 2018; Quttainah et al., 6 7 2013). Examining the abnormal loan loss provision and loss avoidance, these studies find that Islamic banks exhibit lower propensity to engage in earnings management. In part, this has been attributed to the role of the SSB (Quttainah et al., 2013), as well as the more conservative accounting sentiment (Abdelsalam et al., 2016) inherent in Islamic banks. Islamic banks were early adopters of the expected loss model for loan loss provisions, which is regarded as more proactive than the incurred loss model considering the economic cycle expectations; thus, more appropriate for the equity/participation type of contracts in use by these banks. Relatedly, the study of Elnahass et al. (2018) finds that because of the different loan loss provisioning systems, Islamic banks do not use the loan loss provision for capital or earnings management. Closely related to the literature, a handful of papers also examine the role of religiosity and financial reporting. Besides, it has been documented that religious investors are more risk- averse in general; more so during periods of pronounced religious importance, such as the month of Ramadan (Białkowski et al., 2012; Hilary & Hui, 2009; Taap et al., 2011). Focused in the US, Dyreng et al. (2012) and McGuire et al. (2012) document that earnings management and financial reporting irregularities have lower propensities for firms located in counties with high religious adherence. A different angle is taken by Mallin et al. (2014), who examine CSR activities in Islamic banks. They find that Islamic banks generally engage in a broad range of social activities. Importantly, there is a positive association between CSR disclosure and corporate financial performance. The loan loss provision is one of the key accounting policies for Islamic banks. Accordingly, Elnahass et al. (2014) investigate the value relevance of the loan loss provision in Islamic vs. commercial banks, in a cross- country study. They document that the loan loss provision is value relevant in both Islamic and conventional banks. The discretionary component of the loan loss provision has lower value relevance in Islamic banks than in conventional banks. Electronic copy available at: https://ssrn.com/abstract=3845365 Hypotheses development On the one hand, we expect that audit fees should be lower in Islamic banks than in conventional banks for two reasons. First, audit risk is expected to be lower in Islamic banks than in conventional banks because the former have been shown to exhibit lower credit risk and default risk (Abedifar et al., 2013; Baele et al., 2014; Ongena & Şendeniz-Yüncü, 2011; Pappas et al., 2017; Sorwar et al., 2016). Second, Islamic banks have a dual-board structure with a Shariah Supervisory Board (SSB) working alongside the Board of Directors. Although the primary role of the SSB is to opine on the conformity of the offered products to the Islamic law, it is considered as the “Supra Authority” (Choudhury & Hoque, 2006). The presence and the well-functioning of the SSB in an Islamic bank has been linked to enhanced financial performance (Farag et al., 2017; Mollah & Zaman, 2015) and superior financial stability (Mollah, Hassan, et al., 2017; Mollah, Skully, et al., 2017; Pappas et al., 2017; Uddin et al., 2017). Overall, the existence of the SSB may have a beneficiary impact on audit fees, either indirectly (e.g., through lower financial risk of the institution) or directly (e.g., by acting as an additional layer of control and, hence, reducing audit risk). On the other hand, audit fees might be higher in Islamic than in conventional banks for three, partly related with each other, reasons. First, Islamic banks use specialized financial products, which bear little or no resemblance to conventional products. Some of these products (typically the equity-based ones) are custom made to projects and/or individuals, which may render the auditing process lengthier and more complex. Second, and strictly related to the In particular, Abedifar et al. (2013) find that Islamic banks have lower credit risk than conventional banks. The results are stronger for small, leveraged banks as well as for those operating in countries with more a Muslim population higher than 90%. They also find that the insolvency risk of small Islamic banks is lower than that of small conventional banks, as the former are more capitalized. Relatedly, Baele et al. (2014) document that the default rate of Islamic loans is less than half than that of conventional loans. In line with the view that the clients of Islamic banks have relatively low risk of default, Ongena and Şendeniz-Yüncü (2011) find that Islamic banks mainly have corporate clients that are young, transparent, industry-focused, and have multiple-bank relationships. Using market-based indicators of risk, Sorwar et al. (2016) document a lower market risk for Islamic banks, in particular during the financial crisis. Based on the results of a survival analysis, Pappas et al. (2017) find that Islamic banks are more stable than conventional banks. Electronic copy available at: https://ssrn.com/abstract=3845365 previous point, auditors in Islamic banks may require some additional training and familiarity with the Islamic finance terminology and the contract specifics. This may amount to an additional cost, particularly during the first years of auditing in an Islamic bank and assuming no prior expertise on the auditor’s behalf. It may be expected however, that over time the auditor would have become accustomed to the specifics of Islamic finance, hence any higher audit fees are expected to be only in the short run. Third, the ownership structure of Islamic banks, which are typically owned by a small number of shareholders who are often related to the government and/or royal families, implies a greater opaqueness of the information environment and increases audit risk. Because of the competing arguments, we formulate a nondirectional hypothesis regarding the relationship between Islamic banking and audit fees. HYPOTHESIS 1. Audit fees charged to Islamic banks are not different than audit fees charged to conventional banks. Next, we examine whether the expertise of the auditors in Islamic banking affects the fees which are charged to bank clients. We expect that Islamic banks will be willing to pay more for the services of auditors with higher expertise in Islamic banking, because they are perceived as being more competent. In addition, auditors with higher expertise in Islamic banking are likely to charge higher fees to their Islamic bank clients as a compensation for the time and resources spent on their specialized training. Accordingly, we hypothesise that the audit fees charged to Islamic banks increase as the Islamic banking expertise of the auditors increases. These arguments are in line with those of a branch of research which examines the effects of auditor industry expertise on the audit outcomes. Specifically, many archival and experimental studies document a positive association between industry expertise and audit fees Electronic copy available at: https://ssrn.com/abstract=3845365 (Cahan et al., 2011; Carson, 2009; Casterella et al., 2004; Craswell et al., 1995; DeFond et al., 2000; Ferguson et al., 2003; Francis et al., 2005; Mayhew & Wilkins, 2003). HYPOTHESIS 2. Audit fees charged to Islamic banks increase as the auditor expertise in Islamic banking increases. After having tested whether audit pricing for Islamic banks is different than for conventional banks, we investigate the quality of auditing. To examine audit quality, we focus on the discretionary loan loss provision, the likelihood of meeting or beating earnings benchmarks and restatements. On the one hand, we expect audit quality to be lower for Islamic banks than for conventional banks because, as mentioned when developing H1, the complexity of the audit process is potentially greater for Islamic than conventional banks. This is due to the existence of highly specialized financial products, to the necessity to acquire new skills and to a less transparent information environment. This greater complexity of the audit process may lead to a lower quality of auditing. On the other hand, in Islamic banks there is an additional layer of control on managers, relative to conventional banks. Specifically, the presence of a Shariah Board, which has also been discussed in the development of H1, although its focus is not on financial reporting, may help prevent opportunistic reporting by managers. Since there are competing arguments, we formulate a nondirectional hypothesis regarding the relationship between Islamic banking and audit quality. HYPOTHESIS 3. Audit quality in Islamic banks is not different from conventional banks. It is important to note, however, that other papers do not find a positive association between auditor industry expertise and audit fees (Ferguson et al., 2003; Mayhew & Wilkins, 2003; Minutti-Meza, 2013). Electronic copy available at: https://ssrn.com/abstract=3845365 3. Data and methods Data Our dataset covers the period 2010-2017 and features 14 Islamic and 57 conventional banks that operate in Malaysia. This sample corresponds to all the banks with data available in FitchConnect. Islamic banks represent around 20% of our sample that is consistent with similar studies (Beck et al., 2013; Izzeldin et al., 2021). Financial and accounting data are obtained from the FitchConnect database. Data on audit fees are hand-collected from the annual reports. Methods Main analysis We first examine the Islamic banking effect on audit fees (H1). Hence, we regress the natural logarithm of audit fees, LAF, on an Islamic bank binary dummy. We include a full set of control variables and year fixed effects. For our choice of control variables we are guided by the extant literature on audit fees in the banking industry, in particular the seminal papers of Cullen et al. (2018) and Fields et al. (2004), and data availability. In particular, and to examine audit fees, we estimate the following model: LAF = β + β ΙΒ + β IBCONC + β IBCONC × ΙΒ + γΧ (1) ijt 0 1 it 2 3 jt it it + ε ijt where 𝑖 , 𝑗 , 𝑡 index banks, auditors and years respectively, 𝐹𝐿𝐴 is the natural log of audit fees, 𝐼𝐵 is a binary variable that takes the value one for Islamic banks, zero otherwise; the control variables (𝑋 ) are defined in the Appendix. We base our inference on cluster-adjusted standard errors. The Appendix contains the definitions of the variables used in the empirical models. Electronic copy available at: https://ssrn.com/abstract=3845365 To test H2, we build a measure of expertise in Islamic banking. Expertise is unobservable; therefore, in line with prior auditing research on industry specialization, we calculate a measure of expertise which is based on the fees received from Islamic banks relative to the sum of the fees received from all the bank clients. Specifically, we focus on the variable IBCONC, which is defined at the auditor level as the sum of audit fees from Islamic banks to the total audit fees in a given year. To test whether auditor expertise affects the relation between Islamic banking and audit fees, we include, in equation [1], the interaction term between IBCONC and IB. We also investigate whether differences in audit fees reflect differences in audit quality (H3), which we measure using the discretionary loan loss provision, the likelihood of meeting or beating earnings benchmarks and restatements. First, we examine the discretionary loan loss provision, DLLP, calculated following Kanagaretnam et al. (2010). The discretionary loan loss provision is obtained as the residuals of the equation [2], which relates the loan loss provision scaled by total assets, LLP, to a set of control variables and year fixed effects. Because the loan loss provision can be used to manage the reported performance by banks, the common interpretation in the literature is that the higher the discretionary loan loss provision the lower the quality of auditing. LLP = α + 𝛼 BEGLLA + α LCO + α CHLOANS + α LOANS (2) it 0 1 it 2 it 3 it 4 it + α NPL + α DNPL + ε 5 it 6 it it where BEGLLA is the ratio of the beginning of the period loan loss allowance to beginning of the period total assets; LCO is the ratio of net charge-offs to total assets; change in loans, scaled Alternative measures of audit quality are based on qualified audit opinions. We manually inspected the audit reports of all the observations and we did not find any report in which the auditor state that they have doubts ont he ability of the firm to continue as a “going concern”. Electronic copy available at: https://ssrn.com/abstract=3845365 by total assets, from year t-1 to year t; NPL is the ratio of nonperforming loans to total assets; DNPL is the change in NPL from year t-1 to year t. Our second measure of audit quality is the likelihood of meeting or beating earnings benchmarks by a small amount. We focus on the variable MBE, which is a dummy variable taking value one if the ratio of operating profit to total assets is included in the interval (0;0.005). In untabulated tests we consider an alternative measure of the likelihood of meeting or beating earnings benchmark and obtained similar results. The alternative measure is a dummy variable taking value one if the change in the ratio of operating profit to total assets is included in the interval (0;0.0025). It has been widely documented that managers have incentives to manage earnings to avoid missing earnings benchmarks. Accordingly, the common interpretation is that as the likelihood of (just) meeting or beating earnings benchmarks increases, audit quality decreases. As a third measure of audit quality, we use restatements. We obtain the list of restatements in our sample from FitchConnect and manually inspect the annual reports which contain details on the restatements. We focus on a dummy variable (REST) which indicates whether the restatements which have an effect on the statement of comprehensive income; the results are similar if we include all the restatements in the analysis. Restatements are meant to capture audit failures and they are commonly considered as a direct measure of audit quality (DeFond and Zhang, 2014). We then relate our measures of audit quality (AQ) to the IB dummy, a set of control variables (𝐹 ) and year fixed effects, as shown in equation [3]. AQ = b + b IB + gF + u (3) it 0 1 it it it In further untabulated tests we also included the boundaries of the interval (for both measures) and inference about the coefficient on IB is unchanged. Electronic copy available at: https://ssrn.com/abstract=3845365 The definition of the control variables, which are chosen in a similar way to Kanagaretnam et al. (2010), is contained in the Appendix. Equation (3) is estimated using OLS when the dependent variable is DLLP and using a Probit when the dependent variable is MBE. With both models we use bank cluster-adjusted standard errors. An extended specification For robustness, we use an extended specification to equation [1], which is in line with the banking literature and further accounts for financial stability, technical efficiency, and loan portfolio differences. Our motivation for controlling for these factors is that Islamic banking has been purported to be fundamentally different to conventional practices, with a large strand of the banking literature documenting significant differences in respect to financial risk profile, efficiency, and business model practices. To control for financial stability of the bank we use the popular z-score indicator (Boyd & Runkle, 1993; Laeven & Levine, 2009). The z-score is defined as: ROA + E /TA (4) it it it z − score = it σ(ROA ) it For the calculation of the z-score, ROA is the return on assets, E/TA is the equity to total assets ratio, and σ(ROA) is the standard deviation of ROA computed based on the full dataset. As the z-score is highly skewed we take the natural log. Higher values of the z-score indicate higher financial stability. Technical efficiency is associated with the bank’s ability to obtain maximum output with a given set of inputs. Efficiency can be measured either by using traditional financial ratio analysis (FRA) or by frontier estimation methods. A drawback of financial ratios is that they do not take into consideration the input prices and the output mix and weights of the ratios are selected subjectively (Berger & Humphrey, 1992). Here we estimate the technical efficiency Electronic copy available at: https://ssrn.com/abstract=3845365 (EFF) of each bank using a stochastic frontier approach. We assume the banks act as intermediaries between fund surplus and deficit units, as introduced by Sealey and Lindley (1977) and in line with Casu and Girardone (2010). Hence banks are assumed to produce Loans (y1), Securities (y2) and Other Earning Assets (y3) that constitute the outputs. The input variables are Deposits (x1), Personnel Expenses (x2), Fixed Assets (x3) and Equity (x4), in line with Izzeldin et al. (2021). All monetary variables have been deflated using the GDP deflator. We use the following translog function: M−1 M−1 M−1 (5) y 1 y y mit mit nit ln y = α + ∑ α ln( ) + ∑ ∑ α ln ( ) ln ( ) Mit 0 m mn y 2 y y Mit Mit Mit m=1 m=1 n=1 K K K + ∑ β ln x + ∑ ∑ β ln x ln x k kit kl kit lit k=1 k=1 l=1 K M−1 mit + ∑ ∑ δ lnx ln( ) + ε km kit it Mit k=1 m=1 where the error term 𝜀 is split into two components, i.e. 𝜀 = 𝑣 − 𝑢 where 𝑣 represents 𝑖𝑡 𝑖𝑡 𝑖𝑡 𝑖𝑡 𝑖𝑡 statistical noise, i.e., 𝑣 ~𝑁 (0, 𝜎 ), and 𝑢 represents the efficiency of bank 𝑖 in time period 𝑖𝑡 𝑣 𝑖𝑡 + 2 13 𝑡 and is distributed as half-normal i.e. 𝑢 ~𝑁 (𝜇 , 𝜎 ), following Aigner et al. (1977). 𝑖𝑡 To capture the diversity in the activities of each bank, we use the income diversity (ID) that is defined as: Net interest income− Noninterest income (6) ID = 1 − | | it Total income Higher values show a more diversified stream of income. In addition, banks may have different specialisation in their loan portfolios, which typically comprise of credit card loans, manufacturing loans, loans to small & medium enterprises, corporate loans, property The average efficiency for Islamic banks is 0.752 and for conventional banks is 0.627, a statistically significant difference. Islamic banks do not charge/receive interest; in their case the “interest rate” is reflective of the profit share ratios used in the asset and liability side of their balance sheet. Electronic copy available at: https://ssrn.com/abstract=3845365 development loans, agricultural loans, commercial property loans and mortgages. We extract two common factors (F1 and F2) within the loan portfolio using Principal Component Analysis (PCA). 4. Results Descriptive statistics Table 1 summarizes the main descriptive statistics for the key variables in our analysis for Islamic and conventional banks. A first inspection of the table suggests notable differences between the two bank types with regards to bank size, capitalisation, funding mode and operations, profitability and cost efficiency. In particular, Islamic banks appear to be smaller on average in terms of total assets compared to conventional banks ($8.52 bil. vs $14.13 bil.), of lower capitalization ratio (CAPRATIO: 12.77 vs 25.14), engage less in securities (SECURITIES: 0.18 vs 0.26), less profitable (EBTP: 1.51 vs 7.82), of lower liquidity despite their business model restrictions on use of debt instruments (LIQUIDITY: 8.14 vs 10.64) and with higher cost efficiency ratios (COSTTOINCOME: 49.24 vs 55.00). Most of both Islamic and conventional banks are audited by BIG4 audit firms. In addition, average fees are lower in Islamic than in conventional banks ($0.68 mil. vs $0.75 mil.); the measures of audit quality (DLLP, MBE, REST) are similar in the two subsamples. [Table 1 around here] Table 2 presents the Pearson correlations for the main variables used in the audit fee model. Interestingly, the correlation between audit fees and the dummy for Islamic banking is negative and significant (9.6%). The correlations for the control variables used in the audit quality model are untabulated. It is worthwhile to note the correlation between each of our audit The two retained factors account for around 26.4% of the variance and are reasonably reflective of return (F1) and risk (F2). These results are omitted for brevity and are available upon request. Electronic copy available at: https://ssrn.com/abstract=3845365 quality measures (discretionary loan loss provision, DLLP; likelihood of meeting or beating earning benchmarks, MBE; restatements, REST) and the dummy for Islamic banking is insignificantly different from zero. [Table 2 around here] Islamic banking, audit fees and audit quality The results of our main model on audit fees are reported in Table 3. The coefficient on the dummy for Islamic banks is negative and highly significant, suggesting that there is a fee discount for Islamic banks. H1, which is formulated in nondirectional form, is not confirmed. This result is consistent the view that audit risk is lower in Islamic banks than in conventional banks. Lower audit risk can be explained by lower credit and default risk; lower audit risk can also be due to a lower probability of fraud or accounting misstatements because of the greater emphasis on ethical considerations. The economic magnitude of the effect is of Islamic banking on audit fees is strong. Specifically, the results imply that, after controlling for the determinants of audit fees, there is a fee discount for Islamic banks of approximately 50%. [Table 3 around here] Next, we investigate whether the expertise of the auditors in Islamic banking affects the pricing of auditing services. The last column of Table 3 show that the coefficient on the interaction terms between IB and our measure of expertise in Islamic banking, IBCONC, is positive and highly significant. These findings suggest that, consistent with H2, fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. The results are in line with the view that auditors with higher expertise in Islamic banking are perceived as being more competent by Islamic bank clients; therefore, they can charge higher We also calculated an alternative measure of Islamic banking expertise, which is based on the total assets of the clients. The alternative measure is defined as: (Total assets of Islamic bank clients)/ (Total assets of all bank clients). The results, which are untabulated, are qualitatively unchanged relative to those obtained with IBCONC. Electronic copy available at: https://ssrn.com/abstract=3845365 fees to these clients. The results are also consistent with the branch of auditing literature which documents a positive association between industry expertise and audit fees. We also examine whether differences in audit prices reflect differences in audit quality, which we measure using the discretionary loan loss provision (DLLP), the likelihood of meeting or beating earnings benchmarks (MBE) and restatements (REST). The results of our audit quality models are reported in Tables 4 and 5. We note that, similar to Kanagaretnam et al. (2010), the control variables in Table 4 are different from those used in Table 5. In Table 4, we examine DLLP. Both when using all the values of DLLP (column 2) and when positive values of DLLP (column 5), the coefficient on the dummy for Islamic banking is positive, but it is not significantly different from zero. In Table 5, we present the results for MBE (columns 2) and REST (column 5). These results are in line with those observed in Table 4. H3, which is formulated in nondirectional form, is confirmed: after controlling for its cross-sectional determinants, audit quality does not differ between Islamic and conventional banks. Therefore, importantly, the fee discount for Islamic banks comes at no cost for the quality of audit services. [Table 4 around here] [Table 5 around here] The insignificant difference in audit quality is in line with the view that the two competing effects of Islamic banking offset each other. Specifically, on the one hand, the complexity of the audit process is potentially greater for Islamic than conventional banks. This As a further alternative proxy for industry expertise, we also defined, for each year, the Islamic banking industry leader as the auditor with the highest amount of fees received from Islamic banks during the year. Accordingly, we built the dummy variable IBLEAD, which takes value one for Islamic banks which are audited by the industry leader. We replicated the analysis in the last column of Table 3 using IBLEAD instead of IBCONC. The results, which are untabulated, show that the coefficients on IBLEAD and on the interaction term between IBLEAD and IB are insignificantly different from zero. We also replicated the analysis interacting IB with all the control variables. Inference regarding the IB dummy variable is unchanged. Electronic copy available at: https://ssrn.com/abstract=3845365 is due to the existence of highly specialized financial products, to the necessity to acquire new skills and to a less transparent information environment. The higher complexity may lead to lower audit quality for Islamic banks. On the other hand, the presence of an additional layer of control on managers, which is represented by the Shariah Board, may help to constrain managers’ reporting choices and to increase audit quality. In the columns (3) and (6) of Tables 4 and 5, we examine the effect of Islamic banking expertise on audit quality. We find that the coefficient on the interaction terms between IB and our measure of Islamic banking expertise is insignificantly different from zero. Therefore, the effect of IB on audit quality is not affected by the expertise of the auditors in Islamic banking. It is also interesting to notice that, in column (6) of Table 5, the coefficient on IBCONC is significant and negative. This indicates that restatements are (weakly) negatively associated with auditor expertise in Islamic banking. Additional analyses on audit pricing We run two additional analyses on audit pricing. First, we examine the results in selected subsamples. Second, we estimate an extended model for audit fees (as described in Section 3.2.2.). Table 6, panels A-E presents the results on sample splits. We re-estimate the main audit fee model using median sample splits on five variables: size, which is measured as total assets; and four variables used in the extended audit fee model, financial stability, technical efficiency and the two principal components of the loan portfolio. The purpose of these tests is to examine the cross-sectional variation of our results and investigate the robustness of our conclusions. Electronic copy available at: https://ssrn.com/abstract=3845365 The models contain the full set of control variables, but, for brevity, in the table we only report the estimated IB coefficient and robust t-statistic in brackets. [Table 6 around here] A cursory inspection of the results shows that the negative coefficient on the IB dummy corroborates the main conclusions from the paper, whereby Islamic banks exhibit lower audit fees. The differences in the coefficient on IB across the subsamples are not significantly different from zero. Overall, these findings corroborate the main results. In Table 7 we present the results of the extended audit fee model. The results confirm the audit fee discount for Islamic banks of the main part of the paper. The additional control variables appear to be only weakly related to audit fees. Specifically, F1 and F2 have insignificant coefficients. The ZSCORE, our proxy for financial instability has a positive and significant coefficient in the second column. A positive coefficient is consistent with the interpretation that higher fees are required if the risk of insolvency increases. In addition, EFF, our measure of technical efficiency has a negative and significant coefficient in the first column. A negative coefficient is in line with the view that auditors perceive less efficient banks as riskier. The results in the last column also confirm those presented in the main analysis. Specifically, the fee discount for Islamic banks is lower as the Islamic banking expertise of the auditors increases. [Table 7 around here] We note that the number of observations in the High and Low portfolios are different because of different availability of some of the control variables in the two subsamples. In further untabulated tests we also replicated the analysis excluding the conventional banks which are listed, and the results are similar to the main analysis. Electronic copy available at: https://ssrn.com/abstract=3845365 5. Conclusions In this paper, we investigate the audit market in Islamic banks. Despite the increasing importance of Islamic banking in the global finance industry, only scant research examines financial reporting of Islamic banks. To our knowledge, academic research has not yet examined the role of auditors in Islamic banking. We find an audit fee discount of approximately 50% for Islamic banks relative to conventional banks, after controlling for the cross-sectional determinants of fees. Our results also show that the fees charged to Islamic banks increase as the expertise of the auditors in Islamic banking increases. We interpret these results as evidence that auditors bear lower risks in Islamic banks than in conventional banks. This lower audit risk in Islamic banks can be explained by lower credit and default risk; it can also be due to the presence of an additional layer of control on managers, which is represented by the Shariah Supervisory Board. 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TRANSDEP The ratio of transaction accounts (deposits minus saving and term deposits) to total deposits SECURITIES The ratio of investment security assets to total assets COMMLOAN The ratio of commercial loans to total loans MTGLOAN The ratio of loans secured by a mortgage to total loans INTANG The ratio of intangible assets to total assets CHGOFF The ratio of net charge-offs to total loans IMPLOAN The ratio of impaired loans to total loans COSTTOINCOME The ratio of total expenses divided by total income BIG4 An indicator variable, 1 = the auditor is one of the BIG4; zero otherwise INTDERIV The ratio of the notional value of interest rate derivatives to total assets LISTED An indicator variable, 1 = Listed bank; zero otherwise Electronic copy available at: https://ssrn.com/abstract=3845365 B. Audit quality model LLP The ratio of the loan loss provision to total assets BEGLLA The ratio of the beginning of the period loan loss allowance to beginning of the period total assets. LCO The ratio of net charge-offs to total assets CHLOANS The change in LOANS from year t-1 to year t LOANS The ratio of loans to total assets NPL The ratio of nonperforming loans to total assets DNPL The change in NPL from year t-1 to year t DLLP Discretionary loan loss provision (see Section 3.2.1) MBE An indicator variable, 1 = (Operating profit)/ (Total assets) in the interval (0;0.005); zero otherwise. REST An indicator variable, 1 = The accounts have been restated (and the restatement has an effect on the statement of comprehensive income); zero otherwise IB An indicator variable, 1 = Islamic bank; zero otherwise BIG4 An indicator variable, 1 = the auditor is one of the BIG4 LTA Natural logarithm of total assets GROWTH The change in total assets from year t-1 to year t, divided by total assets in year t-1. PASTLLP The LLP in year t-1 ALLOW The ratio of loan loss allowance to beginning of the period total assets CF The change in the ratio earnings before taxes and loan loss provisions to beginning of the period total assets from year t-1 to year t EBTP The ratio earnings before taxes and loan loss provisions to beginning of the period total assets LISTED An indicator variable, 1 = Listed bank; zero otherwise C. Additional variables IB An indicator variable, 1 = Islamic bank; zero otherwise IBCONC An auditor/year specific variable, which is obtained as: (Audit fees from Islamic banks)/ (Total fees from bank clients) EQUITY The ratio of equity to total assets LIQUID The ratio of liquid assets to total assets ZSCORE An indicator of financial stability (see Section 3.2.2) EFF An indicator of technical efficiency (see Section 3.2.2) F1, F2 First two principal components for loan portfolio specialization (see Section 3.3.2) Notes: All data, except audit fees (which are hand-collected), are sourced from FitchConnect. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 1 Descriptive statistics All banks Conventional Islamic Mean SD Mean SD Mean SD LAF -0.3092 1.0532 -0.2884 1.1484 -0.3793 0.6357 LTA 9.4609 1.8046 9.5564 1.9595 9.0505 0.8659 LOSS 0.0372 0.1894 0.0456 0.2088 0.0090 0.0949 FOREIGN 0.2500 0.4335 0.2788 0.4490 0.1532 0.3618 CAPRATIO 22.7002 35.1716 25.1482 38.7705 12.7751 6.2163 TRANSDEP 0.2754 0.2813 0.2833 0.2885 0.2499 0.2560 SECURITIES 0.2467 0.2078 0.2653 0.2263 0.1831 0.1040 COMMLOAN 0.0110 0.0536 0.0091 0.0408 0.0171 0.0820 MTGLOAN 0.1990 0.2272 0.1821 0.2381 0.2528 0.1789 INTANG 0.0068 0.0153 0.0082 0.0169 0.0019 0.0050 CHGOFF 0.4383 1.2386 0.4269 1.3530 0.4847 0.5802 IMPLOANS 3.6472 8.1529 3.7517 8.9334 3.2958 4.6700 COSTTOINCOME 53.8618 29.0821 55.0009 31.1591 49.2433 17.7958 INTDERIV 0.0141 0.0366 0.0175 0.0408 0.0022 0.0053 LISTED 0.2190 0.4140 0.2842 0.4516 0.0000 0.0000 ZSCORE 36.3477 34.7540 36.6515 34.5981 35.1159 35.5441 EFF 0.6534 0.2109 0.6223 0.2168 0.7607 0.1453 F1 -0.0618 0.7949 -0.0791 0.8431 -0.0067 0.6173 F2 -0.0547 0.7239 -0.0152 0.7404 -0.1805 0.6560 DLLP 0.0000 0.0031 -0.0001 0.0030 0.0003 0.0033 MBE 0.0744 0.2627 0.0697 0.2550 0.0901 0.2876 REST 0.0909 0.2878 0.0831 0.2764 0.1171 0.3230 BIG4 0.8988 0.3020 0.9008 0.2993 0.8919 0.3119 GROWTH 0.1068 1.0279 0.1312 1.1649 0.0230 0.1290 PASTLLP 0.0020 0.0037 0.0016 0.0035 0.0032 0.0040 CF -0.0020 0.0844 -0.0023 0.0964 -0.0010 0.0066 ALLOW 0.0123 0.0175 0.0112 0.0168 0.0165 0.0195 EBTP 0.0634 0.0977 0.0782 0.1072 0.0151 0.0108 LIQUID 10.0725 12.1670 10.6453 13.1186 8.1478 7.9472 EQUITY 21.9288 23.0365 24.7261 24.4120 10.5875 10.3723 IB 0.2293 0.4208 0.0000 0.0000 1.0000 0.0000 IBCONC 0.1350 0.1054 0.1245 0.1015 0.1704 0.1111 Notes: The table reports descriptive statistics for the main variables in the analysis. Monetary values are expressed in USD millions. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 2 Cross-correlations 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 2 0.604 3 -0.100 -0.287 4 -0.171 -0.224 0.039 5 -0.221 -0.486 0.346 0.112 6 -0.066 -0.078 0.062 0.270 -0.015 7 -0.128 -0.150 -0.078 -0.220 0.246 -0.090 8 0.071 0.046 0.014 -0.053 -0.069 -0.079 -0.078 9 0.297 0.475 -0.156 -0.046 -0.243 -0.081 -0.256 0.168 10 0.010 0.031 0.041 -0.282 0.037 -0.200 0.230 0.004 -0.153 11 0.004 0.078 0.054 -0.039 -0.145 0.081 -0.032 -0.016 -0.001 -0.035 12 -0.020 -0.180 0.164 -0.139 0.136 -0.061 0.243 -0.005 -0.225 0.027 0.178 13 -0.206 -0.464 0.368 0.107 0.476 0.073 0.029 -0.044 -0.213 0.206 -0.021 0.025 14 0.062 -0.061 0.088 -0.213 0.147 -0.111 0.084 0.101 0.031 0.228 0.120 0.169 0.049 15 0.020 -0.122 -0.020 0.246 -0.022 0.413 0.071 -0.072 -0.125 -0.128 -0.009 -0.124 0.087 -0.062 16 0.179 0.434 -0.043 -0.329 -0.181 -0.195 0.017 0.023 0.148 0.233 0.045 -0.093 -0.090 0.024 -0.146 17 -0.096 0.092 -0.085 -0.165 -0.188 -0.051 -0.197 0.073 0.137 -0.196 0.046 -0.032 -0.107 0.013 -0.197 -0.286 18 0.019 0.054 -0.020 0.240 -0.010 0.103 -0.104 -0.062 -0.112 -0.181 -0.015 0.092 -0.067 -0.305 -0.070 -0.207 0.190 19 -0.081 -0.120 0.217 0.120 0.060 0.077 -0.155 -0.016 -0.034 -0.031 -0.109 -0.040 -0.006 -0.133 0.070 -0.035 0.081 0.120 20 -0.140 -0.240 -0.062 0.148 0.016 0.122 -0.029 0.013 -0.133 0.059 0.005 -0.066 0.243 0.041 0.160 -0.082 0.038 0.084 0.161 21 0.028 0.100 -0.069 -0.112 -0.031 -0.144 0.096 -0.046 -0.073 0.115 0.077 0.088 -0.007 0.093 -0.034 0.093 0.006 0.018 0.002 0.000 Notes: This table reports Pearson correlations for selected variables. Definition of variables: (1) LAF; (2) LOSS; (3) LTA; (4) FOREIGN; (5) CAPRATIO; (6) TRANSDEP; (7) SECURITIES; (8) COMMLOAN; (9) MTGLOAN; (10) INTANG; (11) CHGOFF; (12) IMPLOANS; (13) COSTTOINCOME; (14) BIG4; (15) INTDERIV; (16) LISTED; (17) IB; (18) IBCONC; (19) DLLP; (20) MBE; (21) REST. We report in bold the coefficients which are significant at the 10%. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 3 Audit fees and Islamic banking (1) (2) (3) *** *** *** LTA 0.473 0.498 0.493 [5.91] [6.83] [6.61] LOSS 0.184 0.143 0.149 [1.30] [0.88] [0.92] *** *** FOREIGN -0.140 -0.334 -0.332 [-1.07] [-2.91] [-3.06] CAPRATIO 0.002 0.001 0.001 [0.98] [0.37] [0.44] TRANSDEP -0.219 -0.224 -0.260 [-1.07] [-1.38] [-1.57] ** ** SECURITIES -0.495 -0.671 -0.776 [-1.51] [-2.18] [-2.48] COMMLOAN -0.347 -0.275 -0.282 [-0.72] [-0.66] [-0.70] MTGLOAN -0.122 -0.134 -0.109 [-0.27] [-0.33] [-0.28] INTANG -1.264 -4.607 -4.822 [-0.25] [-0.88] [-0.93] CHGOFF -0.047 -0.032 -0.034 [-1.09] [-0.92] [-0.96] ** * IMPLOANS 0.015 0.012 0.012 [2.23] [1.67] [1.64] * * COSTTOINCOME 0.004 0.005 0.004 [1.65] [1.89] [1.70] BIG4 0.163 0.185 0.240 [0.94] [1.11] [1.30] ** INTDERIV 3.298 1.659 1.792 [2.16] [1.22] [1.31] * * LISTED -0.306 -0.633 -0.647 [-0.93] [-1.88] [-1.90] *** *** IB -0.706 -1.069 [-4.42] [-4.50] IBCONC -0.373 [-0.45] ** IB X IBCONC 2.161 [2.26] *** *** *** CONSTANT -4.650 -4.479 -4.360 [-6.52] [-7.03] [-6.87] Year FE Yes Yes Yes Observations 382 382 382 Adjusted R-squared 0.456 0.515 0.522 *** ** * Notes: The dependent variable is LAF. Standard errors are clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 4. Audit quality and Islamic banking: discretionary loan loss provision + + + DLLP DLLP DLLP DLLP DLLP DLLP (1) (2) (3) (4) (5) (6) BIG4 0.000 0.000 0.000 0.000 0.000 0.000 [-0.17] [-0.17] [-0.07] [0.67] [0.50] [0.46] *** *** *** ** ** ** LTA -0.000 -0.000 -0.000 -0.000 -0.000 -0.000 [-3.82] [-3.58] [-3.58] [-2.22] [-2.25] [-2.42] GROWTH 0.001 0.001 0.001 0.001 0.001 0.001 [1.16] [1.13] [1.18] [1.53] [1.50] [1.44] *** *** *** *** *** *** PASTLLP 0.330 0.327 0.318 0.248 0.230 0.210 [5.37] [5.30] [4.89] [3.69] [3.48] [2.85] * * * ** ** ** EBTP -0.003 -0.003 -0.003 -0.008 -0.008 -0.008 [-1.89] [-1.76] [-1.81] [-2.48] [-2.28] [-2.47] * * * LISTED 0.001 0.001 0.001 0.001 0.001 0.001 [1.71] [1.73] [1.83] [1.24] [1.41] [1.51] IB 0.000 0.000 0.001 0.002 [0.61] [0.64] [1.25] [1.58] IBCONC 0.001 0.003 [0.76] [1.22] IB X IBCONC -0.001 -0.007 [-0.42] [-1.61] * * ** ** *** CONSTANT 0.002 0.002 0.002 0.004 0.004 0.004 [1.71] [1.73] [1.62] [2.56] [2.59] [2.68] Year FE Yes Yes Yes Yes Yes Yes Observations 279 279 279 122 122 122 Adjusted R-squared 0.168 0.166 0.161 0.231 0.238 0.237 Notes: The dependent variable is DLLP (all values) in columns (1)-(3) and DLLP (positive values) in columns *** ** * (4)-(6). We include year fixed effects. Standard errors are clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 5 Audit quality and Islamic banking: Earnings benchmarks and restatements MBE MBE MBE REST REST REST ** ** ** BIG 0.104 -0.036 0.127 -2.624 -2.516 -2.701 [0.06] [-0.02] [0.08] [-2.39] [-2.43] [-2.37] *** *** *** LTA -1.259 -1.467 -1.448 0.228 0.169 0.150 [-3.00] [-2.78] [-2.66] [0.91] [0.61] [0.52] GROWTH 0.747 0.881 0.892 -0.957 -1.526 -1.998 [0.67] [0.75] [0.76] [-0.80] [-1.19] [-1.39] CF 0.356 0.315 0.155 -0.792 -1.182 -0.821 [0.20] [0.20] [0.09] [-0.23] [-0.39] [-0.29] ALLOW -50.003 -46.583 -49.040 3.276 11.748 14.468 [-1.36] [-1.33] [-1.26] [0.13] [0.62] [0.87] * * * LEV -0.065 -0.068 -0.065 0.003 -0.003 -0.007 [-1.73] [-1.91] [-1.85] [0.10] [-0.13] [-0.29] LOANS 1.452 0.647 0.464 -1.003 -2.023 -1.296 [0.99] [0.41] [0.26] [-0.71] [-1.28] [-0.75] *** *** *** EBTP -18.956 -15.696 -15.689 -23.813 -18.029 -18.757 [-1.57] [-1.32] [-1.34] [-2.90] [-2.65] [-2.69] * * LISTED -0.673 -0.440 -0.424 1.361 1.969 1.688 [-1.08] [-0.60] [-0.60] [1.65] [1.95] [1.36] IB 1.068 1.075 1.291 0.182 [0.85] [0.69] [1.52] [0.12] IBCONC 2.336 -6.580 [1.17] [-1.73] IBxIBCONC 0.148 7.140 [0.03] [1.26] *** ** ** CONSTANT 9.006 10.560 10.005 -1.248 -1.126 -0.309 [2.70] [2.57] [2.39] [-0.46] [-0.42] [-0.11] Year FE Yes Yes Yes Yes Yes Yes Observations 286 286 286 286 286 286 Pseudo R-sq. 0.257 0.267 0.274 0.220 0.239 0.258 Notes: The dependent variable is MBE (likelihood of meeting or beating earnings benchmarks) in columns (1)-(3) and REST (restatements) in columns (4)-(6). We include year fixed effects. Standard errors are *** ** * clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 6 Audit fees and Islamic banking: sample splits analysis High Low Panel A: Size ** ** IB -0.500 -0.521 [-2.08] [-2.66] Year FE Yes Yes Observations 223 158 Adj R-squared 0.510 0.463 Chi-sq stat 0.01 Panel B: Financial stability * *** IB -0.618 -0.728 [-1.95] [-4.95] Year FE Yes Yes Observations 195 186 Adj R-squared 0.649 0.571 Chi-sq stat 0.140 Panel C: Technical efficiency *** *** IB -0.891 -0.564 [-4.36] [-3.13] Year FE Yes Yes Observations 166 164 Adj R-squared 0.547 0.505 Chi-sq stat 1.880 Panel D: F1 *** ** IB -0.736 -0.504 [-3.78] [-2.05] Year FE Yes Yes Observations 207 175 Adj R-squared 0.494 0.413 Chi-sq stat 0.790 Panel E: F2 * *** IB -0.475 -0.749 [-2.00] [-3.62] Year FE Yes Yes Observations 200 182 Adj R-squared 0.506 0.550 Chi-sq stat 1.06 Notes: Median sample splits based on total assets (Panel A), financial stability (Panel B), technical efficiency (Panel C), and the two principal components of the loan portfolio (Panels D and E) are reported with the main and extended models of the main paper re-estimated. All control variables are included but are omitted from the table for brevity. The Chi-sq statistic is for the equality of the IB coefficient between the two sample splits. Standard errors are *** ** * clustered by bank. , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365 TABLE 7 Audit fees and Islamic banking - extended model (1) (2) (3) *** *** *** LTA 0.518 0.512 0.498 [6.18] [6.78] [6.42] LOSS 0.033 -0.045 -0.021 [0.19] [-0.23] [-0.11] *** *** FOREIGN -0.162 -0.311 -0.313 [-1.23] [-2.66] [-2.74] CAPRATIO -0.001 -0.002 -0.002 [-0.23] [-0.56] [-0.54] TRANSDEP -0.138 -0.165 -0.180 [-0.63] [-0.97] [-1.05] SECURITIES -0.086 -0.536 -0.687 [-0.22] [-1.55] [-1.90] COMMLOAN -0.467 -0.057 -0.011 [-1.20] [-0.16] [-0.03] MTGLOAN 0.334 0.322 0.299 [0.46] [0.49] [0.46] INTANG -1.252 -4.765 -4.899 [-0.25] [-0.89] [-0.93] CHGOFF -0.072 -0.066 -0.067 [-1.46] [-1.60] [-1.61] ** ** ** IMPLOANS 0.016 0.015 0.015 [2.01] [2.01] [2.00] COSTTOINCOME 0.005 0.007 0.006 [1.37] [1.63] [1.35] BIG4 0.136 0.149 0.220 [0.83] [0.93] [1.21] INTERIV 2.291 1.468 1.700 [1.40] [1.00] [1.16] ** ** LISTED -0.430 -0.739 -0.757 [-1.24] [-2.07] [-2.11] * ** ZSCORE 0.005 0.005 0.006 [1.60] [1.99] [2.20] EFF -0.607 0.010 0.098 [-1.73] [0.03] [0.28] F1 -0.035 -0.068 -0.063 [-0.34] [-0.67] [-0.61] F2 0.153 0.112 0.092 [1.07] [0.86] [0.71] *** *** IB -0.730 -1.161 [-3.70] [-4.18] IBCONC -0.394 [-0.48] ** IB x IBCONC 2.486 [2.45] *** *** *** CONSTANT -5.374 -5.022 -4.858 [-6.78] [-7.29] [-7.08] Year FE Yes Yes Yes Observations 331 331 331 Adj R-squared 0.480 0.529 0.538 Notes: The table reports the results for the extended audit fee model see more details in section 3.2.2. The dependent variable is LAF. Standard errors are clustered by bank. *** ** * , , indicate statistical significance at the 1%, 5%, 10%, respectively. Electronic copy available at: https://ssrn.com/abstract=3845365

Journal

ARN Conferences & Meetings – SSRN

Published: Aug 6, 2021

Keywords: Islamic banking, audit fees, audit quality

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