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Do Former Auditors on the Audit Committee Constrain Earnings Management? Evidence from the Banking Industry Kim Ittonena,*, Per C. Tronnesb,**, Sami Vähämaac,*** a Hanken School of Economics, Department of Accounting b University of New South Wales, School of Accounting c University of Vaasa, Department of Accounting and Finance December 21, 2017 Abstract This paper examines whether former auditors on the audit committee constrain earnings management in the banking industry. Given the complexity and the size of banking organizations, it can be argued that the audit committees of large banks should possess a higher level of financial expertise than stipulated by the regulatory requirements in order to successfully monitor the financial reporting process. Using data on large publicly traded U.S. banks, we document a negative association between earnings management and the presence of audit committee directors with professional auditing experience. Specifically, our empirical findings indicate that banks with former auditors on the audit committee have lower levels of income-increasing as well as absolute discretionary loan loss provisions. We further document that the constraining effect of former auditors on earnings management is strongest for banks in which the former auditors on the audit committee have not been affiliated with the bank’s current audit firm. Overall, our results suggest that audit committee directors with professional auditing experience may improve financial reporting quality in the financial industry. Keywords: Audit committees, former auditors, certified public accountants, discretionary loan loss provisions, earnings management, banks

We would like to thank Kelly Carter, Rebel Cole, Charles Piot, Jukka Sihvonen, and seminar and conference participants at Freie Universität Berlin, Pablo de Olavide University, the University of Vaasa, the EARNet Symposium, and the 55th Annual Meeting of the Southern Finance Association for valuable comments and suggestions. K. Ittonen and S. Vähämaa gratefully acknowledge the financial support of the Academy of Finland. Part of this paper was written while S. Vähämaa was visiting the Alliance Manchester Business School at the University of Manchester. * Address: Hanken School of Economics, Department of Accounting, P.O. Box 479, FI-00101 Helsinki, Finland; Tel.: +358 29 431 3786; E-mail address: [email protected] ** Address: University of New South Wales, School of Accounting, UNSW Sydney NSW 2052, Australia. Tel.: +61 2 9385 5823; E-mail address: [email protected] *** Address: University of Vaasa, Department of Accounting and Finance, P.O. Box 700, FI-65101 Vaasa, Finland; Tel.: +358 29 449 8455; E-mail address: [email protected]

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I. INTRODUCTION

This paper examines whether the presence of former auditors on the audit committee constrains earnings management in the banking industry. The most recent financial crisis has highlighted the fact that the financial statements of large banks are aggregates of complex transactions and instruments and that the valuation of assets and liabilities involves a substantial amount of judgment from the bank’s top management. The complexity and required managerial judgments are examples of “the nature of the industry” that provide bank managers with an opportunity to bias financial statements if they have the incentives and their firm’s internal controls are ineffective (AICPA, 2002). The most prominent component involving considerable managerial discretion in banks’ income statements is the recognition and recording of loan loss provisions (e.g., Ahmed et al. 1999, Leventis et al. 2011, Olszak et al. 2017). Prior studies have suggested that loan loss provisions are used by bank managers to influence earnings when internal controls are weak and when managers have strong personal incentives for using accounting discretion (see e.g, DeBoskey and Jiang 2012, Kanagaretnam et al. 2010, Kanagaretnam et al. 2004, Wahlen 1994, Fonseca and Gonzales 2008). The audit committee is responsible for reviewing and monitoring the firm’s financial reporting process and internal controls, and for ensuring the overall objectivity of financial reporting (SEC 2003, Caskey et al. 2010). Recent regulatory reforms have imposed strict requirements on the composition of the audit committee and have further emphasized the committee’s monitoring responsibilities over financial reporting. Previous studies have documented that the level of financial expertise on the audit committee is reflected in the committee’s monitoring effectiveness and the quality of the firm’s financial reporting (Abbott,

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Parker, and Peters 2004, Mangena and Pike 2005, Carcello et al. 2011, Krishnan and Visvanathan 2008, Dhaliwal et al. 2010, DeFond et al. 2005, Naiker and Sharma 2009). In this paper, we hypothesize that former auditors on the audit committee may influence the processes, activity and role of the audit committee (Beattie, Fearnley and Hines 2012). In particular, we expect that former auditors on the audit committee improve the financial reporting quality of financial institutions by constraining the use of discretionary loan loss provisions. Given the complexity and the sheer size of the entities, we posit that the audit committee members of banks should possess a higher level of financial expertise than stipulated by the regulatory requirements in order to successfully monitor the financial reporting process. Specifically, we focus on the directors who serve on the audit committee and hold a Certified Public Accountant (CPA) qualification. These directors with professional auditing experience should arguable have a substantial amount of education and on-the-job experience as well as a profound understanding of auditing, internal control, and financial reporting processes. When acting as audit committee members, former auditors are likely to evaluate internal controls and managerial assertions more skeptically and be generally more aware of managers’ incentives for earnings management. Hence, we expect to find a negative association between earnings management and the presence of directors with professional auditing experience on the bank’s audit committee. The banking industry provides an expedient context for a study on the role of former auditors for a number of reasons. First, focusing on a single industry provides control over other determinants of cross-sectional differences in earnings management (Kanagaretnam et al. 2010) and the complex nature of financial accounting in the banking industry involves a substantial amount of managerial discretion and judgment. Second, due to the nature of the business and the

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economic and systemic importance of banks, this industry is intensively followed by investors and heavily regulated and monitored by bank supervision authorities, deposit insurers, and central banks to ensure trustworthiness of financial institutions (see e.g., Bai and Elyasiani 2013, de Haan and Vlahu 2016). For this reason, misstating the financial position or the performance of a bank could have serious consequences for the economy, investors, depositors, and overall societal well-being. Third, the complexity, visibility, and important societal role of banks intensify the role of effective audit committee monitoring, and consequently, increase the competence demands of the directors who serve as members of the audit committee. Therefore, we argue that the audit committee members of large banks should possess financial expertise above and beyond the minimum regulatory requirements. We empirically examine the association between earnings management and the presence of former auditors on the audit committee using a sample of large publicly traded U.S. banks included in the S&P 500, S&P MidCap 400, and S&P SmallCap 600 indices. Our sample consists of 78 individual banks and 612 firm-year observations over the period 2004–2012. Following the prior banking literature (e.g., Kanagaretnam et al. 2010, DeBoskey and Jiang 2012), we measure the extent of earnings management with discretionary loan loss provisions. We document a negative association between earnings management and the presence of former auditors on the bank’s audit committee. Specifically, the results indicate that banks with former auditors on the audit committee have lower levels of income-increasing as well as absolute discretionary loan loss provisions. Our empirical findings also indicate that the constraining effect of former auditors is strongest for banks in which the ex-auditors on the audit committee have not been affiliated with the bank’s current audit firm. These main results hold in a number of robustness checks. Furthermore, our additional tests suggest that in addition to curtailing

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earnings management, former auditors on the audit committee may also reduce the likelihood of internal control weaknesses. Overall, the results provide considerable evidence to suggest that audit committee members with professional auditing experience may improve financial reporting quality in the financial industry. Our empirical findings make two main contributions to the literature. Most importantly, this paper is the first attempt to examine how the presence of former auditors on audit committees affects earnings management in the financial industry. In a closely related study, Naiker and Sharma (2009) focus on the association between former auditors and internal control weaknesses, but they exclude banks and other financial institutions from their sample. As recently noted by Adams and Mehran (2012), Bai and Elyasiani (2013), and de Haan and Vlahu (2016), among others, financial firms are different from nonfinancial firms in terms of their operating environment, regulation, corporate governance mechanisms and incentive structures. These differences and the systemic importance of banks to the economy together with the complex nature of banks’ financial accounting impose higher demands on the financial expertise of the audit committee members. Therefore, it is of interest to examine whether the presence of directors with professional auditing experience on the audit committee influences financial reporting quality in the financial industry. Consistent with the findings of Naiker and Sharma (2009) for nonfinancial firms, our results suggest that ex-auditors on the audit committee may improve the monitoring effectiveness of the audit committee. Nevertheless, in contrast to Naiker and Sharma (2009), we also document that the positive effects of former auditors are largely driven by audit committee members who are unaffiliated with the current audit firm. Second, our study provides important insights to banking supervisors, regulators, and policy makers. Overall, our findings highlight the need for financial expertise on the audit

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committees. Consistent with the previous studies based on non-financial firms (Krishnan and Visvanathan 2008, Dhaliwal et al. 2010, Schmidt and Wilkins 2013, Cohen et al. 2014), the results indicate that the general level of financial expertise required by the current regulations may not be sufficient to improve the oversight of the audit committee. Our empirical findings suggest that effective monitoring of complex companies such as large banks may require financial experience and expertise above and beyond the current regulatory requirements set for a “financial expert”. The remainder of this paper is organized as follows. Section II discusses the related literature and presents our research hypothesis. Section III describes the data and presents the methodology used in the empirical analysis. Section IV reports our findings on the association between earnings management and the presence of former auditors on the audit committee. Finally, Section V summarizes the results and concludes the paper.

II. RELATED LITERATURE AND HYPOTHESIS DEVELOPMENT

Audit committees play a prominent role in ensuring the objectivity of financial reports. SOX (U.S. House of Representatives 2002) requires that audit committees provide independent reviews and oversight of the financial reporting process, internal controls, and external auditors. SOX (2002) reinforces the role of the audit committee by increasing the requirements regarding the size of the committee and members’ independence from the firm’s management. Moreover, the SEC (Securities and Exchange Commission 2003), adopting the SOX Section 407 rule, requires companies to disclose whether they have at least one financial expert on the audit committee. The purpose of this requirement is to ensure that the audit committees possess the

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necessary competences related to financial reporting, achieved either through involvement in the production, supervision or consumption of financial reports. Early research on audit committee financial expertise pointed to the benefits of the “financial expertise” requirement. For instance, Abbott et al. (2004), Bèdard et al. (2004), Mangena and Pike (2005), Carcello et al. (2011), and Sharma and Iselin (2012) report that audit committees’ financial expertise is associated with higher financial reporting quality. More recently, a distinction has been made between different types of financial expertise: the accounting financial experts and the non-accounting financial experts. Krishnan and Visvanathan (2008), Dhaliwal et al. (2010), and Schmidt and Wilkins (2013) document that the positive association between audit committee financial expertise and financial reporting quality is mostly attributable to directors with accounting financial expertise, while the findings of DeFond et al. (2005) indicate that investors particularly value the appointment of accounting financial experts to the audit committee.

Audit Committees and Former Auditors

The financial expertise of one or more audit committee members achieved by previously working as an auditor is likely to enhance the audit committee’s effectiveness in reviewing and overseeing the financial reporting process, internal controls, and the work of the external auditors. In particular, given the complexities of financial accounting in the banking sector, a profound understanding of the financial reporting process and experience from identifying the key accounts, management assertions, and risks should be particularly valuable in the banking industry. Moreover, while auditors are required to apply professional skepticism in the exercise of their professional judgments and audit committees have an important role in fostering this

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process, we postulate that a successful fulfillment of the audit committee’s tasks also requires “an attitude that includes a questioning mind and a critical assessment of [audit] evidence” (AICPA, 1997, AU Section 230.7) and the audit committee members should not “be satisfied with less than persuasive evidence because of a belief that management is honest” (AICPA 1997, AU Section 230.9). Given their background as independent auditors, former auditors on the audit committee are likely to understand the risks that managerial pressure imposes on auditor independence, and therefore, we expect that these directors are able to better isolate auditors from the firm’s management. Consequently, audit committee members with auditing background are likely to evaluate internal controls and managerial assertions more critically, be more aware of managerial incentives for earnings management, and to put more effort on safeguarding auditor independence when necessary. It is, however, important to acknowledge that directors with auditing background may still have ties to their alma mater. The findings of Carrera et al. (2017) suggests that social ties between auditors and directors may have a negative impact on the monitoring effectiveness of the audit committee. In contrast with this concern, Naiker and Sharma (2009) provide empirical support for that former auditors enhance the effectiveness of the monitoring provided by the audit committee. In particular, their findings suggest that former auditors, with professional experience from assessing the quality of internal controls and financial reporting process, are associated with a lower amount of reported internal control deficiencies. Moreover, Naiker et al. (2013) and Lennox and Park (2007) document that former auditors on audit committees appear to perform their duties independently from their previous networks, i.e. without pushing business, non-audit services or audit engagements towards their “alma mater” audit firm.

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The evidence concerning former auditors in executive functions is, however, less encouraging. While Dart and Chandler (2013) and Wilson (2017) report that investors do not consider employment of a former auditor as a threat to auditor independence, the prior studies by Menon and Williams (2004), Lennox (2005), and Lennox and Park (2007) suggest that firms with affiliated ex-auditors employed as executive officers have larger abnormal accruals, are more likely receive clean audit opinions, and are more likely to appoint the executive’s “alma mater” audit firm, suggesting that executive-auditor affiliations may impair audit quality and affect the auditor selection process. In contrast to executives, directors who serve on audit committees are likely to have stronger economic incentives to perform their responsibilities independently and effectively because regulators closely monitor corporate reporting and internal control quality, and because of reputation loss, litigation threat, and severe penalties for noncompliance (Lennox and Park 2007). The prior literature on banks’ earnings management has documented a negative relationship between discretionary loan loss provisions and corporate control mechanisms, such as corporate governance and auditing (e.g. Cornett et al. 2009, DeBoskey and Jiang 2012). In particular, Cornett et al. (2009) find that board independence is negatively associated with earnings management through loan loss provisions, suggesting that stronger governance may constrain earnings management in banks. Similarly, Kanagaretnam et al. (2010) and DeBoskey et al. (2012) report that auditor independence and industry specialization reduce earnings management. These two papers are closely related to our study because safeguarding auditor independence and audit quality are integral tasks of the audit committee, and moreover, because former auditors should be more aware of the importance of these factors.

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In this paper, we aim to contribute to the bank earnings management literature by empirically examining the association between discretionary loan loss provisions and the presence of directors with professional auditing experience on the bank’s audit committee. When acting as audit committee members, the directors with professional auditing experience are likely to evaluate and monitor the financial reporting process, internal controls, and managerial assertions more critically and be generally more aware of managerial incentives for earnings management. Consequently, we hypothesize that former auditors on the audit committee improve the financial reporting quality of financial institutions by constraining the use of discretionary loan loss provisions.

III. DATA AND METHODOLOGY

Sample

The sample used in the empirical analysis consists of publicly traded U.S. banks included in the S&P 500, S&P MidCap 400, and S&P SmallCap 600 indices (i.e., so-called S&P 1500 banks). The sample period extends from 2004 to 2012. We manually collect data on the professional auditing experience of the audit committee members from the BoardEx director biographies. Income statement and balance sheet data used in the analysis are obtained from Bureau van Dijk Bankscope, and the data on the banks’ governance characteristics are retrieved from Audit Analytics and BoardEx. After excluding banks with insufficient or missing director, financial and/or governance data, we obtain a sample of 78 individual banks and an unbalanced panel of 612 firm-year observations. Despite the relatively small number of individual institutions, our sample covers a substantial proportion of the total amount of banking assets in the U.S.

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The Empirical Framework

We empirically examine the association between discretionary loan loss provisions and former auditors on the audit committee with fixed-effects panel regressions. Our analysis requires a two-step approach in which we first estimate the discretionary loan loss provisions (DLLP) for each bank. Following Kanagaretnam et al. (2010) and DeBoskey and Jiang (2012), we estimate DLLP with the following regression specification:

LLPi ,t

1

NPLi ,t

2

LLRi ,t

3

NPLi ,t

4

NLC i ,t

5

(1)

2012 6

LOANS i ,t

Y

YEARiY

LOANS i ,t

i ,t

Y 2005

where LLPi,t denotes loan loss provisions for bank i in year t, NPL is non-performing loans, LLR is loan loss reserves, NPL is the change in non-performing loans, NLC is net loan charge-offs, LOANS is the change in total loans, LOANS is total loans, and YEAR is a dummy variable for fiscal years. All variables in Equation are scaled by lagged total assets. Equation (1) is estimated separately for four types of banks based on the banks’ SIC codes: national commercial banks (SIC 6021), state commercial banks (SIC 6022), other commercial banks (SIC 6029), and federally chartered savings institutions (SIC6035). Discretionary loan loss provisions for bank i in year t (DLLPi,t) are then defined as the residuals of Equation (1). After obtaining a measure of the discretionary loan loss provisions, we test our research hypothesis that the presence of directors with professional auditing experience on the bank’s audit committee constrains earnings management by estimating alternative variations of the following fixed-effects panel regression:

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DLLPi ,t

1

Ex-auditori ,t

21 23

2 20

Bank-specific controls

Bank-type dummies

i ,t

24 31

i ,t

Year dummies

(2) i ,t

i ,t

where the dependent variable DLLPi,t is one of two alternative measures of earnings management for bank i at time t. The two earning management measures used in the regressions are the negative values of the discretionary loan loss provisions (DLLPNEGi,t) and the absolute values of the discretionary loan loss provisions (|DLLPi,t|). The negative discretionary loan loss provisions are used as a proxy for income-increasing earnings management, while the absolute discretionary loan loss provisions are a proxy for the overall extent of earnings management. The test variable of interest in Equation (2) is Ex-auditor which captures the presence and the role of directors with professional auditing experience on the bank’s audit committee. Based on BoardEx director biographies, we identify audit committee members who hold a Certified Public Accountant qualification. We acknowledge that a director with a CPA qualification may not have necessarily worked on any audit engagements before becoming a director, but even the directors without audit engagement experience are bound to have formal education and on-thejob experience of auditing and financial reporting processes and are therefore classified as former auditors in this study. We define the following six different ex-auditor dummy variables which are used in our regressions: (i) Ex-auditor chair is assigned to one if the chairman of the audit committee is a former auditor, (ii) Affiliated ex-auditor chair equals one if the chairman of the audit committee is a former auditor with a previous affiliation with the bank’s incumbent audit firm, (iii) Unaffiliated ex-auditor chair equals one if the chairman of the audit committee is a former auditor without a previous affiliation with the bank’s incumbent audit firm, (iv) Ex-auditor members is assigned to one if any of the audit committee members is a former auditor, (v)

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Affiliated ex-auditor members equals one if any of the audit committee members is a former auditor with a previous affiliation with the bank’s incumbent audit firm, and (vi) Unaffiliated exauditor members equals one if any of the audit committee members is a former auditor and the former auditors on the audit committee have not been affiliated with the bank’s incumbent audit firm. The classification of former auditors into affiliated and unaffiliated audit committee members follows the approach of Naiker and Sharma (2009) and Naiker et al. (2013) and the findings that audit committee chairs may influence audit committee decision making more than members (Bonner et al. 2002, Beattie et al. 2014, Tanyi and Smith 2015). We employ a number of control variables in Equation (2) to account for the effects of bank-specific factors on earnings management. First, we include bank size and growth to control for the possibility that loan loss provisions differ systematically across banks of different size and growth perspectives. Bank size is measured as the logarithm of total assets and growth is proxied by the percentage change in total assets from year t–1 to year t. We account for the amount of equity capital by including capital ratio in the regressions. Capital ratio is calculated as the ratio of total equity capital to total assets. Capital ratio is considered as a proxy for the riskiness and financial soundness of a bank. Moreover, due to regulatory minimum capital requirements, the amount of equity capital may affect the use of discretionary loan loss provisions for capital and earnings management purposes. We control for bank profitability by including the return on three year average assets because poor financial performance may create incentives for earnings management. We account for the quality of banks’ loan portfolios with the amount of loan loss reserves and changes in impaired and non-performing loans. These three variables reflect lending risks and are likely to be associated with current loan loss provisions. Furthermore, given that different

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types of loans are associated with different risk characteristics, we include the amounts of commercial loans, consumer loans, and real estate loans scaled by total assets as additional controls for loan portfolio attributes. To account for unusual patterns in loan loss provisions of banks’ that are engaged in a merger or acquisition, we also include a dummy variable which equals one if the bank was involved in in a merger or acquisition during the fiscal year. We control for a number of corporate governance attributes because strong corporate mechanisms are fundamental for overseeing and controlling managerial discretion in the financial industry (see e.g., Sierra et al. 2006, Cornett et al. 2009, de Haan and Vlahu 2016). We use a dummy variable for the Big-4 audit firms to proxy for banks’ audit quality and we also include a dummy variable for auditor reported material weaknesses in internal controls. In order to account for the effects of board and audit committee characteristics, we include board size, board independence, and audit committee size as additional control variables in the regressions. To control for other types of financial and/or accounting expertise on the audit committee, we include dummy variables for financial expert audit committee chairs, accounting expert audit committee chairs, and accounting expert audit committee members. Specifically, we follow the previous literature (DeFond et al. 2005, Cohen 2014) to determine the financial and accounting expertise of the audit committee members; audit committee members who are designated as financial experts by the bank are classified as financial experts and audit committee members who are not former auditors but have working experience as a chief financial officer, chief accounting officer, controller, or treasurer are classified as accounting experts. Similar to the former auditor status, we manually identify the accounting expertise of audit committee members based on BoardEx director biographies.

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(Insert Table 1 about here)

Finally, we control for potential systemic variation in discretionary loan loss provisions across different types of banks and over time by including bank-type fixed-effects as well as year fixed-effects in the regressions. Throughout the estimations, we use robust standard errors which are adjusted for heteroskedasticity and firm-level clustering. All the variables included in Equation (2) are summarized and formally defined in Table 1.

IV. EMPIRICAL ANALYSIS

Descriptive Statistics and Correlations

Table 2 reports the descriptive statistics for the variables used in the empirical analysis. As expected, for an average bank, both the negative (DLLPNEG) and the absolute (|DLLP|) discretionary loan loss provisions are close to zero, suggesting that the sample banks on average are involved in relatively low levels of earnings management. With respect to the former auditor dummy variables, the descriptive statistics indicate that former auditors are surprisingly prevalent on banks’ audit committees. About 30 percent of the audit committee chairmen are former auditors and almost 60 percent of the sample banks have at least one former auditor on the audit committee. Interestingly, the mean values of the former auditor dummies further indicate that most of the former auditors serving on the audit committees, either as chairs or members, are unaffiliated with the bank’s incumbent audit firm. This suggests that the PCAOB Rule 3526 (PCAOB 2008) requiring disclosure from the audit firm regarding all relationships between the audit firm and the client and the SEC Rule (2003b) on a three-year cooling-off

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period for audit firm employees may effectively restrain banks from appointing former employees of the incumbent audit firm on their audit committees.


The descriptive statistics in Table 2 demonstrate that the sample banks are very heterogeneous in terms of the control variables. Although our sample consists of large, publicly traded banks, there is substantial variation in bank size with the amount of total assets varying from 1.02 billion to 2.36 trillion USD. The vast difference between the mean (111.00 billion) and the median (9.81 billion) total assets reflects the inclusion of four inordinately large financial institutions in our sample (i.e., JPMorgan Chase, Bank of America, Citigroup, and Wells Fargo). The sample banks, on average, are well-capitalized with a mean total equity to total assets ratio of 14.1 percent, and the return on assets of these banks varies considerably around the mean of 0.8 percent. On average, the sample banks hold about 1.2 percent of their total assets in loan loss reserves. Most of the sample banks are audited by a Big-4 audit firm, and about 2.4 percent of the banks have auditor reported material weaknesses in internal controls. Regarding the board and audit committee characteristics, Table 2 shows that the boards of U.S. banks have, on average, about 13 members and comprise mostly independent directors. The audit committees, in turn, typically consist of five members and most audit committees are chaired by a bank designated financial expert. It can be further noted that over half of the banks’ audit committee members can be classified as accounting experts.


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The pairwise correlation coefficients between the variables used in the regressions are reported in Table 3. Given that the negative discretionary loan loss provisions reduce the sample size by half, we tabulate the correlations without DLLPNEG. As can be seen from the table, the correlations between our dependent variable |DLLP| and the former auditor dummy variables are statistically insignificant. Hence, the correlations do not provide support for our research hypothesis that former auditors on the audit committee would constrain the use of discretionary loan loss provisions. Table 3 further shows that |DLLP| is significantly positively correlated with Capital ratio, Change in impaired loans, Loan loss reserves, Commercial loans, and Internal control weaknesses, and negatively correlated with Return on assets, Change in total assets, and Change in nonperforming loans. Not surprisingly, the six different former auditor dummy variables are strongly correlated with each other. Overall, it can be concluded that our regression estimates should not be affected by multicollinearity because the correlation coefficients between the variables used in the regressions are relatively low in magnitude. The correlation coefficients between the negative discretionary loan loss provisions and the other variables used in our regressions are qualitatively similar to the correlations reported in Table 3.

Regression Results

Table 4 reports the estimates of six alternative versions of Equation (2) with the negative discretionary loan loss provisions (DLLPNEG) as the dependent variable. Models 1-3 focus on former auditors as audit committee chairs, while Models 4-6 concentrate on former auditors as audit committee members. In Models 1-2 and 4-5, we control for a number of bank-specific financial and governance attributes that may affect earnings management, and in Models 3 and 6 we augment the set of control variables by including proxies for audit committees’ financial and

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accounting expertise. Throughout the regressions, we employ bank-type fixed-effects and year fixed-effects to account for systemic variation in earnings management over time and across different types of banks. As can be noted from Table 4, the adjusted R2s of the regressions are about 32 percent regardless of the model specification, and the F-statistics are statistically significant at the 1 percent level in all six specifications.


Overall, the regression results reported in Table 4 suggest that former auditors on the audit committee constrain earnings management in the banking industry. The estimated coefficient for Ex-auditor chair is positive and statistically significant at the 5 percent level in Model 1, indicating that banks which have former auditors as audit committee chairs are associated with lower levels of income-increasing earnings management. Following Naiker and Sharma (2009) and Naiker et al. (2013), we classify the former auditor chairs into affiliated and unaffiliated former auditors in Models 2 and 3. As can be seen from the table, the coefficient estimates for Unaffiliated ex-auditor chair are positive and statistically significant in both regression specifications, while the coefficients for Affiliated ex-auditor chair appear insignificant. This indicates that the constraining effect of former auditors on the use of income-increasing discretionary loan loss provisions is driven by former auditor chairs who have not been previously affiliated with the bank’s incumbent audit firm. In addition to being statistically significant, the observed negative relationship between former auditor audit committee chairs and income-increasing earnings management can be considered economically significant. Scaling the coefficient estimates of Ex-auditor chair and

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Unaffiliated ex-auditor chair by the mean absolute value of DLLPNEG suggests that banks which have former auditors as audit committee chairs are associated with approximately 30 to 40 percent decrease in the magnitude of income-increasing discretionary loan loss provisions. Consistent with Models 1-3, the estimates of Models 4-6 indicate that the presence of former auditors on the audit committee is negatively associated with income-increasing discretionary loan loss provisions. Specifically, the estimated coefficient for Ex-auditor members is positive and significant at the 5 percent level in Model 4 and coefficients for Unaffiliated exauditor members are positive and statistically significant in Models 5 and 6. Thus, these estimates provide further evidence that the observed negative relationship between former auditors and income-increasing earnings management is pertained to banks in which the former auditors on the audit committee are unaffiliated with the bank’s current audit firm. The magnitudes of the coefficient estimates indicate that the presence of former auditors on the audit committee is associated with an economically significant reduction of about 28 percent in income-increasing discretionary loan loss provisions. Regarding the control variables, it can be noted from Table 4 that DLLPNEG is positively associated with Size and Change in non-performing loans, while being negatively associated with Capital ratio, Loan loss reserves, and Merger. Hence, the regression results indicate that income-increasing earnings management is more prevalent in smaller banks with higher loan loss reserves and capital ratios, and furthermore, that a decrease in the amount of non-performing loans and the bank’s involvement in a merger or an acquisition is likely to increase the use of income-increasing discretionary loan loss provisions. Thus far, we have addressed the relation between former auditors and income-increasing earnings management. Turning the focus onto the extent of earnings management, we estimate

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alternative versions of Equation (2) with the absolute discretionary loan loss provisions (|DLLP|) as the dependent variable. The estimates of six different regression specifications are presented in Table 5. Similar to Table 4, we examine the association between earnings management and former auditors as audit committee chairs in Models 1-3, whereas Models 4-6 focus on former auditors as audit committee members. The adjusted R2s of these regression specifications vary between 34.4 and 35.1 percent and the F-statistics are all statistically significant at the 1 percent level, indicating a good fit of the models.


The estimates of the regressions with absolute discretionary loan loss provisions as the dependent variable in Table 5 are qualitatively similar to the results presented in Table 4. Specifically, the estimated coefficient for Ex-auditor chair is negative and statistically significant at the 10 percent level in Model 1 and the coefficients for Unaffiliated ex-auditor chair are negative and statistically highly significant in Models 2 and 3. Hence, consistent with our research hypothesis, the regressions suggest that former auditors as audit committee chairs may constrain the use of discretionary loan loss provisions. Furthermore, the estimates in Table 5 indicate that the negative relationship between earnings management and former auditor chairs is driven by former auditors who have not been affiliated with the bank’s current audit firm. However, in contrast to Table 4, the estimated coefficients for Ex-auditor members and Unaffiliated ex-auditor members, albeit being negative, are statistically insignificant in Models 4-6. Similar to Table 4, the results regarding former auditors as audit committee chairs can again be considered economically significant. The coefficient estimate of Ex-auditor chair scaled by

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the mean value of |DLLP| indicates a 19.5 percent decrease in absolute discretionary loan loss provisions, while the coefficients for Unaffiliated ex-auditor chair in Models 2 and 3 imply an even larger reduction of about 25 to 28 percent. Consistent with the results reported in Table 4, the coefficient estimates for the control variables demonstrate that smaller banks with higher loan loss reserves and capital ratios and with a decreasing amount of non-performing loans exhibit a higher degree of earnings management as measured by the absolute discretionary loan loss provisions. Furthermore, the estimates in Table 5 suggest that earnings management is negatively related to the amount of real estate loans and, not surprisingly, is more prevalent in banks which have auditor reported material weaknesses in their internal controls. Overall, the regression results presented in Tables 4 and 5 provide evidence of a negative association between earnings management and the presence of former auditors on the bank’s audit committee. Our estimates indicate that the levels of both income-increasing and absolute discretionary loan loss provisions are significantly lower in banks which have former auditors on the audit committee. Hence, the empirical findings support our research hypothesis that directors with professional auditing experience improve the financial reporting quality of financial institutions by constraining the use of discretionary loan loss provisions. Our results further demonstrate that the constraining effect of former auditors is largely driven by directors who have not been affiliated with the bank’s current audit firm. These findings are broadly consistent with Naiker and Sharma (2009) for nonfinancial firms, and thereby give additional empirical evidence that former auditors may improve the effectiveness of audit committee monitoring and oversight.

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Robustness Checks

We conduct a number of additional tests to examine the robustness of our findings. First, to ascertain that the results are not driven by a few outliers or extreme observations, we winsorize the discretionary loan loss provision and the bank-specific financial variables at the 1st and 99th percentiles and re-estimate the regressions using these winsorized variables. The estimation results based on the winsorized data (not tabulated) are consistent with our main analysis. Specifically, the coefficient estimates for Ex-auditor chair, Unaffiliated ex-auditor chair, Exauditor members, and Unaffiliated ex-auditor members are positive and statistically significant in the regressions with negative discretionary loan loss provisions as the dependent variable, and the coefficients for Ex-auditor chair and Unaffiliated ex-auditor chair are negative and significant in the absolute discretionary loan loss provisions regressions. Thus, we conclude that our findings are not induced by outliers. Interestingly, with respect to the control variables, the estimation results based on the winsorized data indicate that earnings management is significantly positively associated with internal control weaknesses and board size. Second, we estimate various parsimonious versions of the regressions in order to ensure that our findings are not caused by spurious correlations between the variables or affected by redundant control variables. Given that the coefficients for Size, Capital ratio, Change in nonperforming loans, and Loan loss reserves are systematically significant in Tables 4 and 5, we use these four variables as the only controls in the parsimonious regressions. The estimates of these regressions (not tabulated) are consistent with our main findings and indicate that former auditors on the audit committee curtail income-increasing and absolute discretionary loan loss provisions.

22

Third, in order to examine whether our results are sensitive to potential firm-size effects, we re-estimate the regressions using two subsamples from which either the five largest or the five smallest banks are excluded. In the subsample without the smallest banks, the estimates of the regressions remain virtually unchanged. The estimates of the regressions without the largest banks are also very similar to the results reported in Tables 4 and 5, with the exception of a positive and statistically significant coefficient for Affiliated ex-auditor chair in the regression with |DLLP| as the dependent variable (cf., Model 2 in Table 5). Overall, these additional regressions suggest that our results are relatively insensitive to firm-size effects. Finally, we perform additional regressions using three truncated subsamples from which fiscal year 2004, the crisis years 2008-2009, or year 2012 have been excluded. The purpose of this exercise is to investigate the sensitivity of our results to the sample period used in the analysis. The estimates based on the truncated samples (not tabulated) are qualitatively similar to the regressions results reported in Tables 4 and 5, and once again indicate the presence of former auditors on the audit committee is negatively associated with earnings management. These estimates also indicate that the negative association between earnings management and former auditors is more prominent when the global financial crisis is excluded from the sample. Overall, we conclude that our results are robust to slightly different sample periods.

Additional Test: Former Auditors and Internal Control Weaknesses

As an additional test, we examine the association between the presence of former auditors on the audit committee and internal control weaknesses. Under Section 404 of the SarbanesOxley Act (SOX), one of the primary tasks of the audit committee is to provide independent evaluations and oversight of the firm’s internal controls. Therefore, if former auditors improve

23

the overall monitoring effectiveness of the audit committee, it is plausible to expect that banks with former auditors on their audit committee are less likely to have material weaknesses in internal controls. Although earnings management and the quality of internal controls are very different concepts and require different type of involvement from the audit committee, we aim to reinforce the results of our main analysis by examining whether the presence of former auditors on the audit committee is also reflected in internal control quality. This additional analysis can be regarded as complementary to Naiker and Sharma (2009), who study the relationship between ex-auditors and internal control weaknesses using a sample of non-financial firms. According to Naiker and Sharma (2009), former auditors should reduce internal control weaknesses because they have professional experience and expertise in assessing the quality of internal controls. Following the prior literature on internal control deficiencies (e.g., Doyle et al., 2007, Naiker and Sharma, 2009), we use logistic regressions to test the association of internal control weaknesses with former auditors on the audit committee. Specifically, we estimate alternative logistic regressions of internal control weaknesses on the ex-auditor dummy variables alongside the set of control variables used in Equation (2). As defined in Table 1, the dependent variable in these regressions is a dummy variable which equals one for banks which have auditor reported material weaknesses in internal controls and zero otherwise. Based on auditors’ internal control reports obtained from Audit Analytics, we are able to identify only 15 bank-year observations with an auditor reported material weakness in internal controls in our sample of publicly traded U.S. banks. Given this very small number of observations, the results of our additional regressions should be viewed as suggestive and need to be interpreted with caution.


24

Table 6 presents the estimates of the logistic regressions examining the association between internal control weaknesses and the presence of ex-auditors on the audit committee. As can be seen from the table, the pseudo R2s of these regressions are around 35 percent, indicating a good explanatory power of the estimated models. The coefficient estimates for Ex-auditor chair, Unaffiliated ex-auditor chair, Ex-auditor members are negative and statistically highly significant in Models 1-3, and also the coefficient for Unaffiliated ex-auditor members is negative, albeit being statistically insignificant at the conventional levels (p-value = 0.105). Thus, the regression results indicate that banks which have former auditors on the audit committee are less likely to have material weaknesses in their internal controls. This finding is consistent with the empirical evidence reported in Naiker and Sharma (2009) for non-financial firms, and thereby provides further evidence to suggest that former auditors on the audit committee may improve the committee’s monitoring effectiveness. Nevertheless, due to the very small number of observations, the results of our additional analysis should be approached cautiously.

V. CONCLUSIONS

This paper examines whether the presence of former auditors on the audit committee constrains earnings management in the banking industry. Recent regulatory reforms have emphasized the audit committee’s responsibility for monitoring the financial reporting process and ensuring the overall objectivity of financial reporting. Given the complexity and the size of the entities, it can be argued that the audit committees of large banks should possess a considerable amount of financial expertise in order to successfully monitor the financial reporting process. In this paper, we posit that former auditors who serve on the audit committee

25

should improve the committee’s monitoring effectiveness. Former auditors are expected to have a profound understanding of the financial reporting process, and when acting as audit committee members, they presumably evaluate internal controls and managerial assertions more critically. Thus, we hypothesize a negative association between earnings management and the presence of directors with professional auditing experience on the bank’s audit committee. We empirically test our hypothesis using data on large publicly traded U.S. banks over the period 2004–2012. Following the prior literature, we measure earnings management with income-increasing and absolute discretionary loan loss provisions. Consistent with our research hypothesis, we document a negative association between earnings management and the presence of former auditors on the bank’s audit committee. Specifically, the results indicate that banks which have former auditors on their audit committees are associated with lower levels of both income-increasing and absolute discretionary loan loss provisions. Furthermore, we document that the negative association between earnings management and former auditors is strongest for banks in which the former auditors are unaffiliated with the bank’s current audit firm. We also perform additional tests which indicate that former auditors on the audit committee may reduce the likelihood of internal control weaknesses. Overall, the empirical findings reported in this paper provide considerable evidence to suggest that former auditors on the audit committee may improve financial reporting quality in the banking industry.

26

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Leventis, S., Dimitropoulos, P. and Anandarajan, A., 2011. Loan loss provisions, earnings management and capital management under IFRS: The case of EU commercial banks. Journal of Financial Services Research, 40, 103-122. Mangena, M., and Pike, R., 2005. The effect of audit committee shareholding, financial expertise and size on interim financial disclosures. Accounting and Business Research, 35 (4), 327349. Menon, K. and Williams, D., 2004. Former audit partners and abnormal accruals. Accounting Review, 79 (4), 1095-1118. Naiker, V. and Sharma, D., 2009. Former audit partners on the audit committee and internal control deficiencies. Accounting Review, 84 (2), 559-587. Naiker, V., Sharma, D. and Sharma, V., 2013. Do former audit firm partners on audit committees procure greater nonaudit services from the auditor? Accounting Review, 88 (1), 297-326. Olszak, M., Pipie , M., Kowalska, I. and Roszkowska, S., 2017. What drives heterogeneity of cyclicality of loan-loss provisions in the EU? Journal of Financial Services Research, 51, 55-96. Public Company Accounting Oversight Board (PCAOB), 2008. Ethics and Independence Rule 3526: Communication with Audit Committees Concerning Independence. PCAOB Release 2008-003. Washington D.C.: PCAOB. Schmidt, J. and Wilkins, M., 2013. Bringing darkness to light: The influence of auditor quality and audit committee expertise on the timeliness of financial statement restatement disclosures. Auditing: A Journal of Practice & Theory, 32 (1), 221-244.

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31

Table 1. Variable definitions. Variable Dependent variables: DLLPNEG

Definition

|DLLP|

Absolute values of the residuals of the loan loss provisions regression model of Kanagaretnam et al. (2010) and DeBoskey and Jiang (2012)

Ex-auditor variables: Ex-auditor chair

Affiliated ex-auditor chair

Unaffiliated ex-auditor chair

Ex-auditor members

Affiliated ex-auditor members Unaffiliated ex-auditor members

Negative values of the residuals of the loan loss provisions regression model of Kanagaretnam et al. (2010) and DeBoskey and Jiang (2012)

Equals one if the chairman of the audit committee is a former auditor and zero otherwise Equals one if the chairman of the audit committee is a former auditor with a previous affiliation with the bank’s incumbent audit firm and zero otherwise Equals one if the chairman of the audit committee is a former auditor without a previous affiliation with the bank’s incumbent audit firm and zero otherwise Equals one if any of the audit committee members is a former auditor and zero otherwise Equals one if any of the audit committee members is a former auditor with a previous affiliation with the bank’s incumbent audit firm and zero otherwise Equals one if any of the audit committee members is a former auditor and the former auditors on the audit committee have not been affiliated with the bank’s incumbent audit firm and zero otherwise

Control variables: Size Capital ratio Return on assets Change in total assets Change in impaired loans Change in non-performing loans Loan loss reserves Commercial loans Consumer loans Real estate loans Internal control weaknesses Merger Big-4

Logarithm of total assets Total equity capital divided by total assets Net income divided by three-year average total assets Change in total assets from t-1 to t divided by lagged total assets Change in impaired loans from t-1 to t divided by lagged total assets Change in non-performing loans from t-1 to divided by lagged total assets Loan loss reserves divided by lagged total assets Commercial loans divided by lagged total assets Consumer loans divided by lagged total assets Real estate loans divided by lagged total assets Equals one if the bank has material weaknesses in internal controls Equals one if the bank is engaged in a merger or acquisition Equals one if the bank is audited by a Big-4 audit firm

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Table 1. Continued. Variable Board size Board independence Audit committee size Financial expert AC chair Accounting expert AC chair Accounting expert AC members Year Bank-type

Definition Logarithm of the number of members on the board of directors Percentage of independent members on the board of directors Logarithm of the number of members on the audit committee Equals one if the chairman of the audit committee is a bank designated financial expert and zero otherwise Equals one if the chairman of the audit committee is not a former auditors but has working experience as a chief financial officer, chief accounting officer, controller, or treasurer Equals one if at least one of the audit committee members is not a former auditors but has working experience as a chief financial officer, chief accounting officer, controller, or treasurer Year fixed effects (2004-2012) Bank-type fixed effects (SIC 6021, SIC 6022, SIC 6029, SIC 6035)

33

Table 2. Descriptive statistics. Variable

Mean

Median

Minimum

Maximum

Std. dev.

-0.002 0.002

-0.001 0.001

-0.017 0.000

0.000 0.017

0.002 0.002

Ex-auditor chair Affiliated ex-auditor chair

0.305 0.029

0.000 0.000

0.000 0.000

1.000 1.000

0.461 0.168

Unaffiliated ex-auditor chair Ex-auditor members

0.276 0.579

0.000 1.000

0.000 0.000

1.000 1.000

0.447 0.494


0.061 0.532

0.000 1.000

0.000 0.000

1.000 1.000

0.240 0.499

Control variables: Size Capital ratio Return on assets Change in total assets Change in impaired loans Change in non-performing loans Loan loss reserves Commercial loans Consumer loans Real estate loans Internal control weaknesses Merger Big-4 Board size Board independence Audit committee size Financial expert AC chair Accounting expert AC chair Accounting expert AC members

111.000 0.141 0.802 0.087 0.002 0.000 0.012 0.186 0.084 0.411 0.024 0.089 0.848 12.579 0.826 4.642 0.752 0.213 0.527

9.807 0.136 0.979 0.048 0.000 0.000 0.011 0.163 0.066 0.402 0.000 0.000 1.000 12.000 0.857 4.000 1.000 0.000 1.000

1.021 0.000 -15.038 -0.395 -0.045 -0.016 0.003 0.000 0.000 0.000 0.000 0.000 0.000 5.000 0.000 3.000 0.000 0.000 0.000

2360.000 0.273 3.690 1.430 0.080 0.023 0.046 0.709 0.445 1.093 1.000 1.000 1.000 26.000 1.000 9.000 1.000 1.000 1.000

384.000 0.028 1.167 0.164 0.008 0.002 0.006 0.122 0.073 0.192 0.154 0.285 0.359 2.991 0.110 1.191 0.432 0.410 0.500

Dependent variables: DLLPNEG |DLLP| Ex-auditor variables:

The table reports the descriptive statistics for a sample of 612 firm-year observations on 78 publicly traded U.S. banks over the period 2004-2012. DLLPNEG and |DLLP| denote negative and absolute discretionary loan loss provisions, respectively. The definitions of the variables are presented in Table 1. Contrary to the variable definitions in Table 1, the descriptive statistics for Size, Board size, and Audit committee size are tabulated without logarithms.

Table 3. Correlations. Variable

1

2

3

4

5

1 |DLLP|

1.00

2 Ex-auditor chair

0.02

1.00

3 Affiliated ex-auditor chair

0.03

0.27

4 Unaffiliated ex-auditor chair

0.01

0.93 -0.11

1.00

-0.01

0.59

0.16

0.54

1.00

0.00

0.15

0.72 -0.12

0.22

5 Ex-auditor members 6 Affiliated ex-auditor members 7 Unaffiliated ex-auditor members

-0.01

8 Size

-0.01

9 Capital ratio

0.60

0.14 -0.10

0.07 -0.07

9

10

11

0.90 -0.19 -0.13

0.12 -0.18

14

15

16

17

18

19

20

21

22

1.00

-0.09

0.03

-0.03

1.00

0.00

0.01

0.00

-0.06

-0.05

1.00

0.00

0.03 -0.01

0.08

0.07

0.04

-0.01

-0.17

0.21

1.00

0.11

0.11

0.02

0.11

0.07 -0.02

0.06

0.04 -0.12 -0.21

0.10

-0.12

13

1.00

-0.03

11 Change in total assets

12

1.00

0.10

-0.23 -0.09

13 Change in non-performing loans

8

-0.08

0.31

10 Return on assets

12 Change in impaired loans

7

1.00

0.53 -0.13 -0.04

6

-0.04

-0.11

0.02

0.02

0.01

-0.04

0.01 -0.05

0.20 -0.06

14 Loan loss reserves

0.51

0.21

0.06

0.20

0.08

0.05

0.08

0.15

15 Commercial loans

0.12 -0.05

0.03 -0.06

0.00

0.13 -0.06

-0.04

0.24 -0.08

-0.03

0.20 -0.11

16 Consumer loans

-0.09

0.01

17 Real estate loans

-0.09

0.16 -0.06

0.19

0.23 -0.05

0.24

0.16 -0.03 0.16

0.05

1.00

0.20

0.04

-0.02

0.17

1.00

0.10 -0.06

0.02

-0.05

0.26 -0.22

0.11

0.07 -0.03

1.00

0.01

0.34

0.12

0.01

0.04

-0.36 -0.42

1.00

-0.11

0.04

0.06

-0.08

0.13

0.08 -0.09

0.05

1.00

0.00 -0.08

0.02

0.04

0.08

0.11

0.07 -0.06

-0.03

0.07

1.00

0.28 -0.20

0.06

-0.03

-0.03

0.03 -0.05

0.13

0.20

-0.26 -0.06

0.02

1.00

0.43 -0.18

0.01

0.08 -0.13

-0.33 -0.15

0.17 -0.08

-0.03

-0.07

-0.09

-0.04

-0.07

-0.05

19 Merger

0.10 -0.12 -0.02

-0.12

-0.12 -0.03

-0.11

0.22

-0.09

20 Big-4

-0.04

0.00

0.08 -0.03

0.00

21 Board size

-0.09

-0.01

0.03 -0.02

0.01 -0.05

0.03

0.02

0.09

22 Board independence

-0.02

0.07

0.08

0.07

0.04

0.04

-0.05

-0.02

0.07

0.04 -0.06

23 Audit committee size

-0.03

0.00

0.04 -0.02

0.05 -0.01

0.04

0.12

0.03

0.02

0.04

1.00

-0.06

-0.11

18 Internal control weaknesses

0.11 -0.04

-0.05

0.31 -0.43

1.00

-0.02

-0.02

-0.01

0.25

-0.11

-0.09

0.09

0.26

1.00

0.02

0.01

0.18

0.23

-0.17

0.00

-0.08

0.00

-0.04

1.00

0.04

0.00

-0.10

0.17

0.00 -0.08

0.22

0.26

0.02 -0.06

The table reports pairwise correlations between the variables used in the regressions. |DLLP| denotes absolute discretionary loan loss provisions. The definitions of the variables are presented in Table 1. Correlation coefficients that are statistically significant at the 0.01 level are highlighted in bold.

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Table 4. Ex-auditors and negative discretionary loan loss provisions.

Constant Ex-auditor variables: Ex-auditor chair

Model (1) 0.164 (0.789)

Model (2) 0.170 (0.812)

Model (3) 0.131 (0.62)

Model (4) 0.150 (0.74)

-0.029 (-0.93) 0.055 ** (2.50)


-0.021 (-0.51) 0.063 ** (2.23)

Ex-auditor members

0.047 ** (2.03)


Capital ratio Return on assets Change in total assets Change in impaired loans Change in non-performing loans Loan loss reserves

Model (6) 0.146 (0.743)

0.048 ** (2.26)


Control variables: Size

Model (5) 0.147 (0.728)

0.041 * (1.84) -0.017 ** (-2.48) -0.028 (-1.44) 0.080 (1.07) 4.251 (0.70) 22.085 *** (2.83) -10.648 *** (-4.11)

0.041 * (1.85) -0.017 ** (-2.52) -0.028 (-1.46) 0.077 (1.04) 4.163 (0.68) 22.199 *** (2.82) -10.940 *** (-4.23)

0.044 * (1.87) -0.017 ** (-2.40) -0.027 (-1.41) 0.071 (0.99) 3.960 (0.64) 22.525 *** (2.75) -10.659 *** (-3.99)

0.042 * (1.93) -0.017 ** (-2.48) -0.029 (-1.48) 0.077 (1.04) 4.511 (0.75) 22.996 *** (2.92) -10.133 *** (-3.78)

0.045 (0.76) 0.049 ** (2.08)

0.041 (0.70) 0.047 ** (2.03)

0.043 * (1.87) -0.017 ** (-2.51) -0.029 (-1.48) 0.082 (1.11) 4.538 (0.75) 23.018 *** (2.93) -10.184 *** (-3.73)

0.044 ** (1.98) -0.016 ** (-2.45) -0.030 (-1.52) 0.090 (1.21) 4.554 (0.74) 23.381 *** (2.94) -10.611 *** (-3.77)

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Table 4. Continued.

Commercial loans Consumer loans Real estate loans Internal control weaknesses Merger Big-4 Board size Board independence Audit committee size

Model (1) -0.039 (-0.43) 0.031 (0.19) -0.025 (-0.30) -0.068 (-1.40) -0.079 ** (-2.04) -0.008 (-0.22) -0.085 (-1.39) -0.011 (-0.12) -0.003 (-0.05)

Model (2) -0.032 (-0.35) 0.076 (0.47) -0.021 (-0.26) -0.068 (-1.42) -0.076 ** (-1.99) -0.007 (-0.21) -0.090 (-1.47) -0.004 (-0.05) -0.004 (-0.08)

Financial expert AC chair Accounting expert AC chair

Model (3) -0.031 (-0.34) 0.104 (0.65) -0.019 (-0.24) -0.059 (-1.14) -0.073 ** (-2.02) -0.005 (-0.14) -0.079 (-1.28) -0.001 (-0.02) -0.010 (-0.18) -0.031 (-1.24) -0.001 (-0.03)

Model (4) -0.067 (-0.68) 0.027 (0.17) -0.035 (-0.41) -0.069 (-1.42) -0.082 ** (-2.21) -0.007 (-0.19) -0.086 (-1.41) -0.025 (-0.28) -0.002 (-0.05)

Model (5) -0.073 (-0.71) 0.002 (0.01) -0.043 (-0.50) -0.069 (-1.42) -0.081 ** (-2.20) -0.007 (-0.19) -0.088 (-1.36) -0.021 (-0.24) 0.002 (0.04)

Accounting expert AC members

Bank-type fixed effects Year fixed effects Adjusted R2 F-stat.

Model (6) -0.095 (-0.94) -0.006 (-0.04) -0.060 (-0.70) -0.063 (-1.24) -0.075 ** (-2.10) -0.002 (-0.05) -0.091 (-1.40) -0.012 (-0.14) 0.012 (0.22)

-0.027 (-1.23) Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes

31.73% 5.65 ***

31.76% 5.49 ***

31.58% 5.17 ***

31.93% 5.69 ***

31.88% 5.52 ***

31.96% 5.39 ***

37 The table reports the estimates of six alternative versions of Equation (2). The dependent variable in the regressions is negative discretionary loan loss provisions. The definitions of the variables are presented in Table 1. The t-statistics (in parentheses) are based on robust standard errors which are adjusted for heteroskedasticity and within-firm clustering. ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels, respectively.

38

Table 5. Ex-auditors and absolute discretionary loan loss provisions.

Constant Ex-auditor variables: Ex-auditor chair

Model (1) 0.073 (0.484)

Model (2) 0.087 (0.571)

Model (3) 0.101 (0.68)

Model (4) 0.092 (0.61)

0.032 (1.14) -0.040 ** (-2.16)


Unaffiliated ex-auditor members

Change in total assets Change in impaired loans Change in non-performing loans Loan loss reserves

0.013 (0.34) -0.012 (-0.66)

-0.037 *** (-2.61) 0.008 * (1.95) 0.010 (1.03) -0.037 (-0.57) 0.456 (0.22) -9.841 *** (-2.93) 16.429 *** (5.49)

-0.038 *** (-2.77) 0.007 * (1.95) 0.011 (1.14) -0.041 (-0.63) 0.429 (0.21) -9.593 *** (-2.96) 17.047 *** (5.73)

-0.010 (-0.54)

Affiliated ex-auditor members

Return on assets

0.008 (0.22) -0.015 (-0.82)

0.029 (1.02) -0.046 ** (-2.18)

Ex-auditor members

Capital ratio

Model (6) 0.101 (0.693)

-0.031 * (-1.83)


Control variables: Size

Model (5) 0.098 (0.651)

-0.035 *** (-2.61) 0.008 ** (1.98) 0.010 (0.99) -0.044 (-0.69) 0.576 (0.28) -9.675 *** (-2.89) 16.631 *** (5.67)

-0.038 *** (-2.74) 0.008 ** (2.02) 0.010 (1.07) -0.043 (-0.68) 0.604 (0.30) -9.582 *** (-2.84) 16.777 *** (5.75)

-0.041 *** (-2.91) 0.008 ** (2.00) 0.009 (1.00) -0.038 (-0.62) 0.640 (0.31) -9.639 *** (-2.91) 16.753 *** (5.77)

-0.034 ** (-2.57) 0.008 * (1.94) 0.010 (1.00) -0.037 (-0.58) 0.413 (0.20) -9.845 *** (-2.94) 16.254 *** (5.38)

39

Table 5. Continued.

Commercial loans Consumer loans Real estate loans Internal control weaknesses Merger Big-4 Board size Board independence Audit committee size

Model (1) -0.022 (-0.24) -0.091 (-0.60) -0.116 * (-1.87) 0.149 * (1.78) 0.050 (1.38) 0.011 (0.45) 0.039 (0.88) -0.001 (-0.02) -0.010 (-0.23)

Model (2) -0.031 (-0.34) -0.129 (-0.88) -0.125 ** (-2.03) 0.150 * (1.78) 0.051 (1.40) 0.010 (0.43) 0.047 (1.05) -0.002 (-0.04) -0.012 (-0.27)

Financial expert AC chair Accounting expert AC chair

Model (3) -0.038 (-0.43) -0.145 (-1.01) -0.132 ** (-2.22) 0.144 * (1.68) 0.048 (1.42) 0.007 (0.31) 0.046 (1.03) -0.003 (-0.05) -0.010 (-0.21) 0.023 (1.21) 0.000 (0.01)

Model (4) -0.019 (-0.21) -0.116 (-0.76) -0.126 * (-1.82) 0.153 * (1.85) 0.054 (1.48) 0.010 (0.40) 0.035 (0.78) -0.010 (-0.16) -0.005 (-0.10)

Model (5) -0.028 (-0.29) -0.134 (-0.87) -0.130 * (-1.93) 0.153 * (1.85) 0.054 (1.49) 0.009 (0.37) 0.042 (0.88) -0.009 (-0.14) -0.005 (-0.12)

Accounting expert AC members

Bank-type fixed effects Year fixed effects Adjusted R2 F-stat.

Model (6) -0.020 (-0.21) -0.126 (-0.85) -0.119 * (-1.80) 0.143 * (1.68) 0.049 (1.42) 0.003 (0.13) 0.042 (0.88) -0.018 (-0.29) -0.015 (-0.30)

0.031 * (1.86) Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

Yes Yes

34.83% 11.88 ***

35.05% 11.61 ***

35.02% 10.91 ***

34.43% 11.69 ***

34.40% 11.31 ***

34.79% 11.14 ***

40 The table reports the estimates of six alternative versions of Equation (2). The dependent variable in the regressions is absolute discretionary loan loss provisions. The definitions of the variables are presented in Table 1. The t-statistics (in parentheses) are based on robust standard errors which are adjusted for heteroskedasticity and within-firm clustering. ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels, respectively.

41

Table 6. Ex-auditors and internal control weaknesses. Model (1) Ex-auditor variables: Ex-auditor chair

Model (2)

Model (3)

-1.110 *** (-2.67)


-1.081 ** (-2.57)

Ex-auditor members

-0.495 ** (-2.00)

Unaffiliated ex-auditor members

Control variables McFadden R LR-stat.

2

Model (4)

-0.417 (-1.62) Yes

Yes

Yes

Yes

34.83% 33.67 ***

35.05% 33.08 ***

35.02% 30.18 **

34.43% 29.09 **

The table reports the estimates of four alternative logistic regressions of internal control weaknesses on the ex-auditor variables. The dependent variable is an indicator variable which equals one for banks which have auditor reported material weaknesses in internal controls and zero otherwise. The definitions of the ex-auditor dummy variables and the control variables are presented in Table 1. The t-statistics (in parentheses) are based on Huber-White standard errors. ***, **, and * denote statistical significance at the 0.01, 0.05, and 0.10 levels, respectively.