ABNORMAL AUDIT FEE ASSESSMENT IN MANUFACTURING COMPANIES

How to cite this paper: Sari, F., Irfan, A., Muklis, F


INTRODUCTION
More and more Indonesian companies are going public along with the rapid growth of the economic sector.The Financial Services Authority (FSA) requires public companies to submit audited annual reports to the FSA in accordance with POJK No. 29 of 2016.The effect of these conditions on increasing demand for audit services is supported based on the report of the Financial Professional Development Center of July 2022, which shows an explosion in the public accounting financial profession.Dewi et al. (2019) claim that high-quality financial reports can reduce information asymmetry between stakeholders and financial report providers so that external audit services can help improve the quality of the financial reports produced.Pandia (2021) states that audit fees are costs incurred by companies when hiring external auditors.Publication of audit fees is optional in Indonesia, according to the FSA Circular Letter No. 30/SEOKJ.04/2016,as noted by Pandia (2021).Audit fees are regulated in Management Regulation No. 2 of 2016 concerning determination of financial statement audit services fees.However, Gultom et al. (2021) stated that it is possible for fraudulent practices in providing audit fees in Indonesia to be determined through negotiation between the auditor and the client.Setyawati and Apandi (2019), who concur, claim that unusual or abnormal audit fees still occur in practice.
Oladipupo and Monye-Emina (2016) define abnormal audit fees as fees that are outside or within the acceptable range of industry standards.Dwiandari and Mardijuwono (2020) state that abnormal audit fees cause auditors to be paid less (negative abnormal audit fees) or larger (positive abnormal audit fees) compared to the usual fees that must be paid.High audit fees allow auditors and customers to have a financial relationship (Nugroho & Fitriany, 2019).However, low audit fees will force auditors to provide low-quality work (Dabor & Benjamine, 2018).Establishments that receive positive abnormal audit fees are more inclined to obtain an unqualified opinion, according to research by Nawalin and Syukurillah (2017).
The PT Tiga Pilar Sejahtera Food case is an example of the abnormal audit fee phenomenon in Indonesia.The company's external auditors were unable to find overruns in the 2017 financial statements, which received an unqualified opinion.As a result, in 2018, the company suffered a loss of more than nine billion rupiahs (Septiadi, 2018).However, despite experiencing losses due to auditor failures, the company's audit fee payments increased 68.75% compared to the previous year.When compared to similar sub-sectors where audit fees increased by around 20%, the audit fee growth of 68.75% is quite significant.This shows that the audit fee paid by the company is unusual.
Joint audits had a favorable impact on abnormal audit fees, according to a study by Monye-Emina and Jeroh (2022) on the factors that affect abnormal audit fees at registered banks in Nigeria.The adoption of International Financial Reporting Standards (IFRS) and firm size have a negative impact on anomalous audit fees, whereas firm complexity has no impact.In their investigation of the connection between family ownership and abnormal audit fees, Surya and Fitriany (2019) discovered that family ownership had a detrimental impact on abnormal audit fees.Ilaboya et al. (2017) investigated the reasons for unusual audit fees in manufacturing companies that are listed on the Nigerian Stock Exchange (NSE).They discover that the Big Four and collaborative audits have a negative impact on high audit fees.Firm size and profitability have a positive relationship, but leverage has no bearing on unusual audit fees.
This study refers to Ilaboya et al. (2017), Surya and Fitriani (2019), and Monye-Emina and Jeroh (2022).Joint auditing and IFRS adoption were not used in this study.This is because joint audits are not commonplace and are not required in Indonesia.In addition, Indonesia has fully adopted IRFS since 2012, so its use in this study is irrelevant.Unusual audit fee analysis is very important because optimal audit fees are needed so that the auditor's audit results can accurately describe the situation and stop fraud.In the end, this will have an enormous impact on the economy and the corporate sector.Monye-Emina et al. (2020) argue that abnormal audit fees in various previous studies have not been the main focus of research.This is one of the basics of researchers conducting this research.In addition, the lack of empirical literature results in a knowledge gap around unusual audit fees.Therefore, the factors that influence abnormal audit fees need to be studied more deeply.
This study attempts to figure out how parameters such as size, complexity, the size of a public accounting firm, leverage, profitability, and family ownership affect atypical audit fees.The research presented here contributes to the body of knowledge on unusual audit expenditures and is expected to act as a benchmark for businesses determining how much to demand routine audit fees.
The structure of this paper is as follows.Section 2 reviews the relevant literature.Section 3 analyses the methodology that has been used to conduct the research.Section 4 describes and discusses the results and finally, Section 5 presents the conclusion.

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
Asymmetry of information resulting from the agency relationship between principals and agents is one of the problems with agency theory.Agents can manipulate financial reports due to information asymmetry to increase their wealth (Arwani et al., 2020).Dewi et al. (2019) suggest that asking an impartial third party to oversee the review of financial accounts to ensure agency performance is consistent with statements made is one method of reducing agency conflicts.
Monitoring costs are agency costs incurred for the supervision carried out by the auditor.As stated by Bernardus and Fitriany (2015), the auditor can prioritize management's interests because the auditor receives audit fees from management.In line with that, Harindahyani and Hananto (2020) emphasized that the auditor can charge an arbitrary audit fee if the auditor and his client have developed a personal, professional and familial relationship.These very expensive audit fees are often referred to as "abnormal audit fees".
Alhadab (2018) asserts that atypical audit fees are a complementary portion paid based on the distinct connection between the audit firm and its customer base and are without any connection to the distinct characteristics of the company itself.On the other hand, Setyawati and Apandi (2019) outline abnormal audit fees as the variation between the actual and predicted regular audit fees that should be stipulated for audit engagements.According to Nawalin and Syukurillah (2017), signed concluding agreements involving auditors and clients bring about inconsistent audit fees, which makes their decision-making process less transparent.
According to Krauß et al. (2015), public accounting firms that are compensated with very high audit fees have incentives to take advantage of opportunities to control profits.On the other hand, audit strategies and practices are modified according to the audit fees collected.Audit quality will decrease if the audit fee is lower (Nugroho & Fitriany, 2019).Several previous studies related to abnormal audit fees include Eshleman and Guo ( 2014 According to Widiastari and Yasa (2018), the words "company size" refer to the scale that classifies businesses according to their size.This scale is based on total assets, total income, share value and other factors.According to Pertiwi (2019), large organizations usually release more information than small companies to meet their internal expectations.The findings of the study by Ilaboya et al. (2017), who found a positive relationship between firm size and abnormal audit fees, support this opinion.
H1: Company size has a positive effect on abnormal audit fees.
As stated by Yulio (2016), complexity has been put on by changing currency transactions, the sheer quantity of affiliates and branches, and every continent's commercial operations.Harindahyani and Hananto (2020) assert that if the subsidiary firm gives the lead auditor the audit results soon after it is finished, the lead auditor's work will be more concentrated and the audit process will be finished on time.Sanusi and Purwanto (2017) became aware of a negative connection between paid audit fees and firm complexity, which is in agreement with this.This implies that the audit fees paid are more modest the more complex the organization is.
Whenever estimating audit fees, a public accounting firm's size is absolutely essential.In the opinion of Nurdjanti and Pramesti (2018), Big Four clientele are liable for auditing costs that are greater than the Big Four since the large four has advantages over the non-Big Four.This perspective was backed by Hasan (2017) and Chandra (2015), who demonstrated the positive impact of audit firm size on audit fees.
H3: Audit firm size has a positive effect on abnormal audit fees.
Leverage is defined by Adli and Suryani (2019) as the capability of a business to fulfill its financial commitments.Sibuea and Arfianti (2021) found that leverage has a positive effect on audit fees.According to Sibuea and Arfianti (2021), a higher leverage ratio indicates a higher company risk, so it requires a significant investment of time and energy on the part of the auditor to minimize this risk.
H4: Leverage has a positive effect on abnormal audit fees.
Profitability is the ability of an operation to achieve a profit at a certain level of revenues, assets, and equity capital, in the words of Maidani and Afriani (2019).Hasan (2017) contends that because they necessitate assurances of authenticity and revenue and expenditure recognition, firms that have significant profitability typically pay high audit fees.Fisabilillah et al. (2020), who reported the beneficial impact of profitability on audit fees, provide support for this opinion.
H5: Profitability has a positive effect on abnormal audit fees.
Sugiarto defines family ownership as a type of business in which the founder or members of his core family or extended family, whether those with blood relations or marital ties hold ownership, management, and control positions (2009, p. 29, as cited in Fitri & Apandi, 2019).According to Primasari and Zulaikha (2017), family businesses usually pay lower audit fees than non-family businesses because they have high supervision for strong business continuity.This opinion is reinforced by Surya and Fitriany (2019), who found a negative effect of family ownership on abnormal audit fees.
H6: Family ownership has a negative effect on abnormal audit fees.

RESEARCH METHODOLOGY
Those of the manufacturing firms that have been listed on the IDX between 2017 and 2021 have been incorporated into the study's population.For the reasons outlined further down, the manufacturing industry was selected as the sample.Initially, the manufacturing industry is a composite made up of plenty of emerging industrial subsectors.Furthermore, businesses that have been included in the IDX are obligated to submit an annual audit report to be conducted by the FSA.Lastly, the examiner is eager with the current state of audit fees across multiple sub-sectors because guidelines are reducing the release of audit fees.
Data has been obtained through detected approaches utilising the firm's annual report, which was found through the IDX website 1 .The sample for this study was made up of 32 businesses, filled out through a purposive sampling technique in accordance with the following specifications: 1. Manufacturing companies that continue listing on the IDX during 2017-2021.
2. Companies that present complete annual reports and attach audit fees following FSA Circular Letter No. 30/SEOJK.04/2016.
3. Companies that publish financial reports in rupiah units.
The following equation is the panel data regression analysis used in this study: where,  ABFEE is an abnormal audit fee;   is the constant of the regression equation;   -is the regression coefficient;  SIZE is the size of the company;  CPX is enterprise complexity;  BIG4 is the size of audit firm;  LEV is leverage;  PROFIT is profitability;  FAM is family ownership;   is a confounding variable.
Variable measurements in this study can be seen in Table 1.Data were evaluated using descriptive statistics, and tests for normality, heteroscedasticity, autocorrelation, and multicollinearity were run to confirm the estimation of the regression equation was accurate.The regression model was chosen using the Chow test and the Hausman test.The hypothesis is tested using the t-test, the coefficient of determination, and the goodness of fit.EViews 12 software is used to examine all data.With a data spread rate of 1.197987, the average abnormal audit fee scale for manufacturing businesses listed on the IDX for the 2017-2021 period is rather modest.It can be seen from the ABFEE (abnormal audit fee) data, which has a median value of 0.013846 and a range from 2.335618 to -2.041591.The company size variable (SIZE), which shows the highest value of 32.44247, the lowest value of 25.93549, and the average value of 28.75894 for manufacturing companies listed on the IDX for the 2017-2021 period, indicates that the average company size scale is large-scale.

Descriptive statistics
The variable firm complexity (CPX) shows the highest value of 1 and the lowest value of 0, with 23 of the 32 companies included in the research sample having subsidiaries.A typical manufacturing business listed on the IDX for the 2017-2021 period has subsidiaries with a data distribution level of 0.456909, according to the average value of enterprise complexity (CPX), which is 0.706250.The audit firm size variable (BIG4) shows the highest value of 1 and the lowest value of 0, where out of 32 companies that were used as research samples, 8 companies were audited by the audit firm (BIG4).The average value is 0.293750, which means that the average manufacturing companies listed on the IDX for the 2017-2021 period were audited by a non-BIG4 audit firm with a data distribution rate of 0.456909.
With an average value of 1.071427 and a data spread rate of 1.621400, the leverage variable (LEV) has a range of -3.826103 to 10.28053.If the standard deviation value exceeds the mean (mean), the data is heterogeneous.The following values are displayed for the profitability variable (PROFIT): the biggest value was 1.059862, the smallest was -2.573123, and the average was 0.041538 with a data spread rate of 0.253838.The family ownership variable (FAM) has a range of values with a data distribution level of 0.437932, with the highest value being 1 and the lowest value being 0, and the average value being 0.256250.

Normality test
Figure 1 indicates that the chance of Jarque-Bera being significant at 0.979624 > 0.05 allows us to infer that the data are already normally distributed and that regression models are appropriate for use.

Heteroscedasticity test
According to Table 3, the chi-square probability value for Obs.* R-squared is 0.0623, which is higher than 0.05.Therefore, it can be said that the regression model has no heteroscedasticity.This demonstrates that the residual variance between observations is constant, making it possible to estimate the regression model.

Autocorrelation test
A mark probability chi-square of 0.3013 is more significant than 0.05, according to Table 4.It follows this approach that There is no autocorrelation.Regression modelling is worthwhile since it demonstrates that there is no happen association between the variables in the model and changes over time.

Multicollinearity test
All of the independent connections between variables are shown in Table 5.No point total exceeding 0.8.This demonstrates that this regression model does not exhibit multicollinearity.This demonstrates that the variables that make up the regression model do not all have a perfectly linear relationship, allowing for the usage of an approximated regression model.

Panel data regression analysis
The R-squared value in Table 8 is 0.982104 indicating that 98% of abnormal audit fees are caused by factors related to company size, company complexity, audit firm size, leverage, profitability, and family ownership, with the remaining 2% explained by factors other.The research model is accepted, according to the probability F-statistic of 0.000000.Based on the results of the panel data regression analysis above, the probability value of firm size is 0.0250 < 0.05 indicating that firm size has a positive effect on abnormal audit fees.The findings of this study are consistent with Ilaboya et al. (2017) and the agency theory of Jensen and Meckling (1976), which states that large organizations will incur greater agency costs than small companies.According to Nawalin and Syukurillah's (2017) research, the existence of opinion shopping can also be indicated by high abnormal audit fees.Big businesses often look to unqualified comments to persuade customers.Therefore, to stop opinion shopping and other fraudulent practices, an adequate internal control system is needed.
The second hypothesis that company complexity has a negative effect on abnormal audit fees is rejected because company complexity has a probability of 0.9313 > 0.05.This result refutes the notion of Jensen and Meckling (1976) that subsidiaries pay higher agency fees.Monye-Emina and Jeroh (2022), who found no effect of firm complexity on abnormal audit fees, support this finding.If the subsidiary company and the parent company have different auditors to audit the financial statements, the audit process will be carried out in a timely manner so that it will not add to and affect the audit fees to be paid.
The probability of audit firm size is 0.0011 < 0.05, indicating that audit firm size has a positive effect on abnormal audit fees.These results support Jensen and Meckling's (1976) theory whereby companies using Big Four accounting firms will pay high audit fees.High audit fees can be attributed to the Big Four's competence, professionalism, and experience.However Leverage has a probability of 0.0370 < 0.05, accepting the fourth hypothesis where leverage positively affects abnormal audit fees.This finding corroborates the theory by Jensen and Meckling (1976) that companies using Big Four accounting firms will incur high audit fees.The proficiency, expertise, and experience of the Big Four can be associated with high audit fees.In contrast, Ilaboya et al. (2017) found a negative relationship between audit firm size and abnormal audit fees but did not reach a significant level.Further explanation regarding this matter needs to be provided by Ilaboya et al. (2017) in their research.
The probability of profitability of 0.0298 < 0.05 indicates a positive effect of profitability on abnormal audit fees.These results support Jensen and Meckling's (1976) agency theory which states that a company with a high level of profitability will pay a higher audit fee due to the need for verification checks related to income and expenses.Ilaboya et al. (2017) found a positive effect on profitability to abnormal audit fees but did not reach a significant level.Further explanation regarding this matter needs to be provided by Ilaboya et al. (2017) in their research.
The sixth hypothesis which discusses the negative effect of family ownership on abnormal audit fees is rejected because family ownership has a probability of 0.9941 > 0.05.Jensen and Meckling's (1976) agency theory, which argues that family businesses pay lower audit fees than family businesses because they have sufficient oversight to ensure business continuity, is refuted by this finding.However, if supervision of the family business is insufficient, it will not be able to stop unusual audit fees from occurring.Nugroho and Fitriani (2019) found the impact of family ownership on a positive abnormal audit fee but not on a negative abnormal audit fee.

CONCLUSION
This research effort attempts to establish the effects of company size, complexity, audit firm size, leverage, profitability, and own family on excessive audit charges among firms that manufacture objects that are listed on the Indonesia Stock Exchange between 2017 and 2021.The results presented to establish that profitability, leverage, audit firm size, and audit firm size all significantly interfere with how uncommon audit fees remain.However, the unusual impact of a complicated company and its own family on audit was not made obvious by the present investigation.Consequently, in order to safeguard fraud, it must be done to establish precise guidelines and encourage additional societal integration with respect to a consistent and transparent approach to formulating audit fees.
The following analysis would likely be used as a point of departure for clarity about unusual audit fees to customers and auditors.Ilaboya et al. (2017), Monye-Emina and Jeroh (2022), Li (2021), and others have published studies that indicate that future research to delve more into the calculation of atypical audit fees.Monye-Emina and Jeroh (2022) state that abnormal audit fees as the remaining portion of the total audit fees using regression techniques, whereas Li (2021) explored abnormal audit fees using the rate.Ilaboya et al. estimated abnormal audit fees using the median deviation of audit fees.This study is limited to Indonesian manufacturing companies; afterwards, investigators may examine other industry sectors other countries to obtain more exhaustive conclusions.

4. 6 .
Regression model selection 4.6.1.Chow testTable 6 displays the probability of the chi-square cross-section, which is less than 0.05 and equal to 0.0000.The fixed effects model is chosen based on the Chow test results, and the Hausman test is required to determine which model, out of fixed effects and random effects, provides the greatest fit.
, this contrasts with Ilaboya et al. (2017), who found a negative effect of audit firm size on abnormal audit fees.Furthermore, Ilaboya et al. (2017) argue that the negative effect of audit firm size on abnormal audit fees is associated with the technological and professional competence of the Big Four.However, this position has no empirical justification.

Table 1 .
Operational variable definitions Source: Prior research.

Table 2
describes the factors employed in this investigation.

Table 7 .
Therefore, it can be said that the chosen fixed effect model is what the Hausman test results use.The results showed that a fixed effects model performed the best in modelling panel data of the study.

Table 8 .
Panel data regression analysis results (fixed effect model)