THE EFFECT OF AUDIT, CORPORATE CULTURE, AUDIT COMMITTEE, INSPECTION, POLICIES AND PROCEDURES, AND IT ADOPTION ON FRAUD EFFECTIVENESS RISK MANAGEMENT BANKING INDUSTRY IN INDONESIA

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INTRODUCTION
According to Todorović, Tomaš, & Todorović (2020), fraud is a morally repugnant, illegal, costly societal issue. Because fraud has such a negative impact on economic development, profitability, and the welfare of business, it has emerged as a major threat on a global scale (ACFE, 2020). For this reason, the public, the government, and auditors all pay a great deal of attention to the issue of fraud. Also, as can be shown in figure 1 below, financial losses and reputational harm are the two most common impacts faced by businesses, as indicated by a study conducted by RSM (2020)

Figure 1. The Worst Impact of Fraud
Source: RSM (2020) Each year, there are a growing number of instances of fraud that are recorded. In Recent years, instances of fraud have captured the attention of the general public. According to the respondents of the PricewaterhouseCoopers (PWC) Global Fraud and Crime Investigation Report 2020. as many as 47% of respondents experienced fraud in their firm over the preceding 24 months. The whole fraud cost $42 billion in damages to businesses and customers. In a survey that PWC has conducted over the course of the past 20 years, this rate came in second (PWC, 2020). The finding of the PWC fraud research give a clear picture of the feact that the number of reported incidents of fraud is still significantly increasing and that all types of businesses have an equal likelihood of becoming victims of fraud.
According to the ACFE's 2020 Report to the Nations, there were 2.504 cases of fraud throughout the globe that resulted in losses totaling more than $3.6 billion USD. These losses were spread among 125 countries. The United States and Canada had the highest number of occurrences of fraud, totaling 895, which accounted for 46% of all instances of fraud that were reported globally. The nations of the Asia-Pacific region came in second place with a percentage of 10%, followed by the countries of Africa other than those in North Africa with a percentage of 15%.
The Asia-Pacific region suffers an average financial loss of $195.000 per incident, making it the third-highest region in the globe in terms of the number of fraud cases, with 198 reported instances (ACFE, 2020). In the countries of Asia and the Pacific, property appropriation is responsible for 74% of all incidents of fraud, making it the most common kind of fraudulent scheme in the area. Fraud-related losses, on the other hand, were caused by a method of manipulating financial statements that led to a loss of three million dollars.
Taxes are one of the primary sources of income for the Indonesian government, which are collected from the citizens of the country (Ministry of Finance, 2021). Income and value added taxes are still collected in Indonesia from a wide range of companies, including the banking and insurance sectors (Kemenkeu, 2019). On the other hand, since frauds are so common in today's society, the financial system is especially susceptible to failing (LPS, 2019). This failure will result in the deposit Insurance Corporation and the Financial Services Authority placing a freeze on a variety of financial institution since fraud allegations have been leveled against them. The indefinite halting of operation at a great number of banks in Indonesia as a result of fraudulent activity has a large and negative effect on the country's overall financial status. Bank customers and other stakeholders, in addition to the state, suffer losses as a result of the proliferation of fraudulent activities involving banks. As a consequence of arranging illegal loans to two companies with a combined amount of 8,7 billion rupiah, the BJB branch manager was sentenced to a prison term of six years in 202 (Kompas, 2021). In addition to BJB, Panin Bank was also charged with tax evasion for allegedly colluding with one of the audit directors, which ultimately resulted in the suspension of the Directorate General of Taxes (Kompas, 2021). In the meanwhile, losses were oncurred by Bank Central Asia as consequence of theft conducted by third pasrties using virtual accounts (Kompas, 2020). In addition to BCA, many other financial institutions including Bank Mega and a few others were robbed. As a direct consequence of the robbery at Bank Mega, a total of fourteen customers have suffered losses that amount to 56 billion rupiah (Tempo, 2021).
Customers of Bank Mandiri, Bank Negara Indonesia, and Bank Rakyat Indonesia have all reported unauthorized withdrawals form their saving accounts (Tempo, 2021). These cases demonstrate that fraudulent activity in the banking business may come from both within and outside the industry. As a direct result of this, the government via the Financial Services Authority has set guidelines for commercial banks to follow in order to ensure that an anti-fraud strategy is effectively implemented. The passing of these rules is intended to put an end to inappropriate activity in the banking industry, particularly fraud that results in financial losses for customers or organization. The prevention, identification, investigation, and monitoring of fraudulent activity are the four pillars that support the anti-fraud strategy (OJK, 2011). In addition, in accordance with the Bank Indonesia Regulation on Payment Service Providers No.23/6/PBI/2021, financial institutions that provide payment services are required to have the capacity to access information systems (Article 14). One of the Information system characteristics that is highlighted in part 28 of PBI No.23/6/PBU/2021 is called a Fraud Management System (FMS).
In most cases, The implementation of anti-fraud methods that are widely employed by companies is the audit of the financial accounts that is performed by external auditors. This audit must correspond to the code of professional ethics and ethics in a degree that is at least 83% internal control. When compared to other precautions against fraud that were already in place, the code of ethics was shown to reduce losses due to fraud by 51%. In addition to the code of ethics, the internal audit function the external audit function, as well as the inspection and certification of the financial records of the Board of Directors, each have a success rate of fifty percent in mitigating the damage caused by fraud. It is possible that the deployment of antifraud measures may decrease the amount of time required to uncover fraudulent activity by speeding up that process. It is possible that a code of ethics, employment rotation, internal auditing task, and the inspection and approval of financial statements by management would reduce the amount of time spent on fraud by fifty percent (ACFE, 2020). Following closely behind external audits, which are responsible for 93% of all anti-fraud measures carried out in Asia Pacific, Internal audit functions and codes of ethics are carried out by a ratio that is over 1:1 (ACFE, 2020). According to Alzeban and Gwilliam (2014), one of the most effective approaches is conducting an internal audit with the support of management. Assessment on the Inside, evaluation on the outside, observation, and reporting are the four types of anti-fraud procedures that are used for fraud detection in Indonesia (ACFE Indonesia, 2020). This study aims to determine whether internal audit, corporate culture, audit committees, inspectors, policies, and procedures as well as the adoption of information technology affect the effectiveness of management fraud risk in the banking sector in Indonesia or not.

Internal audit
Internal audit is part of corporate governance. Deloitte (2012) found that 53% of fraud cases in banks can be identified by internal audit. Therefore, internal audit is an effective tool to combat fraud (PWC, 2020). Siregar and Tenoyo (2015) find that internal audit can be used as a tool to detect and prevent fraud. These conclusions are also found by Mangala and Kumari (2017). H1: Internal Audit has a positive effect on the effectiveness of fraud risk management. Corporate Culture Llopis et al. (2007) said that ethical culture exists when ethical values are carried out and become the responsibility of all employees of a company, not only at the managerial level. And that's where we get what is called corporate governance ethical behavior.

Ethical Values
Workplace integrityis an important component that must be owned by every organization. Fraud committed by employees can be suppressed by implementing strong workplace integrity as a company culture. Siregar and Tenoyo (2015) found that companies received threats of fraud due to a lack of ethical values. H2: Corporate Culture has a positive effect on the effectiveness of fraud risk management.

Audit Committee
The audit committee may include independent members as well as members of the company's board of directors. Independent members of the audit committee are defined as those who have no personal or financial connection to the company and management.

Independence of Audit Committee
The independent audit committee is a party that has no personal or financial contact with the company or its directors. The audit committee can come from inside or outside the company, so the independence of the audit committee can be measured using the ratio between the external audit committee divided by the audit committee. external audit.

Effectiveness of Audit Committee
The audit committee has an important role for the company. Hakim (2011) found that the effectiveness of the audit committee affects the reduction of fraud in the company. H3: Audit Committee has a positive effect on the effectiveness of fraud risk management.

Inspection
Inspection is one of the internal control techniques that can be carried out by companies in the application of fraud risk management. Employee Reference Check Perpetrators of fraud may move from one company to another. Therefore, the company may be able to hire dishonest employees. Employee reference checks can be used as a step that can make companies more selective in hiring new employees. If the employee reference check is not carried out by the company, the risk of loss caused by employee fraud is higher for the company. Siregar and Tenoyo (2015) found that 79.1% of respondents in their study stated that their company conducted background screening of prospective employees as a step to prevent fraud. Findings from research (Bierstaker et al., 2006) H4: Inspection has a positive effect on the effectiveness of fraud risk management.

Policies and Procedures
Policies and procedures owned by the company have their respective roles in minimizing or even eradicating fraud in the company. Through this policy the company can be more effective in avoiding fraud. Mangala and Kumari (2017) state that an auditor has his own assessment of the policies and procedures that apply in the company as a manifestation of the important role played to sabotage the fraud that exists in the company.

Whistle Blowing Policies
Whistle blowingis one of the controls that can be applied to prevent fraud and also help detect fraud. Whistle blowing can make employees more aware and responsible for what they do (PWC, 2008). Furthermore, the reporting mechanism is designed in such a way that fraud can be reported to the company's board of directors and audit committee. ACFE (2021) found that reporting of fraud through the whistle blowing mechanism was widely reported to supervisors. Bierstaker et al. (2006) found that whistle blowing is widely used in eradicating fraud with a percentage of 73% and is a fairly effective mechanism in eradicating fraud. H5: Policies and procedures have a positive effect on the effectiveness of fraud risk management.

IT Adoption
The development of increasingly sophisticated technology makes fraud in the company higher and more difficult to overcome. Even so, the emergence of technology also facilitates human work, even in tackling acts of fraud in organizations or companies. Thus, the use of increasingly sophisticated technology can be maximized in a more positive direction, namely, to overcome fraud which is currently increasingly complicated. A survey conducted by RSM (2020) shows 67% of respondents believe that IT has the ability to reduce the possibility of fraud. This can be seen from the findings of Mangala and Kumari (2017) which state that every auditor makes information technology an important element that must be used in overcoming fraud in the company. However, Halbouni et al. (2016) found the similarity of functions between information technology and traditional techniques that are usually used to prevent and detect fraud. Utami et al. (2020) also suggested that the banking industry in Indonesia should start paying attention and strengthening their information technology because at this time the role of information technology is very important. H6: IT Adoption has a positive effect on the effectiveness of fraud risk management

Research design
In this study, the researchers used a descriptive quantitative method. A quantitative research method is defined by Sugiyono (2018) as a research method based on a positivist philosophy, used to examine populations or quantitative/statistical samples, for the purpose of testing hypotheses theory has been established. According to Lehmann in Yusuf (2017), quantitative descriptive research is a type of research that aims to systematically, realistically and accurately describe the facts and characteristics of a particular population or to try to describe phenomena in detail.

Identifying variables
Identifying variables in research is a step-in identifying variables in research and determining the function of each variable (Azwar, 2007). Research variable is an attribute or value of a community, object or activity of some diversity that is selected by the author for later research and conclusions (Creswell & Poth, 2016). In this study, the author reveals two variables, namely the independent variable and the dependent variable.

Independent variable (Exogenous variable)
An independent variable is a variable that affects or causes changes in the dependent or dependent variable (Darmawan, 2013). This study uses several independent variables, including audit (X1a), corporate culture (X1b), audit committee (X1c), audit (X2a), policies and procedures (X2b), and application of information technology (X3).

Dependent variable (Endogenous variable) http://eduvest.greenvest.co.id
The dependent variable or dependent variable is the variable that is affected or the result of the independent variable (Sugiyono, 2018). In this study, the dependent variable is the effectiveness of fraud risk management in some companies operating in the banking sector in Indonesia.

Types and sources of data
The data used in this document is primary. Handoko (2020) defines primary data as data obtained directly by researchers through means recorded by other parties. Key data were obtained from the distribution of questionnaires through social media such as email, WhatsApp and other social media. The questionnaire used in this study will use the tool, namely the Likert scale. Sugiyono (2018) argues that the Likert scale is used to measure the attitudes, opinions and perceptions of a person or a group of people about a social phenomenon. The Likert scale in this study will use a scale of 1 (strongly disagree) to 6 (strongly agree).

Population and Sample
According to Sugiyono (2018), a population is a general field of objects or subjects with a certain number and characteristics assigned by researchers to study and then that draw conclusions. The subject matter of this study is human attributes or nature or values. Objects or activities with certain variables are identified for research and conclusions (Sekaran & Bougie, 2017). The subject of this study is the internal auditor of a banking company in Indonesia. Due to the large number of listeners in Indonesia, this study will use a representative population sample. Sugiyono (2018) defines a sample as a portion of a population or characteristics possessed by the population itself. The sampling technique used in this study is purposive sampling where the technique of sample determination uses certain considerations (Sugiyono, 2018). The considerations used to define the sample for this study were participants with experience as internal auditors of banks listed on IDX. Hair (2019) state that a measure is considered good when using the maximum likelihood estimation (MLE) technique using up to 100-200 participants. Therefore, this study will use a sample of 100 respondents.

Data Analysis Method
Analytical method is the systematic process of studying and compiling processed data from field observations and documenting data sources by organizing data into various categories, describing them by units, by synthesis, by compiling models, by selecting the important ones. which parts and which parts need to be studied and drawn conclusions that are easy for themselves and others to understand (Narimawati et al., 2010). The data analysis method used in this study is Structural Equation Modeling (SEM) based on partial least squares (PLS) using SmartPLS 3 device. According to Santoso (2014), SEM aims to the purpose of testing the relationship between the variables of the model and is defined as an analytical technique. Multivariate analysis is a combination of factor analysis and regression analysis.

Descriptive Statistics
Descriptive statistics aims to analyze data by describing or describing previously collected data so that the data becomes clearer and the information easier to understand. Sugiyono (2018) also conveyed that descriptive analysis can be useful as a tool for data analysis by describing or describing the data that has been collected respectively without drawing general conclusions.

Smart PLS (Partial Least Square)
The analytical method of the PLS method can be applied to all scales of the data held. In addition, PLS also does not require many estimates and does not necessarily require a large sample size.

Outer model
Outer model describes the relationship between the indicator block and its latent variables. Specifically, this model can relate latent variables to their indicators.

Validity test
The validity test in PLS-SEM consists of two types, namely convergent validity and discriminant validity (Narimawati et al., 2020).

Convergent Validity
A commonly used measure to calculate convergence validity in structures is to use extracted mean variance (AVE) and external load. The value of the required external load/load factor is 0.7, but for early-stage research a value of 0.5-0.7 is still confirmed to pass the assembly validity test. capacitors (Ghozali & Latan, 2012). This benchmark is defined as the global mean of the squared load index relative to the building (i.e. the sum of the squares of the loads divided by the number of ratings). An AVE score of 0.50 or higher suggests that the mean structure explains more than half of the indicator's variance (Narimawati et al., 2020). Conversely, an AVE less than 0.50 indicates that the mean of the other error values contained in the structure is larger than the variance described by the structure. In Discriminant validity Discriminant validity is based on the principle that, based on single construction indices or other constructs, it should not be highly correlated (Ghozali & Latan, 2012). Discriminant validity testing is intended to determine whether a reflectance indicator is a good measure of its own structure. Discriminant validity testing is performed by evaluating the value of the crossload. The flag load value of each variable must be greater than the load value of the other variables (Hair et al., 2019).

Reliability Test
Reliability testing is used to measure the internal consistency of the measuring instrument. Reliability refers to the accuracy and consistency of measurement tools in measurement (Sekaran & Bougie, 2017). In SmartPLS 3 software, reliability testing can use two methods, namely composite reliability, and Cronbach's alpha. Ghozali (2014) states that Cronbach's alpha measures the lower limit of the reliability value as an index variable. Reliability is achieved when Cronbach's alpha is greater than 0.70.

Inner model
Inner model testing was performed to determine the relationship between the exogenous structure and the previously emitted endogenous structure. Also checking internal model is called structural testing. There are several tests in the internal model, namely:

Coefficient of Determination (R2)
The coefficient of determination test is performed to measure how well the model can explain the changes. in the dependent variable. The coefficient of determination test is performed to determine the significance of the percentage contribution of the influence of the independent variable on the dependent variable. The coefficient of determination varies from 0 to 1. The higher the value of the coefficient of determination (closer to 1), the stronger the influence of the independent variable in explaining the dependent variable. Meanwhile, the coefficient of determination becomes smaller (closer to 0) indicating that the influence of the independent variable is weak or limited in explaining the dependent variable. There are three scoring criteria for the coefficient of determination, namely: 0.67 means strong, 0.33 means moderate and 0.19 means weak (Ghozali, 2014).

Influence Size (f2)
The influence size of each orbital pattern was determined using f2 analysis (Cohen, 1998). The effect size (f2) was calculated by observing the change in R2 when a construct was removed from the model. There are three types of f2 values, namely: 0.02 describes a weak effect, 0.15 describes a moderate effect, and 0.35 describes the strong effect of potential predictors at the structural level (Ghozali, 2014).

Predictive Relevance (Q2)
Predictive Fit is useful to confirm the predictive power of a model by evaluating the predictive goodness of the independent variable relative to the dependent variable. This model is only suitable for the dependent variable with reflectance indices. The predicted relevance value if Q2 > 0 indicates a good exogenous latent structure for the model to have predicted relevance. Meanwhile, the value of Q2 and <; 0 indicates a lack of predictive relevance (Narimawati et al., 2020).

T-statistics
The t-statistical test is performed to see the importance of the relationship between the variables in the structural model. T-statistics were performed using the bootstrap (resampling) procedure in SmartPLS3 software. The value of the tstatistic of the bootstrap results will be compared with the value of the t-table. To test the hypothesis, this study uses one-sided with 95% significance level, then the panel t value is 1.65 (Ghozali, 2014). If the t-statistic exceeds 1.65, there is a nonsignificant relationship, while a t-statistic less than 1.65 describes a significant relationship.

Variable operations
Variable operations are used to make abstract implicit variables real and

Demographic Characteristics
Based on the results of the questionnaire distributed via Google Forms medium, 100 respondents who were internal auditors of banks in Indonesia were registered as public companies on IDX. This number is consistent with the target number of the study sample. Respondents in this study came from banks in Indonesia as shown in table 3. The respondents in this study came from a variety of educational backgrounds. This is clearly shown in Table 4 below. Based on experience as a bank internal auditor, 72% of respondents have more than 5 years of experience, 17% of respondents have 3 to 5 years of experience, 6% of respondents have 1 to 5 years of experience. 2 years and the remaining 5% of respondents have less than one year of experience.

Convergent Validity Test
Convergent validity of the value of the external load and the extracted mean variance (AVE) where the threshold value is for each value, namely: for external load/required load factor value is 0.7 (Ghozali & Latan, 2015;Höck & Ringle, 2006). Then, Hair (2019) suggested that the convergence value is considered satisfactory if the average extracted variance (AVE) value is 0.5. The results of the convergent validity test are as follows: Source: processed by researchers Table 5 shows all the values of outer loadings on the indicators used in the measuring the variable is valid because it produces a value of outer loadings > 0.5. Source: processed by researchers Table 6 shows that the three variables used in this study are valid because they produce an AVE value > 0.5.

Reliability Test
The reliability test is used to measure the internal consistency of the measuring instrument. The reliability of the data can be checked by looking at the composite reliability and Cronbach's alpha. Table 6 shows that all variables used in this study are reliable because they produce Cronbach's alpha value > 0.7, except for the dependent variable, namely the effectiveness of Fraud Risk Management. It was concluded that the data had passed the reliability test, so the data could be continued to the next analysis. From table 6 also, the Composite Reliability value of all variables has a Composite Realibility value > 0.7, so the data is reliable.

Coefficient of Determination (R2)
For the data analysis part, the structural model test results (internal model) will be presented first in terms of the coefficient of determination (R2). To determine the value of the coefficient of determination /R-square (R2), the value varies from 0 to 1 and is divided into three evaluation criteria, which are: 0.67 means good, 0.33 means is average and 0.19 means low (Ghozali, 2014).

Source: processed by researchers
Based on the results of the coefficient of determination (R squared) generated by the research concept, it can be concluded that the audit variables, audit committee, corporate culture, IT adoption, testing and policies and procedures on the fraud risk management variable is 0.957 or 95.7%. While the remaining 4.3% (100% -95.7%) is affected by variables other than this research model.

Effect Size (f2)
F2 is used to measure the influence of each specified path pattern. The value of the effect size (f2) is classified into 3, namely, 0.02 describes the weak effect, 0.15 describes the moderate effect, and 0.35 describes the strong effect of the predictive variables implicit report at structure time (Ghozali, 2014).

Source: processed by researchers
Based on the results of f2, it can be seen that audit practices, corporate culture, technology adoption, audit and audit committees have a strong influence on the effectiveness of fraud risk management. Policies and procedures have little effect on the effectiveness of fraud risk management.

Predictive Relevance (Q2)
To determine the predicted goodness of fit (Q2) value, the value ranges from 0 to 1. If the value of Q2 > 0, this indicates that the model used in the study has a good fit. predictive and if the value of Q2 is 0, then the model used in the study lacks the predictive fit. A predictive relevance value closer to 1 means that the search pattern has a higher prediction pattern.

Source: processed by researchers
Based on the results of the predicted relevance value (q squared) generated by the study structure, it is 0.529 for the degree of fraud risk management, which means it is higher than the value of zero. distribution of the risk level of management fraud has a predictive relationship.

Path Coefficient
In this study, the path coefficient test was performed to determine the hypothetical relationship between the variables. The path coefficient has a range from -1 to 1, if the value of the path coefficient is close to 1, it can be concluded that there is a strong positive relationship between the variables. Meanwhile, the value of the path coefficient close to -1 indicates a strong negative relationship between the variables in the hypothesis (Hair et al., 2019).  Table 10 shows a t-statistic was performed in this study to determine whether the hypothesis was accepted or rejected. The hypothesis can be accepted if the value of the t-statistic is greater than 1.65 and the hypothesis is rejected if the value of the t-statistic is less than 1.65. The T statistic value is less than 1.65. The relationship between these lines is the effectiveness of policies and procedures for fraud risk management with a T-statistic of 0.087. Meanwhile, the other 5 path relationships have a significant relationship because they have a Tstatistic greater than 1.65.

T-statistics
A t-statistic was performed in this study to determine whether the hypothesis was accepted or rejected. The hypothesis can be accepted if the value of the t-statistic is greater than 1.65 and the hypothesis is rejected if the value of the t-statistic is less than 1.65. The T statistic value is less than 1.65. The relationship between these lines is the effectiveness of policies and procedures for fraud risk management with a T-statistic of 0.087. Meanwhile, the other 5 path relationships have a significant relationship because they have a T-statistic greater than 1.65.

Hypothesis Test
Hypothesis testing was performed using the t test. The independent variable is said to have a significant influence on the dependent variable if the calculated value of t is greater than the table t and the significant value of the p-value is less than 0.05. The value of t-table in this study is Table 10 shows that there is a significant influence between audit committee, corporate culture, technology adoption, inspection, and audit on management effectiveness. fraud risk. Meanwhile, policies and procedures have no significant effect on the effectiveness of fraud risk management.

Discussion
Data for this study was collected using a questionnaire. Then, the questionnaire data was processed using Smart PLS software. From the data processing results, it can be seen that:

Internal audit
Internal audit has a significant positive effect on the effectiveness of fraud risk management. The results we found in this study were also found by Law (2011), who found that the effectiveness of internal audit had a significant impact on reducing the number of fraud cases reported. In addition to Law, Alleyne, and Howard (2005), in their study conducted in Barbados, also found that companies with internal auditors can be prepared to prevent and detect fraud. Not only that, Halbouni et al. (2016) also found that the internal audit function is the function that has the most impact on fraud prevention and detection in the United Arab Emirates. The findings of this and several earlier studies are also supported by data presented by ACFE (2021) in its Report to Countries 2020, which states that the internal audit function is effective. effective in reducing losses due to fraud and reducing fraud time by 50%. The internal audit function in a bank greatly affects the effectiveness of fraud risk management because internal audit provides objective and independent assurance services to ensure effectiveness, efficiency, and good use. organization's resources. In addition, the internal audit function plays a vital role in corporate governance. A good corporate governance mechanism will encourage efficiency in risk management and control (IIA, 1999).
In addition, Siregar and Tenoyo (2015) found that internal audit is the most used important function in preventing and detecting fraud. The internal audit function in large companies uses advanced technology which is currently growing to assist the role of auditors in operating the company's internal controls. Therefore, an effective internal audit function can help detect a fraud risk at an early stage (Gramling & Myers, 2003) so that internal audit can be seen as the first line of defense against fraud (Nicolãescu, 2013).

Corporate Culture
Corporate culture is stated to have a significant negative effect on the effectiveness of Fraud Risk Management. This result shows that it is not in line with the research found by Siregar and Tenoyo (2015) which states that companies receive threats of fraud due to lack of ethical values. Corporate culture is an important aspect that must be owned by every company. The culture that is owned by a bank will be greatly influenced by the highest management in the company. When the management can create strong cultural values and norms, indirectly the created work environment will strengthen the judgment and attitudes and ethics of employees in the company. Akhsani (2018) agrees that corporate culture does not prevent fraud.

Audit Committee
The audit committee has a significant negative influence on the effectiveness of fraud risk management. Contrary to the findings of this study, Law's study (2011) was conducted in Hong Kong. Law (2011 found that the effectiveness of the audit committee has a significant effect on reducing the number of fraud cases. Furthermore, these conclusions are also inconsistent with the results of Alleyne and Howard (2005), who found that an effective audit committee would be better equipped to handle prevention and detection. currently cheating. In addition, Halbouni et al. (2016) also shows that corporate governance through the audit committee plays an important role in fraud prevention and detection.

Inspection
Inspection is stated to have a positive and significant influence on the effectiveness of fraud risk management. This result is also stated in accordance with the research conducted by Manggala and Kumari (2015), where inspection also has an important role in eliminating fraud, especially inspections that are carried out regularly. In addition, other checks that can be carried out are by checking employee acceptance references, which is also one of the indicators in http://eduvest.greenvest.co.id the indicators of this study. Age-old password protection continues to evolve from what began as just a few digits to now possible biometrics.
The use of password protection in the banking sector has been widely used in digital banking applications and bank operational systems. For example, CIMB Niaga, which is one of the banks that became the research sample, has used biometric password protection for the OCTO Mobile application which is usually used by customers to make transactions so that users can validate transactions with passwords. The use of password protection in the banking sector has been widely used in digital banking applications and bank operational systems. For example, CIMB Niaga, which is one of the banks that became the research sample, has used biometric password protection for the OCTO Mobile application which is usually used by customers to conduct transactions so that users can validate transactions with passwords. The use of password protection in the banking sector has been widely used in digital banking applications and bank operational systems. For example, CIMB Niaga, which is one of the banks that became the research sample, has used biometric password protection for the OCTO Mobile application which is usually used by customers to conduct transactions so that users can validate transactions with passwords.

CONCLUSION
This study was conducted to determine whether the independent variables in this study, including internal audit, corporate culture, audit committee, audit, policies and procedures, and applicable information IT, has an impact on the effectiveness of fraud risk management. Variable in this study from a sample of Indonesian banks listed on IDX, the researchers found that the variables of internal audit, inspection and IT adoption have a positive and significant relationship with the efficiency of the bank fraud risk management. While other variables, namely corporate culture, audit committee and policies and procedures, have a negative relationship with the effectiveness of fraud risk management, although the policies and procedures are not related to the effectiveness of fraud risk management has no significant impact on the effectiveness of fraud risk management.