The impact of forensic accounting tools in investigating white-collar crime

. This study examines the impact of forensic accounting tools in the investigation of white-collar crime in Malaysia. Models consist of multiple regression has been evaluated. Our results show, the impact Encase software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK), and ProDiscover Forensics have a significant relationship with investigating white-collar crime in Malaysia. Firstly, Encase is widely acknowledged as the world's premier provider of digital forensics, cyber security, and electronic discovery, making it the gold standard for criminal digital forensics. Secondly, CAAT allows a database of thousands of transactions to be centrally audited and finished more efficiently and quickly. Thirdly, FTK's primary purpose is speed and performance, hence it concentrates on pre-indexing files to improve speed. It is compatible with electronic discovery and mobility. Lastly, ProDiscover is a great computer security tool because it enables computer specialists to swiftly locate all data on computer disks and safeguard evidence for use in legal procedures. This study raises awareness of forensic accounting tools to investigate white-collar crime more effectively. Keywords: White-Collar Crime


Introduction
The term white-collar crime was coined in 1939 by sociologist Edwin Sutherland. To identify crimes committed by respectable persons of high social status, he used the word "white-collar crime". Now "white-collar crime" is used to describe businessmen and government officials who commit various kinds of fraud in their daily life (CFI Education Inc., 2021).
Miele & Rymsza (2018) stated that one study found that about 36% of businesses and 25% of households are victims of white-collar crime, showing that white-collar crime has a greater effect than property crimes or violence-related crimes. Moreover, because whitecollar crime has a significant effect on individuals because white-collar crime typically requires thousands or even millions of dollars, it will cause them to lose all their wealth, lead indirectly or directly to the failure of their families or the bankruptcy of their businesses, and eventually, they will choose to commit suicide. White-collar crime prosecutions are mainly against individuals, corporations, and business organizations are rarely prosecuted. This is because the occurrence of white-collar crime is mainly related to personal interests. Only 1,300 companies or business entities were prosecuted for white-collar offences between FY2004 and FY2020, compared to 124,402 individuals. As exhibit 1.1 shows, between FY2004 and FY2020, only one in every 100 white-collar crimes involved a company or business entity (TRAC, 2020).
According to HG.org Legal Resources (2021), more than 80 percent of crimes in Malaysia are property crimes. Property crime is also known as white-collar crime. Property crimes include bribery, forgery, bank fraud, embezzlement of public funds, and so on. According to Liew et al. (2011) stated in Malaysia, 11,714 white-collar crime cases were investigated by the police in 2003 with a loss of RM579 million and 9,899 cases with a loss of RM836 million in 2004. In 2008, the number of cases of white-collar crime in Malaysia increased to 17,311, with a loss of approximately RM846 million. According to the statistics above, white-collar crime is very serious in Malaysia. As can be seen from Exhibit 1.2, the number of white-collar crimes is decreasing gradually because the FBI analyzes white-collar crimes and investigates and tracks down criminals and stops them before the scams start. Overall, the number of white-collar crimes fell 68.70 percent from 8,108 cases in 2008 to 5,570 cases in 2018 (TRAC, 2018). Although white-collar crime cases are gradually decreasing, but the impact of white-collar crime is very serious, so we should be cautious when investigating white-collar crime.
On the other side, corporate fraud is also on the rise. Based on the KPMG Fraud Survey 2004, which examined 130 publicly traded businesses, 83 percent of respondents reported to having experienced fraud, a 33 percent increase over 2002. According to the report, the three most common types of fraud seen by Malaysian businesses are covert commissions or kickbacks, lapping (withholding cash receipts) and kiting (too many accounts) and fake invoicing (Qureshi et al., 2015).
According to the above shows, white-collar crimes are becoming more and more serious in society and will cause serious negative effects. However, the forensic accounting tools in investigating white-collar crime is a paucity of research. Therefore, this research study will discuss the impact of forensic accounting tools including Encase software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK), and ProDiscover Forensics to investigating white-collar crime.
2 Literature review 2.1 Encase software Qureshi et al (2015) defined Encase software as a toolkit for capturing, analyzing, and reporting digital evidence. It encompasses most of the work done by ITM (Information Technology Management) forensics analysis. For analysis, web surveys, civil or criminal surveys, data surveys, and electronic digital media can all be used. It is appropriate for law enforcement agencies and businesses because it has been employed effectively in numerous court systems across the world. Furthermore, encase is widely acknowledged as the world's premier provider of digital forensics, cyber security, and electronic discovery, making it the gold standard for criminal digital forensics.
According to Ghazinour et al. (2017), Encase investigation process consists of classification, collection, decryption, procedure, investigation, and reporting. Encase's classification refers to the fact that it enables users to read it more quickly, request prospective validation, and assist in determining whether it is reasonable. Collecting refers to acquiring further evidence via a range of file types and operating systems. Furthermore, encase can also operate with Tableau hardware to unlock or repair passwords. The process of Encase investigation means that it can automate complex queries to improve speed and performance. The ability to employ survey analysis evidence and expertise to conduct an inquiry follows, and the process concludes with reporting. Encase provides a reporting structure from which investigators or users can generate reports.
Apart from that, encase also provides powerful filters and scripts for collecting trustworthy evidence and information from Internet activity, chat sessions, emails, files, graphics, and over 200 different file types for investigators. In addition, encase can also examine data, such as system files and encrypted or concealed data that other programs cannot access. Furthermore, encase can assist in the recovery of destroyed digital evidence such as files, disk reformatting, file concealing, and printing spools (Abdulkadir et al., 2021). Therefore, encase software can help decrease the duration of investigations, save money, and reduce liability risk.

Computer Aided Audit Tools (CAAT)
Widyastuti (2019) defined computer-aided auditing tools (CAAT) is a device and technology used to verify and process the internal logic of computer programs with data. CAAT allows a database of thousands of transactions to be centrally audited and finished more efficiently and quickly. Therefore, this software aids in the efficiency of forensic accountants. Furthermore, with the use of CAAT, forensic accountants can perform more precise financial statement analyses and informed discussions.
Moreover, because CAAT tools include ACV auditing, command languages, thought analysis, WIZ rules, and so on, it has advantages over manual data testing techniques. With the CAAT tool, forensic accountants can more accurately review, test, and analyze all the data to avoid white-collar crime because computer-based data analysis tools can collect the profile of possible fraud. Apart from that, CAAT has also established opportunities for automatic red flags that will reveal differences in data that should be unified (Qureshi et al., 2015). Olasanmi (2013) mentioned that because it is difficult for auditors to obtain sufficient or relevant evidence by using manual or traditional audit techniques, computers can be used as an auxiliary tool to obtain audit evidence. In addition, since 1982, CAAT has been a robust financial audit tool and the most extensively used audit program. These general-purpose module computer programs can be used to read existing computer files and execute sophisticated actions on the data contained in the files to complete audit duties. Overall, CAAT is a significant information-gathering tool for auditors since it can extract and analyze data to improve the reliability of auditors' test results. Kamal et al. (2020) stated that it is difficult to finish the audit process using only human factors, hence auditors employ CAAT to assist them in doing all audit activities. Furthermore, CAAT reduces the time and expense of auditing by allowing auditors to do automated audits to repeat the audit job. Furthermore, auditors can use CAAT rather than a single sample to test 100% of the population, increasing the dependability of audit test outcomes and improving corporate efficiency and performance.

Forensic toolkit (FTK)
According to Kapoor et al. (2019), the Access Data Group created the Forensic Toolkit (FTK). Due to FTK being the only product that employed a multi-core CPU to function in parallel, FTK reported a 400% reduction in survey documentation when compared to other tools. Furthermore, because it is a shared case database, all data can be accessed in a single location. This not only saves resources for the organization, but it also enhances work efficiency. FTK's primary purpose is speed and performance, hence it concentrates on preindexing files to improve speed. It is compatible with electronic discovery and mobility. Furthermore, this comprehensive survey solution includes email analysis, data sculpting, data visualization, file decryption, Web Viewer, OCR, and Cerberus support.
Moreover, features of FTK include the ability to use Known File Filters (KFF) to help investigators focus on projects of interest, the use of internal viewers to help investigators view Word, PowerPoint, and Excel documents and various images, and the use of keyword retrieval functions (Ambhire & Meshram, 2012). Abdulkadir et al. (2021) mentioned that FTK is simple to use for analysis because it can decrypt files or folders and locate extra important information. When you add evidence to a case and choose Decrypt EFS Files in the New Case Wizard, FTK runs PRTK and decrypts EFS files. Furthermore, FTK may be used to recover encrypted Instant chats as well as extra information such as contact lists. Finally, FTK is regarded as one of the primary forensics tools for doing E-mail analysis by law enforcement and corporate security specialists since it can readily discover the location of deleted e-mails and has powerful filtering and search functions (Qureshi et al., 2015).

ProDiscover Forensics
According to Ghazinour et al. (2017), ProDiscover Forensics is characterized primarily by flexibility and speed. In addition, its features include inspection, image acquisition, and search in hardware reserves. ProDiscover is a great computer security tool because it enables computer specialists to swiftly locate all data on computer disks and safeguard evidence for use in legal procedures (Ambhire & Meshram, 2012). For example, it searches for keywords using the Boolean function to find the proof you seek. By using the included data from the National Drug Intelligence Center in their Hashkeeper Database, you can use the hash comparison capability to find known illegal files or to weed out known good files such as standard operating system files (Ghazinour et al., 2017).
In addition, Ambhire & Meshram (2012) agreed that the features and benefits of ProDiscover include that it can search the entire file or disc to complete the analysis of disc forensics, including alternate data sources for Slack room, HPA segment, and Windows NT/2000/XP. Furthermore, images in the ubiquitous UNIX® dd format can be read and written and images in the E01 format can be read. To ensure that nothing is hidden, it is helpful to analyze and refer to the data in the file, as well as utilize Perl Scripts to explore the task automatically. It is also built-in accordance with the NIST Disk Imaging Tools criteria to assure good quality. Exhibit 2.1 shows the conceptual framework of the hypotheses developed based on the expected relationship between the independent variable and dependent variable. This study uses the impact of forensic accounting tools and examines the following hypotheses: H1: There is a positive relationship between the impact of Encase software and investigating white-collar crime.
H2: There is a positive relationship between the impact of Computer Aided Audit Tools (CAAT) and investigating white-collar crime.
H3: There is a positive relationship between the impact of Forensic toolkit (FTK) and investigating white-collar crime.
H4: There is a positive relationship between the impact of ProDiscover Forensics and investigating white-collar crime.

Data and methodology
The primary data of this research study will be obtained through an explanatory questionnaire survey. Besides, the secondary sources are collected from existing literature, books, websites, and other reliable methods. This research study set target groups such as forensic accountants, auditors, and accountants of different organizations to collect the primary data and develop a questionnaire. In addition, due to time and budget constraints, data sources for this study were collected through the Internet. In this study, it is expected that there will be 100 questionnaires and responses. Lastly, feedback for this study will be collected via Google forms and direct email distribution.
This questionnaire of this study has a total of six sections. An estimated total of 32 questions. The first section is the demographic variable under investigation (gender, nationality, age, academic qualification, position), while the other sections include measurements of dependent variables which as white-collar crime, and independent variables such as Encase software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK) and ProDiscover Forensics. In addition, the Likert scale was used in this study (1= Strongly Disagree to 5= Strongly Agree) to calculate each variable in this questionnaire to provide more real and reliable data in the research study of Encase software, Computer Assisted Audit Tools (CAAT), Forensic Toolkit (FTK) and ProDiscover Forensics and to have a relationship with white-collar crime investigation.
Data processing would insert the questionnaire questions into an Excel spreadsheet and then pass all the information to the Google Docs folder to send the questionnaire electronically to the individual respondents in this sample. Then, after all the data has been obtained, to extract the hypothetical relationship, the data collection will continue to be loaded into the SPSS program. to determine if a dataset is heavy-tailed or light-tailed when compared to a normal distribution. A high kurtosis has a heavy tail with more outliers than a low kurtosis, which has light tails and few outliers (Wulandari, 2021). The Kurtosis for dependent variable in this study is at 1.827. In terms of independent variables, the kurtosis values are at 3.103, 2.769, 3.249 and 2.642. Cronbach Alpha was used to test the reliability of variables in this study. The formula for Cronbach Alpha is N= number of items, C = average covariance between item pairs, and v= average variance. Cronbach's alpha has an acceptable value between 0.70 and 0.95 (Taber, 2017). Tables 4.2.1 show Cronbach's alpha reliability coefficients of dependent and independent variables. The proportion of items per variable. The number of items per variable is also shown in both tables, which represents the number of questions asked in each variable. Table 4.2.1 shows that Cronbach's alpha value of White-collar crime is 0.912. In addition, Encase Software value is 0.912, Computer Aided Audit Tools (CAAT) value is 0.887, Forensic Toolkit (FTK) and ProDiscover Forensic were 0.904 and 0.914 respectively. Therefore, the values of dependent and independent variables in this study are greater than 0.7, and the alpha value is reliable.  1 and 4.3.2 give the test of normality of the dependent variable, white-collar crime, in this study. As a result, descriptive analysis is done on variable data, such as mean, standard deviation, and, of course, skewness and kurtosis. Exhibit 4.3.1 shows the histogram of the dependent variable, white-collar crime, after the normality test, and the histogram skewed to the left.

Normality Test
Because of Shapiro and Wilke tests, the sample size was limited to less than 50 participants (Mishra et al., 2019). As a result, the sample size of this study is 173, researchers are examining the Kolmogorov-Smirnov column in this study. The normal test criterion indicates that the survey distribution is normal, and the p-value should be bigger than 0.05. The Kolmogorov-Smirnov tests show that the significant level is less than 0.001, which is less than 0.05, as shown in Table 4.3.2. Hence, the findings of this investigation are abnormal, and a Z score test is required. The z-value is calculated by dividing the kurtosis (1.827) by the standard error (0.367), which is 4.97. When the z value is less than or greater than 3.29, P < 0.001 is significant, indicating that the sample distribution is normal (Ghasemi and Zahedal, 2012). It is in this range because the z-score = -3.29 is bigger than 3.29. Therefore, it can be demonstrated that the dependent variable in this study, white-collar crime, is normal. Based on the table 4.5.1 correlation analysis carried out White-collar crime, Encase software, Computer-aided audit tools (CAAT), Forensic Toolkit (FTK), Prodiscover Forensic have obtained the coefficient values of 1,0.840,0.836,0.817,0.771 respectively. By analyzing these results, it is known that Encase software has the highest correlation with the white-collar crime while Prodiscover forensic has the lowest correlation with white-collar crime.  (Dhakal, 2018). The R-value range of -1 to 1 indicates whether the association is positive or negative. Whereas R square represents the rate of variation in the dependent variable as indicated by the linear regression model (Frost, 2017). As indicated in Table 4.6.1, the multiple R depicts the correlation coefficient, which is at 0.860, indicating a high degree of correlation and acting as a multiple correlation value between the real and expected values of the dependent variable. The R square value ("R" ^"2") represents the coefficient of determination, which indicates how much variation falls on the regression line and is at 0.740, indicating that the four independent variables can explain 74.0% of the dependent variable in this study. Following that, the summary demonstrates a substantial association between white-collar crime and the independent variables Encase Software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK), and ProDiscover Forensic. Finally, other factors can influence or support the remaining 26.0% of white-collar crime.  Dhakal (2018)'s study, when the significant value is less than or equal to 0.05, it indicates that the relationship between the two variables is significant and the null hypothesis will be rejected, whereas p-value > 0.05 indicates that the relationship between the two variables is not significant and the null hypothesis will not be rejected. This table shows that the significance level is lower than 0.001, which is lower than 0.05, indicating that the relationship between the dependent variable and the four independent variables is significant. Hence, the null hypothesis should be rejected.  Based on Table 4.8.1, all the relationships between the dependent variable white-collar crime and independent variables Encase Software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK), and ProDiscover Forensic are accepted and able to affect each other. The methods used to test the hypothesis result in significant relationships.

Conclusion
Forensic accountants, compliance officers, organizations, and audit firms must be aware of white-collar crime. A positive work environment can help to reduce the occurrence of whitecollar crime. The basic tool for investigating white-collar crimes is forensic accounting. Many studies have been conducted, and it has been discovered that there is a positive relationship between the impact of forensic accounting tools and white-collar crime. Forensic accounting tools can thoroughly analyze white-collar crime to assist auditors in more effectively investigating or even reducing the occurrence of white-collar crime. Because white-collar crime is primarily motivated by personal gain, it is rarely detected or prosecuted. On the other hand, Forensic accounting tools frequently provide powerful filters and scripts to collect credible evidence and information from multiple file types to assist in the investigation of white-collar crime. In this study, the researcher proposed four variables of forensic accounting tools in investigating white-collar crime.
This study examined the effectiveness of forensic accounting tools such as Encase Software, Computer Aided Audit Tools (CAAT), Forensic Toolkit (FTK), and ProDiscover Forensic in the investigation of white-collar crime. Throughout the study, it was discovered that all four independent variables mentioned above have a positive and significant relationship in the investigation of white-collar crime. Furthermore, the results show that the most significant relationship exists between the Encase software and the investigation of white-collar crime. However, the other three variables are also important in investigating white-collar crime and should be considered by auditors or accountants.