White-collar crime: a statistical study on its common causes

MultiCraft International Journal of Business, Management and Social Sciences Vol. 2, No. 4, 2011, pp. 44-49 INTERNATIONAL JOURNAL OF BUSINESS, MANAGEMENT AND SOCIAL SCIENCES www.ijbmss-ng.com 2011 MultiCraft Limited. All rights reserved White-collar crime: a statistical study on its common causes Samuel Wei-Siew Liew 1, Chin-Hong Puah 2 * and Harry Entebang 3 1,2,3 Faculty of Economics and Business, Universiti Malaysia Sarawak, MALAYSIA. * Corresponding Author: e-mail: chpuah@feb.unimas.my, Tel +6082-584294, Fax +6082-583339 Abstract White-collar crime has always managed to find its way to corrode the values and ethics that people have in a society. A statistical study was carried out to identify some of the common causes of white-collar crime in Malaysia. To pursue this, survey questionnaires were distributed to both potential and existing investors to assess their view regarding the matter. The study found that, one of the leading causes of white-collar crime in Malaysia is due to the fact that there is a belief that competitors are paying bribes to win contracts, and hence others follow suit. On the other hand, most perpetrators commit white-collar crime because there are many opportune moments for them to do so. Companies should, therefore, gear toward good governance structure and internal controls so as not to give potential and existing perpetrators opportunity to engage in any misdeed. Keywords: White-Collar Crime; Fraud; Internal Control; Governance Structure 1. Introduction White-collar crime can occur or exist in many forms. Gottschalk (2010) categorized it into four main forms, namely: corruption, fraud, theft, and manipulation. Arguably, an apt definition of white-collar crime is perhaps formulated by Edelhertz (1970). According to Edelhertz (1970, p. 3), crime is defined as an illegal act or series of illegal acts committed by non-physical means and by concealment or guile, to obtain money or property, to avoid the payment or loss of money or property, or to obtain business or personal advantage. In a survey conducted by PricewaterhouseCoopers in 2009, it is found that the most common types of white-collar crime perpetrated worldwide were asset misappropriation, accounting fraud, as well as bribery and corruption (PricewaterhouseCoopers, 2009). In Malaysia, the survey initiated by KPMG shows that theft of cash, theft of inventory, fraudulent expense claims, and kickbacks are the most common types of corporate fraud committed (KPMG, 2009). KPMG (2009) also reported that 49 percent of all respondents experienced at least one fraud during the survey period from 2006 to 2008. According to the statistics compiled by the Commercial Crimes Investigation Department (CCID), the number of white-collar crime cases investigated by the police in 2003 was 11,714 cases and it involved approximately RM579 million, and in 2004 the number of cases declined to 9,899 but the amount of losses rose to about RM836 million (Lim, 2005). For the year 2008, the amount of losses recorded a slight increase of about RM846 million, but the number of cases climbed significantly to 17,311 ( White-Collar Crimes, 2009). In another study carried out by the Global Financial Integrity (GFI) (2011), illicit financial flows for the years 2000-2008 from Malaysia is US$291 billion (GFI, 2011). Evidently, the statistics and survey reports showed that the acts of white-collar crime in Malaysia are rampant. Therefore, the purpose of the study is to provide further empirical evidence regarding the pertinent issue so that appropriate actions can be taken to minimize illegal behaviors by irresponsible individuals. Building on such awareness and knowledge, the relevant stakeholders of organizations can make informed decisions to reduce the number of occurrences of white-collar crime and in fact this can be seen as the beginning of a new climate to combat white-collar crime proactively in Malaysia.

45 The rest of the paper will discuss several theories behind the occurrences of white-collar crime and this is followed by describing the methodologies used in the study. We then present the empirical findings and discussions. Finally, conclusions and future research will be provided in the last section of the paper. 2. Literature Review Who are the perpetrators of white-collar crime? According to the survey conducted by KPMG (2009), it has become extremely difficult to profile a typical fraudster. In fact the person can be of any age group, income level, or any tenure of employment. For instance, KPMG (2005) discovered that most fraudsters are in the age group of 26-40, earn an average annual income of RM30,000 and below, and have been employed for between 2-5 years. Nonetheless, both surveys found that men are more typical a perpetrator of fraud than women. It is, therefore, essential to identify and to understand why they resort to such crime. The theories explaining the occurrences of white-collar crime are numerous and they can basically be divided into theories explaining the occurrences by group and by individual. The former involves two streams of research which are labeled as organizational theories and managerial theories of white-collar crime (Gottschalk, 2010). The organizational theories are usually explained using the monopolistic model, which implies that potential criminals have no other choice but are forced to join the criminal organization if they decide to commit a crime (Gottschalk, 2010, p. 212). The managerial theories, in the similar context of collectivity, can be explained using the agency theory. For example, Garoupa (2007) modeled the criminal organization as a family business in which there is one principal and many agents. It is in his opinion that this model makes it difficult to detect and punish the principal unless an agent is detected first. The main stream of research explaining the individualistic occurrences of white-collar crime is labeled behavioral theories (Gottschalk, 2010). The underlying criminology theories relating to behavioral theories, according to Hansen (2009), are differential association theory, self-control theory, social bonding theory, exchange theory, and control balance theory. In simplicity, many researchers found the three main causes of white-collar crime as opportunities to commit crime, situational pressures on the individuals, and issues pertaining to integrity (Ilter, 2009; Romney et al., 1980). The more recent surveys conducted by PricewaterhouseCoopers and KPMG [see PricewaterhouseCoopers (2009) and KPMG (2009)] did not, however, explain the theories leading to the occurrences of white-collar crime, but drew out lists of general factors contributing towards increased incentives/pressures to commit fraud and factors that allowed fraud to take place in the respondents organizations respectively. In its global economic crime survey, PricewaterhouseCoopers identified that the increased difficulty in achieving financial targets is the most influential factor contributing towards increased incentives/pressures to commit fraud, followed by the fear of losing jobs (PricewaterhouseCoopers, 2009). Focusing on the occurrences of crime within organizations, KPMG reported that poor internal controls, and collusion between employees and third party are the top two factors in Malaysia (KPMG, 2009). Naicker (2006) and Seetharaman et al. (2004) also found collusion to be a key motive for the commitment of white-collar crime, but mostly between managers and employees. The latter believed that such collusion is a pervasive problem as it is very difficult to prevent and detect. In another research which concerns the occurrences of white-collar crime in Malaysia, the three highest ranking factors stimulating the crime are inadequate cash security practices, inadequate supervision of staff, and internal auditing failures (Puah et al., 2009). 3. Data and Methodology The target respondent in this study is any potential or existing investor, who is at least 17 years of age, in Malaysia. A convenience sampling procedure is adopted to gather 300 completed questionnaires. The questionnaire is divided into two sections. In the first section, respondents have to fill in their demographic information, and to rate their perception on a five-point numerical scale towards the different causes of white-collar crime in the second section. To increase the construct validity of the questionnaire and the reliability of the findings, the construction of the questionnaire is based on published surveys, researches, and textbooks (Smith et al., 2005). Some examples of the published works are KPMG (2009), PricewaterhouseCoopers (2009), and Puah et al. (2009). After gathering 300 completed questionnaires, the demographic data is translated into a frequency table. One-way analysis of variance (ANOVA) is also conducted to test whether or not the difference in the respondents demographics influence the outcome of their perception towards the causes of white-collar crime listed in the questionnaire. The causes are then ranked according to their mean in a descending manner from the highest mean to the lowest mean. 4. Result Findings Table 1 depicts the profiles of 300 respondents who responded to the questionnaire. Most of the respondents are male, but the percentage difference between male and female is only 1.4%. As an overall, it can be deduced that the distribution of respondents in terms of gender is quite balanced. The bulk of the respondents are in the age group of 20-29. They are mostly Chinese, followed by Malay and the other ethnic groups. Some examples of the ethnic groups are Iban, Bidayuh and Kayan. The number of Indian respondents is the lowest. Concerning the demographic information of marital status, the frequencies for both single and married

46 respondents are almost equivalent. The percentage difference is merely 4%. Almost half of the total respondents are degree holders. The minority of respondents are master s degree or higher, and certificate holders, constituting a combined total of almost 18%. As for the respondents occupation, most of them are working as professionals. Their professions include lecturers, stock analysts, engineers, accountants, lawyers and doctors. They comprise 27% of the total respondents. However, most of the respondents earn less than RM4,000 a month, constituting a combined total of 70.7%. Table 1. Respondents Profiles Demographics Frequency Percentage (%) Gender Male 152 50.7 Female 148 49.3 Age 17-19 19 6.3 20-29 124 41.3 30-39 61 20.3 40-49 58 19.3 50 or above 38 12.7 Ethinicity Malay 41 13.7 Chinese 195 65.0 Indian 7 2.3 Others 57 19.0 Marital Single 154 51.3 Status Married 142 47.3 Divorced 4 1.3 Education SPM or below 54 18.0 Level Certificate 26 8.7 Diploma 59 19.7 Bachelor Degree 134 44.7 Master Degree or above 27 9.0 Occupation Professional 81 27.0 Management & Administration 48 16.0 Clerical 23 7.7 Sales & Services 20 6.7 Technical 9 3.0 Self-Employed 47 15.7 Home Duties 6 2.0 Unemployed 12 4.0 Retired 5 1.7 Others 49 16.3 Income per Below RM2,000 108 36.0 Month RM2,000-RM3,999 104 34.7 RM4,000-RM5,999 49 16.3 RM6,000-RM7,999 20 6.7 RM8,000 or above 19 6.3 Subsequently, Table 2 portrays the one-way ANOVA statistical test results of whether or not the difference in the respondents demographics influence the outcome of their perception towards the causes of white-collar crime listed in the questionnaire. The significance level set for the statistical test is at 5%. The causes of the crime (see Table 3) are greatly influenced by most of the demographics, with the exceptions of gender and income. It implies that an individual s experience, education, working environment, and the community in which he or she lives or grows up do indeed influence his or her perceptions towards the causes of white-collar crime. Table 2. One-Way ANOVA of Respondents Demographics towards the Elements of White-Collar Crime in Malaysia Demographics Causes of White-Collar Crime (F-value) Gender 1.092 Age 6.489** Ethnicity 3.033** Marital Status 8.313** Education Level 3.179** Occupation 2.620** Income per Month 1.693 Note: Asterisk (**) denotes significant at 5% level.

47 Table 3 summarizes the common causes of white-collar crime by rank according to their means. Most respondents are of the opinion that the commitment of white-collar crime in Malaysia is due to the belief that other competitors are also paying bribes in order to win contracts. The other causes, in a descending manner, that record a mean of 3.500 and above are poor internal controls, desire to earn personal performance bonuses, and poor ethical practices. At the bottom of the ranking suggests that peer influence and bonuses not paid this year appeared to be the lowest perceived causes of white collar crime. Table 3. Ranking of the Causes of White-Collar Crime in Malaysia Rank Causes of White-Collar Crime Mean 1 There is a belief that competitors are paying bribes to win contracts 3.630 2 Poor internal controls 3.573 3 Desire to earn personal performance bonuses 3.553 4 Poor ethical practices 3.507 5 Lack of control over management by directors 3.347 6 For senior executives to achieve desired financial results 3.317 7 Management override of internal controls 3.193 8 Maintain financial performance to ensure lenders do not cancel debt facilities 3.093 9 Type of industry 3.057 10 Financial targets more difficult to achieve 3.043 11 Corporate culture 3.027 12 Collusion between employees and third party 3.000 13 Fear of losing jobs 2.983 14 Poor hiring practices 2.973 15 Peer influence 2.760 16 Bonuses not paid this year 2.700 Table 4 shows the ranking of the three groups of white-collar crime causes. The three groups are opportunistic causes, organizational and managerial causes, and behavioral causes. The majority of the respondents perceived that white-collar crime is usually committed because there are many opportune moments for such illegalities to be perpetrated. Following opportunistic causes, the study also revealed that the causes of white-collar crime can also come from the organization and the management of the organization themselves. Behavioral factors, according to the respondents, are the least common contributors of white-collar crime in Malaysia. Table 4. Ranking of the Causes of White-Collar Crime by Group Rank Causes of White-Collar Crime Individual Mean Group Mean 1.0 Opportunistic causes 3.275 1.1 Poor internal controls 3.573 1.2 Poor ethical practices 3.507 1.3 Lack of control over management by directors 3.347 1.4 Management override of internal controls 3.193 1.5 Type of industry 3.057 1.6 Poor hiring practices 2.973 2.0 Organizational and managerial causes 3.222 2.1 There is a belief that competitors are paying bribes to win contracts 3.630 2.2 For senior executives to achieve desired financial results 3.317 2.3 Maintain financial performance to ensure lenders do not cancel debt facilities 3.093 2.4 Financial targets more difficult to achieve 3.043 2.5 Corporate culture 3.027 3.0 Behavioral causes 2.999 5. Discussions 3.1 Desire to earn personal performance bonuses 3.553 3.2 Collusion between employees and third party 3.000 3.3 Fear of losing jobs 2.983 3.4 Peer influence 2.760 3.5 Bonuses not paid this year 2.700 The leading cause of white-collar crime in Malaysia is that there is a belief that competitors are paying bribes to win contracts, and hence others follow suit. This outcome appeared to be inconsistent with that of the survey conducted by

48 PricewaterhouseCoopers (2009), because the same factor is ranked among the lowest in their study. The leading factor contributing towards increased incentives/pressures to commit fraud, according to the survey, is that financial targets become more difficult to achieve, which, in turn, is only ranked at number 10 in this research. However, it must be noted that the survey conducted by PricewaterhouseCoopers (2009) is a global one, including countries not only from the Asia Pacific, but America, Europe and Africa. Hence, this might explain the difference in findings. The second leading cause of white-collar crime found in this research is poor internal controls. This finding is consistent with many studies previously conducted by KPMG in Australia, Singapore and Thailand (KPMG, 2009). In fact, the finding is also aligned with a recent study carried out by Puah et al. (2009). In their study, inadequate cash security practices, inadequate supervision of staff, internal auditing failures, failure to verify identification evidence and inadequate purchasing/procurement controls are found to be the top five factors stimulating corporate crime in Malaysia. These factors can all be classified as poor internal controls within a company. The other common causes of white-collar crime within the top 5 ranking are desire to earn personal performance bonuses, poor ethical practices, and lack of control over management by directors. In PricewaterhouseCoopers (2009), the desire to earn personal performance bonuses is also ranked third as found in this paper. Hence, the result confirms that greed is one of the leading motivations for the commitment of white-collar crime not only in Malaysia, but also globally. KPMG (2009) also reached the same result in identifying greed as the leading motivation for fraud. Concerning poor ethical practices and lack of control over management by directors, they can basically be categorized under what Naicker (2006) called corporate modeling. Some companies do not discourage, or some even encourage poor ethical practices for the sole purpose of profit-making. As a result, the moral base among the employees is lost (Naicker, 2006) and it disrupts a major component of internal control and creates a much higher level of insecurity for the organization (Seetharaman et al., 2004, p.1067). It is also worthwhile to note the 3 bottom ranked causes. They are poor hiring practices, peer influence, and bonuses not paid this year. In line with the outcome of the study, poor hiring practices is among the bottom few factors found in KPMG (2009) that allowed the incidence of fraud to take place in an organization. Nevertheless, Seetharaman et al. (2004) suggest that good hiring practices can, to a certain extent, help to prevent fraud. Peer influence and bonuses not paid this year are found to be the least common cause of white-collar crime. In Malaysia, bonuses are usually paid and hence it does not really come into question as far as the causes of white-collar crime are concerned. 6. Conclusions and Future Research In this study, the findings are perhaps more telling when one examines the causes of white-collar crime in terms of their grouping. Opportunistic causes are found to be the main causes of white-collar crime in Malaysia. Due to poor internal controls and ethical practices, potential and existing perpetrators can always find opportune moments to carry out the crime. In addition, corporate governance can always be suppressed by the board of directors by the overriding of internal controls. The type of industry which also falls under opportunistic causes should be given more weight in view of the recent developments in Malaysia. The findings in KPMG (2009) rank this factor among the lowest and it is ranked at number 9 in this study. As reported in the local news, the Malaysian Anti-Corruption Commission (MACC) has probed into one of the biggest tax evasion implicating Customs officers, involving millions of Ringgit ( RM2mil Traced, 2011). The result of this investigation is perhaps a strong indication that, depending on the nature of their business, some industries do present more opportunities than the others to commit illegalities. For instance, PricewaterhouseCoopers (2009) has continuously found insurance and financial services to record high levels of fraud for over 10 years. Organizational and managerial causes have also contributed towards the occurrences of white-collar crime in Malaysia. The pressure to meet performance targets, particularly, motivates perpetrators to commit the crime. The matter is exacerbated when some employers convey their insatiable desires of gaining extra profits to the employees. Consequently, the employees have to shoulder great pressure in the face of losing their jobs. In the survey conducted by PricewaterhouseCoopers (2009), increased incentives or pressures are found to be the leading contributor to greater fraud risk. Behavioral causes concern issues pertaining to integrity of an individual. Some of the causes under the heading may be linked to pressure. Fear of losing jobs is one of them. The more apparent causes pertaining to an individual s integrity are the desire to earn personal performance bonuses and bonuses not paid this year. Some perpetrators tend to rationalize their misconducts by convincing themselves that they are merely taking what is due to them. Like the findings in PricewaterhouseCoopers (2009), these sorts of causes which pertain to the integrity on a person are the lowest ranked group in this research. More emphasis, therefore, has to be placed in reducing opportunities and situational pressures, particularly in relation to organizational and managerial causes, in order to fight against white-collar crime in Malaysia. In line with increasing awareness among stakeholders, it is recommended for companies not to engage in white-collar crime due to the belief that others are doing the same. The chances of backfire are higher today than in the past as the government has clearly stepped up their efforts in combating white-collar crime. The enactment of the Whistleblower Protection Act 2010 is one good example of such effort. With this in mind, the companies should seriously invest in placing good governance system and internal controls so as not to give potential and existing perpetrators opportunity to engage in any misdeed. Such governances have to be reviewed and improved on continuous basis so that white-collar crime risk can be minimized.

49 The impact of white-collar crime on firm s performance should call for greater attention among researchers and corporate leaders. This study among others has examined some of the common causes of corporate crime in Malaysia. The fact that there are many opportune moments for a crime to occur, future research should investigate the effectiveness of corporate internal control systems in preventing such crime in companies. In addition, a further study should also consider the role of regulators in educating companies directors and top management about the importance of promoting good business ethics and governance for better performance of companies. References Edelhertz, H., 1970. The nature, impact and prosecution of white-collar crime. Washington, DC: U.S. Department of Justice, National Institute of Law Enforcement and Criminal Justice. Garoupa, N., 2007. Optimal law enforcement and criminal organization. Journal of Economic Behavior & Organization, Vol. 63, pp. 461-474. Global Financial Integrity., 2011. Illicit financial flows from developing countries: 2000-2009. Washington, DC: Kar & Curcio. Gottschalk, P., 2010. Theories of financial crime. Journal of Financial Crime, Vol. 17, No. 2, pp. 210-222. Hansen, L.L., 2009. Corporate financial crime: Social diagnosis and treatment. Journal of Financial Crime, Vol. 16, No. 1, pp. 28-40. Ilter, C., 2009. Fraudulent money transfers: A case from Turkey. Journal of Financial Crime, Vol. 16, No. 2, pp. 125-136. KPMG., 2005. KPMG fraud survey 2004 report. Kuala Lumpur: KPMG. KPMG., 2009. KPMG Malaysia fraud survey report 2009. Kuala Lumpur: KPMG. Lim, H.S., 2005. White-collar crime in Malaysia. Retrieved from http://rmpckl.rmp.gov.my/journal/bi/whitecollarcrime.pdf Naicker, K., 2006. White-collar crime in South Africa. (Unpublished doctoral dissertation). University of Johannesburg, Johannesburg. PricewaterhouseCoopers., 2009. Global economic crime survey November 2009. Retrieved from http://www.pwc.com/en_gx/gx/economic-crime-survey/pdf/global-economic-crime-survey-2009.pdf Puah, C.H., Voon, S.L. and Entebang, H., 2009. Factors stimulating corporate crime in Malaysia. Economics, Management, and Financial Markets, Vol. 4, No. 3, pp. 87-99. RM2mil traced., 2011, April 9. The Star, p. N1. Romney, M.B., Albrecht, W.S. and Cherrington, D.J., 1980. Red-flagging the white-collar criminal. Management Accounting, Vol. 61, pp 51-57. Seetharaman, A., Senthilvelmurugam, M. and Periyanayagam, R., 2004. Anatomy of computer accounting frauds. Managerial Auditing Journal, Vol. 19, No. 8, pp. 1055-1072. Smith, M., Omear, N.H., Idris, I.Z. and Baharuddin, I., 2005. Auditors perception of fraud indicators Malaysian evidence. Managerial Auditing Journal, Vol. 20, No. 1, pp. 73-82. White-collar crimes accounted for RM788 mil losses last year IGP., 2009, June 19. Bernama. Retrieved from http://www.insuranceonline.my/2009/06/white-collar-crimes-accounted-for-rm788-mil-losses-last-year-igp/ Biographical notes Samuel Wei-Siew Liew has obtained his Bachelor Degree (Bachelor of Law) from the University of London and his Master Degree (Corporate Master of Business Administration) from Universiti Malaysia Sarawak. Currently, he is working as a National Officer in Standard Chartered Bank in Kuala Lumpur, Malaysia. Chin-Hong Puah is an Associate Professor cum Associate Managing Editor of International Journal of Business and Society in the Department of Economics, Faculty of Economics and Business, Universiti Malaysia Sarawak, Malaysia. He has more than 13 years of experience in teaching and research. His current area of research includes Monetary Economics and Applied Macroeconomics Studies. Harry Entebang is a Senior Lecturer in the Department of Business Management, Faculty of Economics and Business, Universiti Malaysia Sarawak, Malaysia. He has more than 20 years' experience as practitioner, academician and researcher. His current area of research includes corporate entrepreneurship and financial performance measurement of firms. Received September 2011 Accepted October 2011 Final acceptance in revised form October 2011