Keywords

Anti-Money Laundering Regulations, Making Financial Decisions, Jordanian Commercial Banks.

Introduction

Money Laundering has become one of the hot topics internationally, governments, security agencies and all financial organization in general and specially banking ones seek to resist this phenomenon due to the threat it poses to peace and national security (Unger et al. 2014).

Money Laundering is considered a significant and effectual topic and effectual on the national economy so as governments security agencies and all financial organization in general and specially banking ones works intensively to fight it because of the hazards it presents in the way to national peace and security (Aini & Nahariah, 2018).

The concept of Money Laundering has possessed the attention of financial and economic policy makers and specially those interested in monetary and banking policies whether at local, regional or national level. Henceforth, there is no agreement on one definition for this concept because of the multiplicity of illegal resources of cash, the difference in perspectives about these resources and the diversity in laundering means and methods (Levi, 2014).

Consequently, this study emerged to identify the effect of anti-money laundering regulations on making financial decisions at Jordanian commercial banks.

The Problem of the Study

The researcher has been guided to the problem of the study through reviewing previous researches and studies that recommended more investigation of combating money laundering operations and financial decisions such as the study of Al-Rikabi & Talib (2012); Obaid & Ali (2014); Irshaid (2018); Loayza et al., (2018); and Colladon & Remondi (2018). Therefore, the objective of this study is to identify the effect that anti- money laundering regulations can have on making financial decisions in Jordanian commercial banks.

Study Questions

To this end, the study will attempt to answer the following questions:

Main question: Do anti-money laundering regulations by their dimensions (money transfers risks, transaction risks and bulk cash smuggling risks) have an effect on making financial decisions in Jordanian commercial banks?

The following sub-questions emerged from the main question of the study:

1. Do money transfers risks regulations have an effect on making financial decisions in Jordanian commercial banks?

2. Do transaction risks regulations have an effect on making financial decisions in Jordanian commercial banks?

3. Do bulk cash smuggling risks regulations have an effect on making financial decisions in Jordanian commercial banks?

The Importance of The Study

The importance of the study is divided into:

1. The Scientific Importance: The scientific importance of this study is represented in its pursue to provide a brief theoretical framework of the operations of money laundering based on reviewing books and studies comprising an important addition to Arabic library with a modern study about the effect of anti-money laundering regulations on making financial decisions at Jordanian commercial banks. The researcher also hopes that other researcher could benefit from this study so that its results and recommendation be a starting point for future studies in this field.

2. The Practical Importance: The practical importance of the study is clarified in the attempt of this study to provide an effective internal control system within the commercial banks supported by effective auditing system that is considered an independent correction means contributing to promotion of the effectiveness and the efficiency of the operations and to ensuring the commitment to instructions and laws issued by the Central Bank to combat the crime of money laundering due to its bad effects on the national economy of the country.

The Study Hypothesis

Based on the problem of the study and its questions, the following hypotheses has been formulated:

H0: Anti-Money Laundering Regulations by their dimensions (money transfers risks, transaction risks and bulk cash smuggling risks) has no statistically significant effect on making financial decisions at Jordanian commercial banks.

The Study Model

To achieve the goal of this study in identifying the effect of the independent variable on the dependent variable, the researcher has built a virtual study model represented by Figure 1.

Table 1: Study Model References
Variable	Studies and References used
Independent Variable	Irshaid (2018); Loayza et al., (2018); Colladon & Remondi (2018)
Dependent Variable	Aini and Nahariah (2018), Soni et al., (2018)

Procedural Definitions

Money laundering systems: These are practices of illegal activities when transferring the money generated in banks enjoying a sound legal appearance in terms of their sources.

Risks of money transfers: These are transfers of funds acquired from illegal and criminal activities with falsification of its source or covering it up in Jordanian commercial banks.

Transaction risk: These are unlawful mergers of wrongfully acquired funds in various financial and economic operations in banks.

Bulk cash smuggling risks: It is the phenomenon of theft and smuggling of currency and its sale in international markets, or by smuggling machines, equipment and factories abroad.

Financial decision-making: Decision-making is defined as choosing one of the achievable alternatives according to resources. It is also known as the primary goal that banks aim to achieve through administrative operations, which is to reach the appropriate decision to develop them or to solve a problem.

Theoretical Framework

The First Topic: Anti-Money Laundering Systems

Laundering is a set of practical and successive operational stages that organized crime gangs undertake to legalize illicit money to find a source that appears legitimate to it. This is done through various means and tools in order to launder the dirty money of the crime gangs that he gained from the practice of crimes prior to the laundering. Then, this money needs to be laundered and put in both banking and non-bank channels to keep away suspicion of crime from it and to demonstrate it as honest and pure money (Bello & Harvey, 2017).

As considered a white crime, Money Laundering can be defined "as an international organized crime, whereby a person conducts a series of successive financial operations on illicit funds resulting from illegal activities, punishable by the state's legislation, this person using the intermediaries as an interface to deal using the climate of administrative corruption and the confidentiality of banking accounts to secure their dirty money from regulatory and security prosecution” (Savona & Riccardi, 2017).

Money Laundering is the "process by which one conceals the existence illegal source or illegal application of income and disguises the income to make it appear legitimate (Duncan, 1994).

The strict definition: It is the illicit money generated by the drug and psychotropic substances trade. Among jurisprudence legislation is The United Nations Convention Against Illicit Traffic in Narcotic Drugs and Psychotropic Substances, adopted in December 1988 in Vienna and the recommendation issued by the Council of the European Community in (1991) (King, 2018).

Reasons for the emergence of money laundering operations: The money laundering operations were caused by reasons related to the economic, political, moral and banking levels. Among the most important of these reasons that have helped the emergence and spread of money laundering operations are administrative and political corruption such as crimes of embezzlement of public money and the emergence of bribery, which in fact has become the most important crimes associated with administrative corruption, as well as their direct link in money laundering operations. These embezzled sums and large bribes are deposited in foreign banks and after a certain period return again to the country of the corrupted person as legitimate so that he is able to buy assets or repeat the process and expand its channels (Savona & Riccardi, 2017).

In addition to the overlapping of global outlets in the era of economic globalization, the openness occurring between countries and the technical development in the field of electronic communications and networks without facing any obstacles, the spread of unemployment and the deficit of the local economy, and the hunger due to the inability of productive sectors to provide the basic needs of society (Abdel Azim, 2017) . Also, the reasons that led to the emergence of money laundering operations are the absence of a financial (intelligence) policy that tracks the progress of banking operations, the lack of methods in banks that reveal the identity of the beneficiary account holders, and the expansion of the base of relations between banks, which increases suspicious financial services and channels that pretend to be legitimate and are used as a cover for cash transactions. One example is foreign exchange trade (Abboud, 2017).

The Elements of Money Laundering Crime

Money Laundering as any crime consists of two elements: the physical element (actus reus) and the moral element (mens rea). Actus reus sometimes called the external element or the objective element of a crime, is the Latin term for the "guilty act" which, when proved beyond a reasonable doubt in combination with the mens rea “guilty mind” (the mental element of a person's intention to commit a crime; or knowledge that one's action or lack of action would cause a crime to be committed) produces criminal liability in the common law (Dawe, 2013).

1. Actus reus It is known that the physical side, or the outward appearance of the crime, that it is possible to assault the public or private interest. Hence, the physical side is the basic condition for researching the availability of the crime or not, and this pillar is based on three elements: behavior, the overall result, and the causal relationship between them (Treasury, 2017).

2. Mens rea is the intent a person has behind committing a crime. The moral component of the intended crime is generally when the offender’s behavior turns into behavioral will. But the intended crime in particular is to achieve a certain purpose in committing criminal behavior and to conceal money or disguise its nature, source, or location (Mills et al. 2013).

The Second Topic: Making Financial Decisions

Financial decision-making is defined as the most appropriate choice and not the best alternative to the decision to accomplish the goal or existing goals, or to solve the problem awaiting the appropriate solution. (Hanafi, 2004). But, Imran (2007) defined it as "the process that builds on study and objective thinking to reach the specific decision, that is, the choice between alternatives." The decision-making process is defined as the process of choosing an alternative from two or more potential alternatives to achieve a goal or a set of goals during a specific time period in light of the data of both the internal and external environment of the organization (Abbas, 2008) (Table 2).

Table 2: Classification of Decisions According to Simon
Item	Programmed Decisions	Programmed Decisions
Nature	Frequent and routine	Infrequent and non-routine
Decision Criteria	Clear	Personal judgment
Determination of Alternatives	Easy	Difficult
Circumstances	Certainty	Semi-uncertainty
Procedures	Identified	Unidentified
Information	Available	Insufficient
Solution tools	Quantitative methods and Commercial Off The Shelf software	Experience and Developed Software

It was also known as this conscious behavior, which aims to test or use the best means to reach its goal or be executed to achieve a goal (Zgood, 2009). Fadhel (2009) defines the concept of decision-making as the process of conscious choice for the goals that are not. The administrative decision is defined as choosing the best available alternative after studying the expected results of each alternative in achieving the required goals (Manasir, 2010).

Types of decision-making:

1. An investment decision: It is a decision that is based on immediate spending in order to benefit from profit on several consecutive periods (Piget, 2011).

2. The financing decision: It is defined as the decision that relates to the types of sources of funds and how to obtain them, and the balance between their different types in order to reach the optimal capital structure (Jamam & Debash, 2015).

3. Dividend decision: It relates to the portion of the profits that will be distributed to shareholders and the portion that will be reinvested. This decision results from the previous two decisions, so the better the investment decision and the financing decision, the more the organization can expect its profits to rise regularly (Jamam & Debash, 2015).

Classification of decisions according to the type of participation:

a. Individual decisions: They are taken by one director as the chief in the organization and the law allow him/her to make these decisions, such as the decisions related to employment and promotion (Al-Rawi, 2000).

b. Organizational decisions: which are shared by many managers and committees in the meetings from binding general rules that apply to an unlimited number of individuals such as issuing regulations and determining the powers to be followed (Al-Shanti, 2010).

Classification of the decisions according to administrative levels:

a. Strategic decisions: are those decisions that are influenced by the external environment of the organization, its mutual relationship and the extent of interaction with it. Or they are the ones that aim to change the company's goals in the long term and the desired overall shape for the organization in the future. In other words, are the decisions that determine what the organization will be in the future such as its size, competitive position or market share (Aql, 2014). Senior management is responsible for this type of decision and one of its most prominent characteristics is that it is rare and related to the organization as a whole and is taken in the event of uncertainty (Al-Zubaidi, 2001).

b. Tactical decisions: are the functional decisions that are taken at the middle management level to reach optimum performance for the various function activities in the organization such as production, marketing, human resource and other functions. These decisions are characterized by being related to short-term activities, involving an acceptable degree of certainty and are usually less ambiguous, less complex and less Repetitive. Such as making decision that is concerned with placing control on production, financial, management, etc. Or a decision regarding the choice of an informational program for accounting. (Bangma et al., 2017).

c. Operational decisions: They are related to making sure that the tasks and activities have been implemented efficiently and effectively. They aim to run normal matters and to solve daily problems, which are frequent decisions, for example, the decision to specify the necessary amount of the raw material in order to place the stock in the safety rate. Calculating and distributing workers’ wages and the decision to monitor product quality (Weston et al., 1996).

Previous Studies

Al-Rikabi & Talib (2012) in their study aimed to identify the effectiveness of internal auditing and its impact in limiting the phenomenon of money laundering. The study has adopted the descriptive analytical approach in testing the hypothesis of the study, samples were drawn from private banks in Bagdad and 35 copies of the questionnaire were distributed to internal auditing department employees in these banks. The statistical analysis demonstrated that internal auditing has a direct impact with 60 percentage in limiting money laundering. The rest of the percentage could be attributed to other factors such as legal, administrative or applying international standards.

Obaid & Ali (2014) in their study sought to measure the extent of the role of the external auditor in light of contemporary challenges in reducing the phenomenon of money laundering in Iraqi banks listed on Iraq Stock Exchange. The study has adopted the descriptive analytical approach in analyzing the study hypotheses, the research population consists of Iraqi banks enlisted on Iraq Stock Exchange. The research sample is represented by Sumer Commercial Bank and Al-Mansour Bank in order to effectively diagnose the availability of indicators of money laundering practice. This was done by relying on the financial statements for the year 2012 and the indicators and observations it contained, in addition to preparing a questionnaire for the purpose of obtaining information about other research variables. The results of the statistical analysis showed that banking institutions are the main target by money launderers to start the money laundering process. It recommended increasing the interest and knowledge of the external auditor in information technology, which began to form the largest part of banking operations in order to be able to carry out his work with professionalism and high quality.

Irshaid (2018) study deals with the attempts to Islamize Banks constructed by usury money or through Islamic escape windows depending on usury brotherhood, or money laundering in an Islamic method. It discusses constructing Islamic establishments with virulent profits, added to the absence of the Islamic standard for circulating their money through the legitimate exchange rates, by laundering them in an Islamic method. The study deals also with these banks' deviation from the real purposes of the Islamic Banking. It tries to define the constructing legitimacy, the impact of the ill-gotten money on the gained profits by investing through legitimate methods. The study concluded the opposition of these banks to the religious values, and the deviation of these banks from the proper implementation of the Islamic capital deals. The study came to the result that these banks have deviated from the real purposes of Islamic exchange procedure and values. The study recommended, given that manpower engaged in usurious work and deviates their understanding of the difference in application between Islamic banking and the usurious model, which made these scams assets and goals.

The study of Ashmila & Sonan (2018) aimed to measure the problem of having legislation that balances the country's economic interests and the rights of individuals in the confidentiality of their banking operations. The descriptive analysis approach was adopted through the study’s dependence on the secondary sources represented in the financial statements for the period (2010- 2016). The results of the study show that the Libyan law has laid down the policy and rules related to bank responsibility dealing with money laundering. It recommended that Libyan banks face the phenomenon of money laundering through a set of procedures and rules laid down by the Libyan Central Bank.

Loayza et al. (2018) aimed at economic analysis of illicit activities and money laundering. The analysis draws a set of macroeconomic equations that can be estimated to measure the size of laundered assets in the Colombian economy in the period (1985-2013). The study collected a set of data whose main components are estimates of illicit income from drug trafficking and ordinary crime. Illegal incomes increased dramatically until the year (2001), and reached a peak of about (12%) of GDP. Then it decreased to less than (2%) by 2013. The results show that the size of laundered assets increased from about (8%) of GDP in the mid-1980s to a peak (14%) by the year (2002), but it decreased to (8%) in (2013). The study recommended encouraging economic analysis methods for illegal activities to reduce the phenomenon of money laundering.

Colladon & Remondi (2017) aimed to explore the opportunities for the application of network analytic techniques to prevent money laundering. The researchers worked on real world data by analyzing the central database of a factoring company, mainly operating in Italy, over a period of 19 months. This database contained the financial operations linked to the factoring business, together with other useful information about the company clients. The study proposed a new approach to sort and map relational data and present predictive models based on network metrics - to assess risk profiles of clients involved in the factoring business. The study found that risk profiles can be predicted by using social network metrics. In the study dataset, the most dangerous social actors deal with bigger or more frequent financial operations; they are more peripheral in the transactions network; they mediate transactions across different economic sectors and operate in riskier countries or Italian regions. Finally, to spot potential clusters of criminals, we propose a visual analysis of the tacit links existing among different companies who share the same owner or representative. The study findings show the importance of using a network-based approach when looking for suspicious financial operations and potential criminals.

Study Methodology

The study relied on the inferential descriptive approach in order to obtain the necessary data for that for the purpose of analyzing and classifying data to describe the study sample, and presenting it in the form of tables and forms. A questionnaire was designed to collect data that was analyzed using the SPSS program, then the results of the study and its recommendations were presented. The questionnaire was used as a tool to collect data related to the study variables.

The study population and its sample: The study population was consisted from all 13 Jordanian commercial banks, according to the (Directory of Banks in Jordan 2018). This sector was chosen due to its importance to the national economy and the daily life of the citizens. Three out of these banks rejected to accept the copies of the questionnaire, so the sample consisted of the rest ten banks. The sampling unit comprised branch managers, their deputies and heads of departments in Jordanian commercial banks, at all administrative level summed to 219 individuals. They all received the copies of the questionnaire, the restored copies equal to 212 copies, 14 of which were neglected because of their inconvenience for statistical analysis. The copies that were statistically treated summed 198 copies with a restoring percentage of 90.4%. The questionnaire was validated as follows:

The study population and its sample: The study population was consisted from all 13 Jordanian commercial banks, according to the (Directory of Banks in Jordan 2018). This sector was chosen due to its importance to the national economy and the daily life of the citizens. Three out of these banks rejected to accept the copies of the questionnaire, so the sample consisted of the rest ten banks. The sampling unit comprised branch managers, their deputies and heads of departments in Jordanian commercial banks, at all administrative level summed to 219 individuals. They all received the copies of the questionnaire, the restored copies equal to 212 copies, 14 of which were neglected because of their inconvenience for statistical analysis. The copies that were statistically treated summed 198 copies with a restoring percentage of 90.4%. The questionnaire was validated as follows:

The validity of the instrument: The questionnaire was evaluated by presenting it to a group of arbitrators from professors at University of Jordan as well as those with expertise and specialization, and their views were taken into account in formulating the final version of the questionnaire.

The reliability of the instrument: The internal consistency of the questionnaire was verified by calculating Cronbach’s Alpha coefficient where it was found to be more than 70% that is considered acceptable in such kind of studies (Sekaran & Bougie, 2012) (Table 3).

Table 3: The Results Of Internal Consistency Test (Cronbach's Alpha Coefficient)
Axis	Field	Internal Consistency Coefficient
Anti-Money Laundering	Money transfers risks	0.866
	Transaction risks	0.697
	Bulk cash smuggling risks	0.734
Financial Decisions		0.879
Instrument as a whole		0.920

Statistical Methods: Utilizing the Statistical Package for Social Sciences (SPSS) the researcher calculated frequencies, percentages to describe the personal and functional characteristics of the sampling unit, as well as arithmetic average to identify the convenience of the individual of the sample to the items of the questionnaire.

The Descriptive Statistics: the arithmetic average and the standard deviation of the variables of the studies were calculated alone and the result was as follows:

First: Dimensions of the independent variable (Anti-Laundering Money Systems) The Anti-Money Laundering Systems were measured through three dimensions:

Money transfers risks, Transaction risks and Bulk cash smuggling risks by identifying the level of answers of the individuals of the sample for items related to each dimension. This is done by performing a descriptive statistical analysis by calculating arithmetic averages and standard deviations, and this is illustrated by the following:

It is indicated from Table 4 that the arithmetic average of the independent variable Anti- Money Laundering systems as whole equals to 4.08 with a high degree of estimation. The dimension (Bulk cash smuggling risks) came first with a high degree of estimation with an arithmetic average of 4.35 and a standard deviation of 0.47 followed by the dimension of (Transaction risks) with an arithmetic average of 4.07 and a standard deviation of 0.54 while the dimension (Money transfers risks) occupied the last rank with an arithmetic average of 3.84 and a standard deviation of 0.76. This demonstrates the concern of Jordanian Commercial Banks (sample of the study) about the Anti-Money Laundering Systems and the level to limit it in an acceptable and respectable way.

Table 4: Arithmetic Averages Of The Dimensions Of Anti-Laundering Money
	Field	Arithmetic Average	S.D.	Estimation Degree
Anti-Money Laundering systems	Money transfers risks	3.8384	0.76798	High
	Transaction risks	4.0657	0.54254	High
	Bulk cash smuggling risks	4.3460	0.47019	High
Overall Arithmetic Average		4.0833		High

1. Money transfers risks: The arithmetic average and the standard deviation of the dimension of Money Transfer Risks and its items have been calculated to ensure that there is correlation as shown in Table 5.

Table 5: Arithmetic Average And Standard Deviations Of The Dimension Of Money Transfers Risks
No	Item	Mean	S.D.	Rank	Estimation
1	There are clear instructions at the bank to set ceilings for the amounts transferred then audited by the internal audit	3.78	1.048	4	High
2	A period of time is set to monitor funds transfers periodically.	3.85	0.892	3	High
3	There are databases that show details of money transfers	3.88	0.915	2	High
4	Sequential transfers to one or more accounts abroad are monitored	3.92	0.923	1	High
5	The bank has contingency plans to deal with emergency events	3.76	0.973	5	High
	Overall Average of (risk of money transfers)	3.8384			High

Table 5 indicates that item 4 stating “Sequential transfers to one or more accounts abroad are monitored,” has the highest arithmetic average of 3.92 with a standard deviation of 0.92 and high degree of estimation that is greater than the overall average of 3.84. while item 5 stating “The bank has contingency plans to deal with emergency events,” has a high degree of estimation and occupied the last rank with an arithmetic average of 3.76 that is less than the overall average of 3.84 and a standard deviation of 0.97. This indicates that banks are characterized by creativity that is based on monitoring sequential transfers to one or more abroad accounts.

2. Transaction risks: The arithmetic average and the standard deviation of the dimension of Transaction Risks and its items have been calculated to ensure that there is correlation as shown in Table 6.

Table 6: Arithmetic Average And Standard Deviations Of The Dimension Of Transaction Risks
No	Item	Mean	S.D.	Rank	Estimation
6	Warranty letters are monitored and relevant documents are verified	3.78	1.048	4	High
7	Unknown-source assets are granted any loan	3.85	0.892	3	High
8	Any unusual banking transaction is completely dealt with in a confidential way	3.88	0.915	2	High
9	The sources of deposits made in bank accounts are checked	3.92	0.923	1	High
10	The concerned departments classify the suspicious accounts according to their severity	3.76	0.973	5	High
	Overall Average of (Transaction risks)	3.8384

Table 6 indicates that item 9 stating “The sources of deposits made in bank accounts are checked,” has the highest arithmetic average of 4.48 with a standard deviation of 0.52 and high degree of estimation that is greater than the overall average of 4.07. while item 8 stating “Any unusual banking transaction is completely dealt with in a confidential way,” has a high degree of estimation and occupied the last rank with an arithmetic average of 3.80 that is less than the overall average of 4.07 and a standard deviation of 0.94. This indicates that banks are concerned about the new and creative ideas and the activities that contribute to monitor the warranty letters and ensure the source of deposits made in the bank.

3. Bulk cash smuggling risks: The arithmetic average and the standard deviation of the dimension of Bulk Cash Smuggling Risks and its items have been calculated to ensure that there is correlation as shown in Table 7.

Table 7: Arithmetic Average And Standard Deviations Of The Dimension Of Bulk Cash Smuggling Risks
No	Item	Mean	S.D.	Rank	Estimation
11	Detailed information is collected and used for customer-specific activities.	4.34	0.699	4	High
12	Before launching any new service, the bank makes sure of the operating risks of the service.	4.36	0.682	1	High
13	Modern information systems are used to ensure information is recorded and accurate reports are produced.	4.34	0.573	3	High
14	Through the concerned departments, banking operations are monitored and arranged according to importance.	4.34	0.555	2	High
	Overall Average of (Bulk cash smuggling risks)	4.3460			High

Table 7 indicates that item 12 stating “Before launching any new service, the bank makes sure of the operating risks of the service,” has the highest arithmetic average of 4.36 with a standard deviation of 0.68 and high degree of estimation that is greater than the overall average of 4.35. while item 11 stating “Detailed information is collected and used for customer-specific activities,” has a high degree of estimation and occupied the last rank with an arithmetic average of 4.34 that is less than the overall average of 4.35 and a standard deviation of 0.70. This indicates that banks are concerned about the new and creative ideas and the activities that contribute to monitor the warranty letters and ensure the source of deposits made in the bank. The staff follows modern standards and methods to ensure that information is recorded and accurate reports are produced.

Second: Dependent Variable (Financial Decisions)

Table 8 indicates that item 15 stating “The Accounting Department prepares detailed data on the elements of the financial statements periodically,” has the highest arithmetic average of 4.07 with a standard deviation of 0.72 and high degree of estimation that is greater than the overall average of 3.81. while item 18 stating “The accounting department prepares reports to show the accounting events that occurred after the financial statements were prepared,” has a high degree of estimation and occupied the last rank with an arithmetic average of 4.34 that is less than the overall average of 3.71 and a standard deviation of 1.05. This indicates the employees of the accounting departments have a great ability to complete all reports that help in making administrative decisions regarding the budget and available resources.

Table 8: Arithmetic Average And Standard Deviations Of The Variable Making Financial Decisions
No	Item	Mean	S.D.	Rank	Estimation
15	The Accounting Department prepares detailed data on the elements of the financial statements periodically.	4.07	0.720	1	High
16	The Accounting Department prepares reports that clarify the accounting policies used in preparing financial statements and the changes therein.	3.76	0.838	5	High
17	The Accounting Department prepares reports explaining ways of depreciation of fixed assets and stock valuation.	3.80	0.987	2	High
18	The accounting department prepares reports to show the accounting events that occurred after the financial statements were prepared.	3.71	1.045	6	High
19	The Accounting Department prepares reports to show the shareholders’ equity and the changes that occurred in it during a specific period of time.	3.79	0.941	3	High
20	The Accounting Department prepares reports in which it clarifies the non- profit areas in which the company has established or contributed.	3.77	0.970	4	High
	Overall Average of (Making Financial Decisions)	3.8148			High

Hypothesis Testing

H0: Anti-Money Laundering Regulations by their dimensions (money transfers risks, transaction risks and bulk cash smuggling risks) has no statistically significant effect on making financial decisions at Jordanian commercial banks.

Multiple Regression was used to test the impact of Anti-Money Laundering Systems on Making Financial Decisions.

Table 9 illustrates the results of the summary of the model to test the main hypothesis. It is indicated that the value of the correlation coefficient between the independent variable (Anti- Money Laundering Systems) and the dependent variable (Making Financial Decisions) equals 0.864 referring to the existence of a high positive correlation between the variables. The value of the determination coefficient R² equals to 0.747, which means that the model interpreted 74.7% of the total variance while the others is interpreted by other factors.

Table 9: Model Summary
Model	R	R2	Adjusted R	Standard Error
1	0.864a	0.747	0.743	0.36974

Table 10 illustrates the results of regression variance analysis of the impact of Anti- Money Laundering on Making financial decisions, the calculated F equals (190.507) at Sig. of (0.00). The decision rule states that the model is convenient if and only if the sig. value of F is less than or equal (0.05). Consequently, the model is considered convenient for analyzing the impact of Anti-Money Laundering on Making Financial Decisions.

Table 10: Results Of Multiple Regression Of The Impact Of Anti-Money Laundering Systems On Making Financial Decisions Anovab
Model	Source	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	78.133	3	26.044	190.507	0.000b
	Residual	26.522	194	.137
	Sum	104.654	197

It appears from Table 11 that the results of the coefficient of the impact of Anti- Money Laundering Systems by its sub-variables on the dependent variable (Making financial Decisions). The Table shows the calculated t value for (Money transfers risks, Transaction risks and Bulk cash smuggling risks) were (15.968, 3.829 and -1.103) respectively at a significance value of (.000, .000, and .271) respectively. According to the decision rule related to t, which states that the null hypothesis is rejected if the significance value of t is less than (0.05). The null hypothesis of dimensions (money transfer risk, transaction risk) will be rejected meaning that they have a statistically significant effect on financial decision- making. But the dimension of Bulk cash smuggling risks had a virtual but insignificant effect on financial decision-making.

Table 11: Coefficients Results Of The Impact Of Anti-Money Laundering Systems On Financial Decision-Making
Independent Variables	Unstandardized Coefficients		Standardized Coefficients	t	Sig
	B	Std. Error	Beta
(Constant)	0.342	0.260		1.318	0.189
Money transfers risks	0.703	0.044	0.741	15.968	0.000
Transaction risks	0.267	0.070	0.199	3.829	0.000
Bulk cash smuggling risks	-0.072	0.065	-0.047	-1.103	0.271

Discussion

1. The results of the statistical test has shown that the arithmetic average of the independent variable as a whole equals 4.08 with a high degree of estimation while the dimension (Bulk cash smuggling risks) came first with a high degree of estimation with an arithmetic average of 4.35 and a standard deviation of 0.47 followed by the dimension of (Transaction risks) with an arithmetic average of 4.07 and a standard deviation of 0.54 while the dimension (Money transfers risks) occupied the last rank with an arithmetic average of 3.84 and a standard deviation of 0.76. This demonstrates the concern of Jordanian Commercial Banks (sample of the study) about the Anti-Money Laundering Systems and the level to limit it in an acceptable and respectable way.

2. The results of the statistical test have shown that the arithmetic average of the dependent variable (Financial Decision-Making) as a whole equal 3.81 with a high degree of estimation. This indicates that the employees of the accounting departments have a great ability to complete all reports that help in making administrative decisions regarding the budget and available resources.

3. The results of the study reveal that there is a statistically significant impact of Anti-Money Laundering Systems on Financial Decision-Making IN Jordanian commercial banks.

4. The results of the study reveal that the dimensions (money transfer risk, transaction risk) have a statistically significant effect on financial decision-making. But the dimension of Bulk cash smuggling risks, had a virtual but insignificant effect on financial decision-making.

It is agreed with the study of Ashmila & Sonan (2018) that the Libyan law has laid down the policy and rules related to bank responsibility dealing with money laundering. In addition to that Libyan banks face the phenomenon of money laundering through a set of procedures and rules laid down by the Libyan Central Bank.

Recommendations

1. It is recommended that Jordanian Commercial banks should especially preserve the current level of methods and standard that limit the phenomenon of Anti-Money Laundering that is considered an organized crime. Since of Anti-Money Laundering depends on the multiplicity of criminals and material and moral criminal units so that each criminal takes care to execute one or more element of the crime.

2. It is recommended that Jordanian Commercial banks should search previous studies and periodicals especially about similar banks because this will help banks to achieve its goals through adapting a methodological and systematic way to correct and to improve the effectiveness of the operations of risk management, control and governance.

3. It is recommended that all organization and especially Jordanian Commercial banks should develop the methods of limiting the risks of Anti- Money Laundering that is done by adding the legal and Sharia characteristics to money gotten in an illegal way to hide its original nature or its real source.

References

1. Abbas, A. (2008). Financial management. 1st Ed. Ithraa for Publishing and Distribution, Amman: Jordan.
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