Money Laundering Intentions of the Bankers: Some Insights from Past Literature

2022, Abstract The serial theories used to answer the research issue, such as collaborative theories, ethical dilemmas, and intellectual opportunism, are presented in this paper. Furthermore, this study deals with numerous concepts that serve as the foundation of this research, namely the Money Laundering Typology, Money Laundering Intention, desire of money, and corporate culture. Money laundering has become a worldwide problem that has extended to many countries. Although this illicit procedure is not new, it has posed a threat to many governments and communities because many organised crime groups support it. Although money laundering is a global phenomenon carried out through an international collaborative process that has certain negative consequences for many parties, it nonetheless finds a way and the ingredients to expand and develop consistently. The methods and techniques used in ML practise vary greatly. For example, the perpetrator's ML in the banking sector and non-banking by utilising professional facilitators, the establishment of fake companies, investment in real estate fields, insurance product purchases and securities companies, as well as the misuse of corporate vehicles are all used.


Introduction
Money Laundering (ML) is a fraud in the banking sector that can harm the country. This study posits Schott (2006); Ravenda et al (2019), arguing that ML is the process of transforming the results of illegal activities into legitimate capital. With the ML, illicit functions are co-mingled with legitimate ones that could cause a misallocation of resources and income distribution (Albrecht et al., 2006;Alldridge, 2003;Ravenda et al., 2019). ML could also cause social ills, increased crime and corruption. This condition causes criminal organizations to become illegal activities (Secretariat, 2006). Countries that are a heaven for ML actors will find it challenging to accept foreign governmental assistance and attract foreign investment (Ravenda et al., 2019;Schott, 2006;Secretariat, 2006). On the other hand, this study notes that ML practice is closely related to banking because it risks fraud in the sector.
Banking can have a conventional concept as well as the Islamic concept. Islamic financial institutions may be more vulnerable to abuse by money launderers than their conventional counterparts (Jabbar, 2020). Some Islamic bank products or transactions involve the process of buying and selling assets, collaborating with the ML to be easier for these transactions (Jabbar, 2020). The background in this research begins with the development of banking in Indonesia, including Islamic Sharia banking, fraud risk, money laundering in the banking sector, ML collaboration and bankers' behavioural aspects.
ML research conducted in the Indonesian banking area, which has conventional and Islamic banking, is fascinating. Jabbar (2020) argued that there is no evidence to support the contention that Islamic financial institutions facilitate ML actors. This research focuses on the bankers' behavioural aspects of conventional and Islamic banking work. Several conditions influence individual behaviour, both from the internal self and the environment. The significance of this research is in testing the ML intention model that uses determinants of diamond fraud, complementing with the moderating factors of internal factors: love of money, and external factors: work environment and organizational culture.
This research has a theoretical contribution to explaining banker collaborators' conduct actors' ML intentions through a serial combination of collaboration theory, ethical dilemma, and intellectual opportunism. In other words, this study emphasized that bankers conduct ML intentions as collaborators that supports the actual actors' ML to include their unclear money in the banking systems easily. Meanwhile, the Indonesian bankers help actors' ML considering the ethical dilemma between focusing on frauds and maintaining or improving bank performances. Moreover, the author argues that their intellectual opportunism supported the bankers' considerations, gaining individual achievement in sufficing budgeted standards. Thus, this study demonstrates that these three serial theories construct the bankers' behaviours to collaborate with the real actors' ML.
This research is also significant for policy making by government and banking regulators, especially in Indonesia. This research argues that bankers' behaviours that their collaborative activities in ML intentions should be are anticipated by compiling policies for preventing and enforcing the law of ML. In other words, it presents the empowerment of ML law as part of strengthening banking governance. Nevertheless, regulators will face difficulties due to collaborative behaviours and moral hazards in ignoring ethical codes primarily supported by intellectual opportunism.

Issues on Bankers Bankers in Ethical Dilemma
As a start, ethical codes are adopted by organizations to support their employees in understanding the difference between right and wrong applying to their job-desk and specifically to their decisions (Bagus & Howden, 2013;Dogarawa, 2006). Financial institutions continuously adopt and improve significant banker ethics behaviours to be more responsible socially. This ethics behaviour covers attitudes to embattle fraud and deception and increases transparency and accountability. In academic literature, bank firms comprehensively give ethics information to their customers in their perspective and services (Cowton, 2010;Thompson & Cowton, 2004). Garcia-Sanchez et al (2017) state that ethical codes intend to become a mechanism system controlling and avoiding various frauds in bank firms. However, the author believes that ethical dilemmas occur intensively in bank-firm environments. Multiple literatures strengthen this statement (Bagus & Howden, 2013;Dogarawa, 2006;Simwayi & Wang, 2011) that unethical behaviour and fraud are common continuous problems in financial industries losing customers and damaging to the firm itself.
On the other hand, various policies in bank firms are in neutral areas that can create massive ethical dilemmas within bankers and in-line advantages to bankers and bank firms clashing with their adopted moral codes (Bowles & White, 1989). Furthermore, bank firms face excessive problems continuously, such as liquidity problems, low cost of funds, the pressure of improving firm performance and welfare employees that can lead them broadly into the unethical culture of bank firms (Chong & Lopez-De-Silanes, 2007). For example, there is a condition that customers have excessive funds to deposit, but they do not want to describe the resource of its funds honestly. This condition has a strategic bargaining position to bankers and bank-firm itself that can drive themselves into an ethical dilemma contrary to their ethical codes.

Bankers' Intellectual Opportunism
Globally, intellectual opportunism is described as brilliant and competent human abilities, and capabilities used to analyse, seize, and actualise them into existent opportunities economically (Liu et al., 2021;Luo, 2006). Wagner (2019) classifies options of principle opportunism into two critical elements that someone can be capable of actualising every opportunity: 1) power (direct & indirect); 2) authority (subject level). Individuals can achieve economic self-interest when they have these two elements maximally and continuously. For example, knowledgeable bankers could easily recognize every opportunity, analyse, and seize between captured opportunity and their capabilities for creating their potential self-interest by using their authority (to shift opinions, to set antinomic goals, to overrule the decision, etc.) and power (manipulate, ignore, lie, etc.) actualising fraud (accounting discounting fraud, ML, fraudulent loans, etc.) and harming their partner and organization widely.
However, intellectual opportunism is viewed as a neutral status positively and negatively based on an individual's moral hazard. In economic theory, moral hazard refers to post-contractual opportunism that results from asymmetric information (Igawa & Kanatas, 1990). Moreover, moral hazard is a change in someone's behaviour due to shifting incentives that cause allocated risk to other partners. Thus, bank firms are prone to moral hazard behaviour (Braverman & Guasch, 1986). They also argue that bankers' behaviour and attitude are the cut-offs of actualizing captured opportunism ethically or unethically.

ML Prevention and Eradication Policy
According to Bintoro et al. (2021), ML can be understood as the transfer or disguise of money from an unauthorized or illegitimate source (dirty money) through legal channels whose source of funds is unknown. So, there is an activity which is a process carried out by a person or organization to hide the origin of money or assets resulting from crime from the government or authorized officials such as law enforcement into the financial system. Thus, if the money goes out of finance, the system becomes legal money. In 1999, the Egmont Group, an association of worldwide Financial Intelligence Units (FIUs), held the Egmont Training Working Group (ETWG). As a result, cases of ML were collected from all FIU members of the Egmont Group, in which a hundred of them told success stories. It is hoped that the preparation of ML cases from members of the Egmont Group will be useful and become a lesson for every FIU. This typology is currently a reference for members of the Edmont Group, which now has 159 (one hundred fifty-nine) Financial Intelligence Units as of February 2019, and the Indonesian Financial Transaction Reports and Analysis Center (PPATK) is part of it based on Law Number 8 of 2010 concerning the Prevention and Eradication of the Crime of ML.
ML has become a global issue that spreads in many countries. Although this illegal process is not a new phenomenon, it has threatened numerous countries and communities because many organized crime groups support such an act (McDonell, 1998). This phenomenon has political and security consequences: it leads to political unrest and instability of societies. In more detail, John Moscow, the former Assistant District Attorney in the County of New York, describes ML as a "process for the concealment of evidence in which a person seeks to evade responsibility for the ownership, origin or use of funds" (Chaikin, 2017). At the heart of ML is the evasion of individual and corporate responsibility to accumulate financial wealth and transactional behaviour. Secret or unaccountable money is an essential source of financial and political power that can easily be abused. Abuse of financial capacity is not limited to developing countries or authoritarian states. Some commentators argue that secret offshore money is a threat to the political system of democratic nations because it facilitates "rising wealth inequality", which will lead to "patrimonial capitalism", were family dynasties control wealth. The implication is that secret financial power is an inherently corrupt in political systems, whether democratic or authoritarian.
Corruption Pope (2007) says that corruption implies the behaviour of all officials, both politicians and civil servants, who enrich themselves improperly and violate the law, or those closest to them by abusing power entrusted to them. Furthermore, Klitgaard (1988) said that there is a formula that can explain the occurrence of corruption: "Corruption = Monopoly of Power + Official Discretion -Accountability (C = M + D-A)". This formulation is proposed in connection with a strategy to prevent corruption that originates from the root of the emergence of opportunities for corruption. Corruption occurs because of a monopoly of power supported by officials' discretion, but there is no accountability.

Good Governance and Bankers' Attitudes & Behaviours
According to Santosa (2008), the government is good (excellent and sound) if public resources and problems are managed effectively and efficiently and respond to community needs. While Van Wart (2014) defined good governance as the existence and functioning of several public institutional devices so that the community's interests can be well guaranteed. The implementation of policies to prevent and eradicate ML at the Corruption Eradication Commission is closely related to the principle of the rule of law in good governance where the implementation of Law Number 8 of 2010 is used to eradicate corruption, mainly associated with the handling of ML cases in the capital market originating from corruption. However, this study borrows the proverb "rules are rules" as a baseline in explaining that policies are commonly obeyed if an individual has bad attitudes and low integrity. Furthermore, based on the fraud diamond theory, bankers assist ML actors in achieving both for their benefit and their bank-firms mutually (Alexander, 2004). Consequently, this collaboration can become a continual behaviour due to bankers secretly supporting ML action with bank-firms permission.

Typology of Money Laundering (ML)
ML is used for unlawful and illegal purposes as it conceals the origins of illicit proceeds, allows organized crime to persist by creating a mask of legitimacy around illicit funds and reduces the probability of these funds from being identified or traced (Lilley, 2003;Utami, 2021;Young, 2013). Moreover, posing an enormous threat and obstacle to the global economy, ML allows criminals to finance their illegal businesses and supports their extravagant, luxurious lifestyles without regard for society (Young, 2013).
It is important to note that ML is mainly driven by criminal activities collaboratively and hiddenly for these illegal activities to remain successful (Lilley, 2003). Criminals use ML to convert dirty money into a form that can be used more conveniently in commerce while hiding the dirty money's true origins (Barbot, 1995). Ping (2004) stated that the Financial Action Task Force (FATF) estimates that as much as $85 billion per year in drug proceeds could be available for laundering in the USA and Europe. An offshore financial centre (OFC) is often used to carry out ML as they have strong banking secrecy laws that allow the origins of the illegally sourced funds to remain hidden (Young, 2013).
ML is the process of concealing the existence, illegal source or illegal application of income and the subsequent disguising of the origin of that income to make it appear legitimate. The development of science and technology has provided many benefits in the economic field, especially in supporting business activities and improving financial services to the community (Teichmann & Sergi, 2018). However, the development of science and technology also increases the risk of deviation (Dujovski & Mojsoska, 2019). The International Narcotics Control Strategic Report explains that the more advanced a country's economy and financial system is, the more attractive it is for criminals to commit crimes. The most common crime committed through the financial system services in a country is ML.
ML is a problem that cannot be avoided by every country in the world (Dujovski & Mojsoska, 2019). ML is the process of taking the results generated by criminal activity and giving these results legality (Teichmann & Sergi, 2018). The modern money launderer would certainly follow more advanced techniques than the gem carriers of India or the Knights Templar, but his aims and primary modus operandi will be the same. The goal will be to obscure the source and thus the essence of the wealth in question, and the modus operandi will unquestionably require the use of actual or imagined transactions intended to confuse the audience and confuse the inquirer. ML is essentially a mechanism in which the proceeds of crime or fraud appear as if they came from a legitimate source. Today, ML usually includes a complicated system of transactions, frequently through a variety of jurisdictions, such that the proceeds of violent crime in, say, Italy resurface as the seemingly usual profits of a pizza restaurant in New York. The goal is to confuse any investigator who attempts to track down 'soft' money either by 'losing' it or by creating a complex network of transactions that is practically impossible to follow.

Fund Placement in Banks
Placement is the first stage in ML, i.e. when the proceeds of a criminal act enter the financial system or change shape. With the development of financial system technology, after obtaining the proceeds of crime, the perpetrator has many options to place his property. Placement is an effort to put funds generated from criminal activity into the financial system. In this phase, illegal funds are entered into the financial system. The most evident and highrisk crime outcomes are detected at this placement stage. Converting illicit funds into cash deposits in bank accounts and using cash to buy high-value assets such as land, property and luxury goods are examples of placement (Chelliah & Prasad, 2017).
The placement stage involves placing or presenting the illicit money before banks or financial institutions or smuggled out of the country. The launderers aim to remove the cash from the location of acquisition to avoid detection from the authorities and then transform it into other asset forms, e.g., Travelers' cheques, Postal order etc. This stage is also referred to as immersion which may also be achieved by a wide variety of means depending on the opportunities available or presented to the ingenuity of the criminal, his cohorts and their network.
At the placement stage, washers tend to put their results into the retail economy's financial system or smuggle it abroad. This is done by breaking up large amounts of cash into smaller portions. The petty cash is then deposited in a bank account or used to buy other monetary instruments. Finally, they aim to issue some money from their origin to avoid detection by the authorities (Moamil, 2014). ML methods and routes evolve because of several factors. Technology is one of them, but other things also influence the flow of dirty money.
The international ML circuit's placement or introduction of illegitimate money is an indispensable but susceptible manoeuvre. This is the first stage in the washing cycle. ML is a "cash-intensive" business, generating vast amounts of cash from illegal activities (for example, street dealing of drugs where payment takes the form of cash in small denominations). Money is generally introduced into the international circuit of ML through financial havens classified as "entry point safe havens". This initial step is the most vulnerable to law enforcement detection because it involves the physical disposal of cash. While cash is an anonymous and attractive quality for criminal proceeds, it is bulky and challenging to transport physically. For example, pounds of cocaine worth $1 million equates to 256 pounds of street cash worth the same amount; the cash weighs more than six times the drugs. This is the movement of cash from its source.
The placement process can be carried out through many techniques, including a) Currency Smuggling. This is the illegal physical movement of currency and monetary instruments out of a country. The various methods of transport do not leave a discernible audit trail FATF 1996-1997 Report on ML Typologies; b) Bank Complicity (FATF, 2010). This is when a financial institution, such as a bank, is owned or controlled by unscrupulous individuals suspected of conniving with drug dealers and other organised crime groups. This makes the process easy for launderers. The complete liberalisation of the financial sector without adequate checks also provides leeway for laundering; c) Currency Exchanges. In several transitional economies, the liberalisation of foreign exchange markets provides room for currency movements, and as such, laundering schemes can benefit from such policies; d) Securities Brokers -Brokers can facilitate the process of ML through structuring large deposits of cash in a way that disguises the source of the funds; e) Blending of Funds -The best place to hide some money is with a lot of other cash. Therefore, financial institutions may be vehicles for laundering. The alternative is to use the money from illicit activities to set up front companies. This enables the funds from illegal activities to be obscured in legal transactions; f) Asset Purchase -Purchasing assets with cash is a classic ML method. The primary purpose is to change the form of the proceeds from conspicuous bulk cash to some equally valuable but less conspicuous form.
The main idea of the placement stage is to convert cash as quickly as possible into other types of assets to avoid detection (Elsbach & Stigliani, 2018). At this stage, money obtained illegally is manipulated into various forms not to be suspicious (Cassella, 2018). For example, placement can be done by depositing illegal cash directly to financial institutions or buying expensive items resold with payment by check and then investing them in financial institutions. Another method is through operating a restaurant, hotel, or casino. Actors can also use insurance agents, travel agents, the security sector, real estate agents, or the banking system to hide sources of illegal funds.

Separation or Layering
Separation or layering is the second stage of ML. At this stage, the proceeds of crime are removed, distributed and disguised to conceal their origin. This separation can be done through a series of financial transactions designed with complex transaction networks to be traced. This stage is related to money abroad through a series of complicated financial transactions (Ba & Huynh, 2018). Such trades are designed to disguise the audit trail and provide anonymity to obscure the origin of illegal funds. To achieve this goal, the offenders use offshore banks, shell companies, or tax-exempt countries so that crimes committed cannot be traced (Cassella, 2018). This intermediary is relatively safe from the detection of law enforcement agencies because the anti ML law is still relatively weak (Niepmann & Schmidt-Eisenlohr, 2017).
The purpose of this stage is to make it more difficult to detect and uncover a laundering activity. In addition, it is meant to make the trailing of illegal proceeds difficult for law enforcement agencies. The known methods are a) Cash converted into Monetary Instruments -Once the placement is successful within the financial system through a bank or financial institution, the proceeds can be converted into monetary instruments. This involves the use of banker's drafts and money orders; b) Material assets bought with cash then sold -Assets purchased through illicit funds can be resold locally or abroad, and in such a case, the assets become more challenging to trace thus seize.
Layering is the second phase that involves financial transactions to decide the trail of ML (Chelliah & Prasad, 2017). An example of the layering phase is the use of a series of complex transactions involving many banks, accounts or companies that aim to move, spread or disguise illegal funds to conceal the true origin of funds (Naheem, 2017). Layering can also structure ML techniques by dividing large amounts of money into smaller deposits (Chelliah & Prasad, 2017). The Layering Stage involves the creation of a complex web of transactions aimed at dissociating the illegal funds from their criminal origin. Such transactions prevent any audit trail from being left and conceal the source and ownership of funds. It is often referred to as dilution or heavy soaping since it involves transferring money or funds to offshore countries, and once deposited in a foreign bank, and the fund can be moved through accounts of "Shell" Corporations that exist solely for laundering purposes.
Some layering modes include a) The transferring of funds electronically. Once placed in the banking system, the offender can easily transfer the asset to wherever it wishes. If the transfer is done electronically, he can move his assets immediately, across borders, over and over, through accounts he has controlled, his associates, or even accounts with false identities until his origins are hard to trace; b) Transfer through offshore banking activities. Offshore banking is a pervasive activity concerning the number of Offshore Financial Centre (OFCs) and the volume of transactions. Several factors ranging from favourable regulatory frameworks and convenient fiscal regimes to the possibility of engaging in illegal activities, including ML, continue to attract business to OFCs. Offshore banking appears to be a particularly appealing option to the sometimes heavily regulated and maturing financial markets of emerging economies, especially those experiencing sustained high growth rates and needing investment financing.
Currently, OFCs are an essential and growing intermediation channel for emerging economies, as suggested by a large and increasing share of OFC assets and liabilities concerning these countries. In addition, offshore banking provides opening account services for residents abroad. By placing funds in a bank, which is subsequently transferred to an Offshore Banking account, the offender may as well distribute the proceeds of their crime. Moreover, offshore Banking tends to have an extensive network of banks, making it easier for criminals to commit ML. Offshore banking has important implications for financial systems surveillance. A greater leeway for balance sheet management, granted by favourable regulatory frameworks in OFCs, makes offshore banks potentially more vulnerable than onshore banks to solvency and foreign exchange risks. These can be transmitted between offshore and onshore banks with implications for the soundness of onshore banking systems. Hence, a better understanding of offshore banking is essential for the fund's financial sector surveillance activities.

Integration
Integration is the effort to combine or use legally-seen assets, whether to be enjoyed directly, invested in various financial products and other material forms, used to finance legitimate business activities or to refinance criminal activities. The integration phase is the final stage which involves the movement of phase 2 (layering) into the formal economy. Integration is usually done through the banking system so that illegal funds will look like income from normal business activities. Actors can invest funds owned in real estate, luxury assets, or legitimate business ventures (Nazri, Zolkaflil & Omar, 2019). It is complicated to distinguish between legal and illegal results at this stage. The integration stage of the process involves the introduction of the funds into the legitimate economic and financial system. This stage is also referred to as "spinning", "repatriation", or "re-integration".
Integration is the use of assets that have appeared legitimate, whether to be enjoyed directly, invested in various forms of material or financial glory, used to finance legitimate business activities or to refinance criminal activities. This is the movement of previously laundered money into the economy mainly through the banking system, and thus such monies appear to be regular business earnings. This is dissimilar to layering, for informants provide detection and identification of laundered funds in the integration process. The known methods used are a) Property Dealing -The sale of the property to integrate laundered money back into the economy is common among criminals.
For instance, many criminal groups use shell companies to buy property; hence proceeds from the sale would be considered legitimate; b) Front Companies and False Loans -Front companies that are incorporated in countries with corporate secrecy laws, in which criminals lend themselves their own laundered proceeds in a legitimate transaction; c) Foreign Bank Complicity -ML using known foreign banks represents a higher order of sophistication and presents a challenging target for law enforcement. However, the generous assistance of foreign banks is frequently protected against law enforcement scrutiny. This is not only through criminals but also by banking laws and regulations of other sovereign countries; d) False Import/Export Invoices -The use of false invoices by import/export companies has proven to be a very effective way of integrating illicit proceeds back into the economy. This involves the overvaluation of entry documents to justify the funds later deposited in domestic banks and the value of funds received from exports.
At this stage, actors combine ML with legal funds, making it more challenging to separate the two (Cassella, 2018). Other techniques in the integration phase include buying letters of credit, bonds, securities, banknotes, bills of lading, and guarantees. Through this step, illegal funds are returned to legitimate economic flows. After reaching this stage, actors can use funds in various ways (Balani, 2019).

Money Laundering Techniques & Its Impact to Various Parties Money Laundering (ML) Techniques
The more popular ML techniques include one or more of different ways: a) Bulk cash smuggling, is defined by bringing into a country (a prohibited item) secretively and intentionally, in violation of the law used to move the money into another country for deposit into offshore banks or other types of financial institutions that honour client secrecy; b) Trade-based laundering, is used for obtaining invoices to show a higher or lower amount of documented transaction value to disguise the movement of money; c) Cash-intensive business, is used because this type of business occurs and legitimately deals with large amounts of cash, and the launderers use its account to deposit money obtained from both everyday business proceeds and money obtained through illegal means; d) Shell companies and trusts, are used to disguise the valid owner of a large amount of money. Launderers try to control and use them; e) Bank owning refers to the use of a bank owned by money launderers; f) Real estate purchasing with money obtained illegally, then sells it; g) Casino or gambling laundering involves an individual going into a casino with obtained unlawfully money, gamble for a while and claims the money as gambling winnings ML risk poses severe threats to financial institutions and individual nations. The risks faced by financial institutions are reputational risk, operational risk, concentration risk and legal risk. Reputation risk is the integrity of the banking and financial services marketplace depends heavily on the perception that it functions within a framework of high legal, professional and ethical standards. Operational risk is the risk of direct or indirect loss resulting from inadequate or failed internal processes, people and systems, or external events.
In general, there are three new ML methods by using technology: a) Using Electronic Money (electronic money), b). Internet Bank (I-Bank), c. Internet Casino (Internet Gambling). According to the Bank for International Settlement, Electronic Money (E-Money) is a "stored value" or "Prepaid" product in which the record of funds or consumer value is stored in a consumer electronics store. E-money has several advantages compared to traditional money, namely: e-Money uses a card or a tool that can save funds in enormous quantities, so it does not need a place or large container to carry it. E-Money is easy to transfer anytime and anywhere with the help of the internet. E-Money is more challenging to track because it doesn't have serial numbers like traditional money. Besides technology, the encoding contained in the E-Money transfer process increasingly makes it difficult to know its origin. With all three advantages, it makes ordinary offenders smuggle their money easily. They can do ML anywhere and whenever because E-Money doesn't need an intermediary to move.
Internet Bank (I-Bank) is a virtual bank that offers a variety of facilities like an anywhere and anytime standard bank via the Internet. Some facilities offered include direct payment, e-money transfer, expenditure checks, letter purchases valuable, and opening and closing accounts. There are several advantages of the Bank as a tool to do ML, namely: 1) Very easy to access anytime and anywhere. 2) No need for direct contact between consumers with I-Bank. 3) I-Bank provides facilities for international finance, and every transaction is done comfortably and safely.
Internet Casino (Internet Gambling) is ML that involves banks and can be defined as any act or attempt that aims to use any banking transaction to hide any money earned from illegal means by bankers, customers, or other people. Banks can be considered the main and the first factor to encourage currency circulation in a country under different laws (Al-Kadi et al., 2012). Therefore, the use of banking institutions is one of the common ways to carry out the act of ML (Marlin-Bennett, 2016). Many factors make it difficult for the crime to be separated from the banking business in the state. Among the factors is the growth of transactions between local and international banks; banks' commitment to the secrecy principle on accounts in an absolute manner; technical progress in financial systems among the various countries of the world; and the involvement of some foreign banks in ML operations.
Although the practice of ML is a global phenomenon done through an international collaborative process, laundering money still finds a way and the ingredients for growing and developing continuously. The methods and techniques used in the ML practice vary greatly, is among others, applied by the perpetrator's ML in the banking sector and non-banking by utilizing professional facilitator, the establishment of fake companies, investment in the real estate fields, insurance product purchases and securities companies, as well misuse of corporate vehicles.
The emergence of ML practices can impact technological advances in the financial transfer system (Teichmann & Sergi, 2018). This is due to the electronic financial transfers that can take place easily and in just a few seconds, such as using an Automatic Teller Machine (ATM) and Electronic Wire Transfer. Technological advances in financial transfer facilitate the flourishing of ML practices because they do not have a geographic horizon, operate for 24 hours, and have the speed of electronic transactions (Niepmann & Schmidt-Eisenlohr, 2017). The advancement of information technology has made national borders meaningless. This makes organized crimes easy to do.

The Impact of Money Laundering (ML)
ML has a wide range of adverse effects on any country's economic, political and social structures. Since laundered money passes through the financial system, ML also has several products on the financial systems as a whole and banks in particular. Some of the effects include: undermining legitimate private-sector efforts. Money launderers use front companies to disguise the proceeds of illicit activities and, in the process, hide the ill-gotten gains. These companies have access to substantial illicit funds, therefore allowing them to subsidize the front company and offer its products and services at levels below market rates. At times they quote prices that are below the production cost. This explains why front companies have a competitive advantage over companies that source their funding from the financial markets. This makes it difficult, if not impossible, for legitimate businesses to compete against such companies. This situation may lead to criminal entities crowding out of legitimate private sector businesses. In addition, such criminal enterprises would not adhere to good corporate governance practices as legitimate businesses would.
Loss of control of economic policy. As already alluded to, the magnitude of ML is between 2% to 5% of world output. In most developing economies, like ours, these proceeds may dwarf government budgets, resulting in loss of control over economic policy by such governments. ML can also affect currencies and interest rates as launderers reinvest their funds where their schemes are less likely to be detected than higher rates of return. ML can also increase the threat of monetary instability due to the misallocation of resources. In this regard, ML may result in inexplicable changes in money demand and increased volatility of international capital flows, interest and exchange rates. The unpredictable nature of ML, coupled with the attendant loss of policy control, may make sound economic policy challenging to achieve.
ML could lead to economic distortion and instability. Since money launderers are not interested in profit generation from their investment but rather in protecting their proceeds, they will invest their funds in activities that are not necessarily economically beneficial to the country where the funds are located. Further, to the extent that ML and financial crime redirect funds from sound investments to low-quality investments that hide their proceeds, economic growth can suffer. For example, in some countries, entire industries, such as construction and hotels, have been financed not because of actual demand but because of the short-term interests of money launderers. When these industries no longer suit the money launderers' scheme of things, they abandon them, causing a collapse of these sectors and immense damage to economies.
ML can disrupt the functioning of market mechanisms (Ba & Huynh, 2018). The illegal acquisition of money causes no protection of property rights, the market becomes inefficient as indicated by increased market transaction costs, and there is asymmetrical access to market information. The crime of ML also avoids tax payment obligations, reducing state revenue (Simser, 2013). Furthermore, the existence of financial transactions is carried out by bringing illegal money abroad and will add to the deficit in the balance of payments abroad and result in a reduction in bank funds which causes difficulties for banks to expand credit. In addition, if the state gets an illegal amount of money from abroad, it will add to the shock of macroeconomic stability.
ML is a crime, justified by the fact that whoever launders money is pursuing a way to legitimize their ill-gotten gains accumulated via illegal activities, and it allows criminals to enjoy the proceeds of their crime (Baldwin, 2003). By looking at the modus operandi of ML, banking institutions are primarily the first-level contact points by money launderers due to several factors, including multiple services provided by banking institutions such as deposits, loans, investments and foreign exchange. In the set-up of a banking institution, assessing ML risk has been primarily focused on organization-based roles, for instance, ML policies and compliance with the supervisory requirements (Raghavan, 2006;Simwayi & Wang, 2011). Limited studies have been found on the individual-based role in assessing ML risk, particularly relating to customer risk assessment. Although banking institutions are exposed to automated solutions in assessing ML risk, the human factor in determining the risk is indispensable.

Concepts of Money Laundering The Love of Money
Love of money is outlined because of how an individual wishes for money. Once the want for cash builds up, people will become keen on cash (Furnham & Argyle, 1998). Tang et al. (2005) summarized the definitions of LOM as "(1) one's desires, values, and aspirations for money, (2) one's attitudes toward money, (3) one's means of money, and (4), not one's desires, but greed (Sloan, 2002), or materialism (Belk, 1985)." Research findings have supported this statement wherever the LOM results in unethical actions within the geographic point (Sardžoska & Tang, 2012;Singhapakdi et al., 2013). Furthermore, previous analysis has frequently found that LOM leads to alternative negative behaviours. As an example, high LOM causes workers to possess lower pay satisfaction (Tang et al., 2005) and job satisfaction (Tang & Chiu, 2003), which then causes withdrawal of knowledge and turnover. Additionally, Tang and Chiu (2003) found LOM as a treater for lower pay satisfaction, that successively causes unethical behavior. By following their cash motives, workers will simply fail to acknowledge intrinsic job satisfaction.
Moreover, as LOM concerns greed (Sloan, 2002), it may also lower psychological wellbeing. The LOM scale is adopted from Tang and Chiu (2003) in this analysis. It consists of 4 dimensions. The first dimension is "success", which could be a psychological feature element to which people read cash as a symptom of success. This is when people keep grading up the money they have because it defines them, however well they're doing in their lives. The second dimension is "rich" as an Associate in Nursing affectional element. People who love money wish to be wealthy and feel strongly positive about being rich. They believe that by being wealthy, their lives are higher. The dimension is "motivator", an activity element, wherever LOM motivates folks to work exhaustingly for it. The dimension is vital as another affectional element. This can be identified as people viewing money as their "primary factor" in life.

Organizational Culture
Organizational culture is the shared principle of beliefs associated with nursing assumptions that influence how people or teams of individuals behave in an organization (Van den Berg & Wilderom, 2004). It is not the definitions of culture that adjust but its operationalization. Organizational culture encompasses five components bedded on time of perspicacity and accessibility. At one end, material artefacts and behaviour patterns comprise the noticeable physical manifestations and patterns of activity. For example, symbols, language, rituals, and mechanisms of decision-making, coordination, and communication are a part of these two primary layers. Behavioural norms are the shared beliefs relating to acceptable and unacceptable behaviour, whereas values are the priorities assigned to specific states or outcomes. At the opposite end, elementary assumptions are the unconscious components that don't seem to be directly cognizable, even to members (Henry, 2006).
Despite the variability of interpretations and cultural dimensions, various common themes and similarities may be known in structure culture analysis (Parker & Bradley, 2000). First, ideas will not determine and outline structure culture and tend to overlap between studies; consequently, many students have tried to develop frameworks to reason necessary dimensions and produce a conceptual foundation for studying structure culture (House et al., 2004;Schein, 2010). Second, values and ideologies associated with beliefs are considered necessary for understanding an organization's culture and are viewed as a reliable illustration. The assessment and measuring of structure culture have so generally targeted organizational values. The third-associated necessary facet of cultural analysis has been the role of an organization's culture (and its underlying values and beliefs of management) in preventing or fostering the implementation of social control innovations (e.g., re-engineering, total quality management) or technological innovations (e.g., versatile producing technologies, enterprise resource coming up with systems) (Zammuto et al., 2000).
Organizational culture is concerned with how employees perceive the characteristics of an organization's culture, not with what they like or do not like. That is, culture is a descriptive term. Organizational culture is a shared perception shared by all organisation members (Arianty, 2015). Luthans (2006) stated that organizational culture is the norms and values that direct the behaviour of executive members. Each member will follow the prevailing culture to be accepted by the environment. According to Tika (2014), organizational culture is the subject of solving external and internal problems, which are carried out consistently by a group which then bequeathed to new members as the right way to understand, think and feel about related issues. Meanwhile, organizational culture is a set of values, beliefs, assumptions, or norms that have long been valid, agreed upon and followed by members of a group of organizations as a code of conduct and problem-solving of organizational issues. Organizational culture covers broader and more profound aspects and becomes a basis for creating an ideal organizational climate.
Behaviour highly depends on what has been experienced, learned and thus cultivated by a person throughout his lifetime culture determines his behaviour (Reisyan, 2015). Culture affects every single interaction in the workplace. Human interactions are the most important events that define an organization's competitiveness. Most relevant organisational decisions are taken based on the intense interaction between members of a work team. Usually, various consultations occur before the meeting, where the final decision will be accepted. So even if the work team is a single person, there is already a lot of interaction.
Much of the violated philosophy is the dubious attitude toward customers that has been instilled in the organization itself. They build stories about "weird" customers, which coworkers tell one another. This kind of situation can be found anywhere in the service sector, increasing and encouraging work on organizational culture. Let's discuss the boundaries between work and personal life, which have become much more relaxed over the last few years. This trend is even accelerating as companies are increasingly active on social media like Facebook or Twitter. That means people are increasingly busy professionally and personally in this medium.
The management and organizational theory field are some of the most popular concepts. However, several studies that previous researchers have carried out have given different opinions about the definition of organizational culture. One of the most popular definitions of an organization is Schein's opinion (Schein, 2010). Schein defined organizational culture as a pattern of shared basic assumptions learned by a group that solves external problems and internal integration, which has worked well enough to approach and teach new members the correct way to understand, think, and feel a connection (Schein, 2010).
There are positives and negatives to this culture. On the positive side, it can help organizations become strong, dynamic, and quick to respond to external cases. Role culture is based on the ability of people to carry out functions that can provide satisfaction, while task culture is more than a project-oriented organization. In this culture, power and authority are controlled by the right people who can realize the results or goals.

Conclusion
This study presents the serial theories used to answer the research question, such as collaboration theories, ethical dilemmas and intellectual opportunism. Moreover, this study deals with various concepts that form the basis of this research, namely the typology of ML, ML intention, love of money and organizational culture. ML has become a global issue that spreads in many countries. Although this illegal process is not a new phenomenon, it has threatened numerous countries and communities because many organized crime groups support such an act. It is important to note that ML is mainly driven by criminal activities collaboratively and hiddenly for these illegal activities to remain successful (Lilley, 2003). Criminals use ML to convert dirty money into a form that can be used more conveniently in commerce while hiding the dirty money's true origins.
Although the practice of ML is a global phenomenon done through an international collaborative process and provide some negative impacts to various parties, laundering money still finds a way and the ingredients for growing and developing continuously. The methods and techniques used in the ML practice vary greatly, is among others, applied by the perpetrator's ML in the banking sector and non-banking by utilizing professional facilitator, the establishment of fake companies, investment in the real estate fields, insurance product purchases and securities companies, as well misuse of corporate vehicles.