INTRODUCTION
Money laundering is seen as critical to the effective operation of transnational and organized crime. However, money laundering effects a country’s economy, government, and social well-being. The economic effects of money laundering discussed included: (1) undermining the legitimate private sector; (2) undermining the integrity of financial markets; (3) loss of control of economic policy; (4) economic distortion and instability; (5) loss of revenue; (6) risks of privatization efforts; and (7) reputation risk. The social costs of money laundering include allowing drug traffickers, smugglers, and other criminal to expand operations and the transfer of economic power from the market, government, and citizens to criminals.
In extreme cases, money laundering can lead to a complete takeover of legitimate government. Anti-money laundering efforts are both a critical and effective component of anti-crime programs. Money laundering presents a complex and dynamic challenge across the world. The shear global nature of money laundering requires global standards and increased international cooperation in order to reduce the ability of criminals to launder their proceeds and carry out criminal activities.
LITERATURE REVIEW
Money laundering is the conversion of criminal incomes into assets that cannot be traced back to the underlying crime (Peter, 2004) People involved in money laundering want to make more money and also, they use traditional business practices to move funds (Jonathan E. Turner, 2011).
“Effective anti-money laundering and combating the financing of terrorism regimes are essential to protect the integrity of markets and of the global financial framework as they help mitigate the factors that facilitate financial abuse.” – Min Zhu, Deputy Managing Director of the IMF
In the recent years, the significance of money laundering has drastically increased in the financial and political world.
The government and the financial institutions have been fighting the money launderers collectively and have created several policies to help prevent it. The intent to hide the proceeds of the crime is what provokes the act of money laundering. Apart from the intent there is also the need to spread the criminal enterprise. There lies a profit-making crime behind every act of money laundering. Such ventures create financial flows that are causes for the redirection of funds from uses that are beneficial economically and socially, having adverse effects on the financial sector as well as the external stability of a country. They are also responsible for deterioration of a society and the economic system as a whole.
Anti-Money Laundering and/or Combating the Financing of Terrorism controls are used to diminish the unfavorable effects of criminal and economic activity. Although they only yield effective results when they are applied in an adequate manner, promoting the integrity and stability in the financial world. AML is basically a set of policies and laws that enforces to keep a watch on the clients of financial institutions in order to prevent the acts of corruption and money laundering. Financial Institutions are required by these laws to report any financial crimes and also to take any measures necessary, keeping in bounds of the AML legislation, to stop these activities. Even though there is pressure to follow the anti-money laundering regulations put by Financial Action Task Force and other international bodies such as the United Nations Office on Drugs and Crime, still the financial institutions do not necessarily agree with them. There have been many numerous cases recently where the banks have been outspoken over the issue that these policies are extremely costly yet ineffective. Every year, there are millions of dollars spent on just the attempt to regulate these policies and to undermine the money laundering activities in just Europe and America alone. Numerous financial institutions are now starting to believe that the AML systems in place at the moment are ineffective and also the costs that they have to bear is not worth their questionable accomplishments.
METHODLOGY
For evaluating the alternatives successfully against criterion MCDM technique will be used after data collection from expertise based on their preference of most important success factors they value for anti-money laundering. The data will be analyzed through either ANP based TOPSIS or Fuzzy Vikor which will be decided after discussion with project advisor.
PRELIMINARY DATA
The primary constituents for the success and the survival of any criminal organization are recruiting, motivation, funding and sanctuary. Like all criminal organizations, terrorists require financial support to establish and maintain effective financial infrastructures that include:
- Sources of funding.
- A means of laundering these funds.
- A way to ensure that these funds can be readily used.
Currently, the strategy followed to mitigate the terrorism activities is to deprive the criminal organizations of these basic constituents. Provided that the expansion of money laundering activities, there is a need for international cooperation by regulatory authorities to effectively uproot this issue. These authorities are required to constantly warn the financial institutions to follow the anti-money laundering regulations that are becoming increasingly strenuous.
Criminal organizations continuously fluctuate between the money laundering activities that are based upon cash and those that are based upon bank and the financial markets. As the range of the products and the services offerings in the financial world increases the complexity also increases and so contemporary ways to launder the money continue to spring up. A blurred audit trail contributes to loopholes that can be exploited by those looking to launder money. Money launderers have also been known to seek help from inside the financial institutions in order to further protect themselves against being exposed. This creates a fourth stage in the money laundering process called “paper trail avoidance”, which circumvents documentation, record keeping, detection, and reporting through non-collection, falsification, alteration or destruction of data and records. (Richard Gibbons, 2005)
There is a need by the financial institutions to invest in IT solutions if they are to meet the minimum regulatory requirements. Moreover, the rise of Blockchain technology in the financial world can prove to completely transform how businesses operate and has the potential to negate all the current money-laundering practices in the world.
STATEMENTS OF LIMITATIONS
The rapid advancement in technology and globalization have created a powerful new headache for banks and governments everywhere. Money laundering is estimated to equal a staggering $2 trillion per year. To put this figure in perspective, that’s roughly the equivalent to the entire GDP of Brazil, the world’s 8th largest economy.
There is a need to for a serious compliance which needs to be structured. Growth of the global anti-money laundering regime has generated relatively little public controversy but the banking sector initially resisted increased government interference in its relationships with clients.
The extent to which money laundering laws are formed and implemented is different in different countries which makes the anti-money laundering structure weak.
So we propose three alternatives to prevent money laundering globally.
- Know Your Customer (KYC) Due Diligence.
- Blockchain
- Anti-Money Laundering regime (Conventional)
Our research would contribute to the efforts made on money laundering prevention by finding out the most effective technique to be used. Modeling the financial systems and finding the best policy against money laundering.
CONCLUSION
Aggregate figures conceal as much as they reveal. The adverse consequences, basically social, of a billion dollars laundered to finance a terrorist act, on the one hand, and a billion-dollar embezzlement, on the other, are so different that adding together the two figures would not produce a useful statistic for policy purposes. What is needed – but not available – is reliable figures for major types of the offenses that generate the total amount.
REFERENCES
- Aldridge, Peter. 2003. Money-Laundering Law: A Liberal Critique. Oxford: Hart.
- Blunden, Brian. 2001. Money Launderers. Chalford, Gloucestershire: Management Books.
- Becker, G.: 1968, Crime and punishment: An economic approach, Journal of Political Economy 76, 169-217.
- Chasing Dirty Money: The Fight Against Money Laundering By Peter Reuter (2004)
- Hassani, H.; Saporta, G.; Silva, E.S. Data Mining and Official Statistics: The past, the present and the future. Big Data 2014.
- International Monetary Fund. 2018. Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT). [ONLINE] Available at: [Accessed 16 October 2018]
- Kharote, M.; Kshirsagar, V.P. Data mining model for money laundering detection in financial domain. Int. J. Comput. Appl. 2014
- Money Laundering Prevention: Deterring, Detecting, and Resolving Financial Fraud By Jonathan E. Turner (2011)
- Richard Gibbons, 2005. IBM. Available at: [Accessed 16 October 2018]. · Wei, W.; Li, J.; Cao, L.; Ou, Y.; Chen, J. Effective detection of sophisticated online banking fraud on extremely imbalanced data. World Wide Web 2013
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