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The 6th Prime Minister, Najib Razak, was found guilty on three counts of money laundering by the Malaysian courts last July, of which he is appealing. Furthermore, former Penang Chief Minister, Lim Guan Eng, is undergoing trial for money laundering. While their fates are tied to the courts for the time being, it’s worth uncovering “money laundering” as an example of financial crime.

Other examples of financial crimes include fraud cases, tax evasion, bribery and more which indirectly leads to criminal issues like robbery, theft, murder, computer crimes and so on. However, money laundering is particularly interesting as it is harder for governments to recognise, track, and trace the evidence of it.

What is money laundering?

Money laundering is a serious crime involving turning a massive amount of illegal ‘dirty’ funds into legal ‘clean’ ones by breaking up chunks of cash into a few smaller deposits and splitting them into different accounts to curb attention.  The origin of laundered money started with drug traffickers or criminals that committed a serious criminal offence. In order to use their money in the economy, they chose to process the illegal profit they made through laundering to avoid suspicions from authorities.

How does money laundering work?
The process of money laundering includes 3 stages: placement, layering and integration.


This is the first stage of money laundering where criminals place unlawful dirty money into financial institutions. For instance, depositing the money into the bank account anonymously will help them to successfully wash and disguise their illegal funds into the legal financial system.  Methods used at this stage are called blending, smurfing and invoice fraud:

Blending is done by placing the cash in businesses such as saloons, car wash stores or restaurants as the cash spent will not have any variable costs.

Smurfing is a structuring technique where criminals break large amounts of cash into multiple smaller transactions to remain under the limit of bookkeeping. 

Invoice Fraud is the creation of a false invoice for goods in which a fake document to prove the transaction of money is provided, but shipment is never carried out.


Upon transferring ”dirty money” into the financial system, it gets separated into multiple transactions to further distance it from its’ illegal origins. 

As the legislation system is not foolproof, there are loopholes launderers will take advantage of to transfer money from one country to another. Apart from loopholes, investments in stock and front from real estate is also a way for them to layer the dirty funds into a big sum of clean and unsuspicious ones.


The final stage of money laundering allows the money to re-enter into the mainstream economy where the money is then returned to the launderers themselves from a legitimate source. With money now “cleaned”, criminals are able to legally use it for whatever purposes they have without fear of getting caught as there is no documented evidence of the illegal origin of the money.

Usually, it gets transferred into multiple bank accounts or used to purchase property, artwork and luxurious vehicles. Besides that, gambling in casinos is also another offshore technique for laundering activity, as casino venues change often and employees do not tend to work long term. With the money being passed through the system in such a complex matter, it’s unlikely for the origin to be uncovered so easily.

Now with the 3 stages in mind, it’s worth exploring the harmful effects of money laundering.

The harmful effects caused by money laundering

The increase in drug trafficking, which is the source of money laundering activity, has caused a reduction in economic growth as black money gained from this criminal act was washed illegally, and entered the financial market without legal acknowledgement. Thus, this serious financial crime has definitely caused numerous negative impacts on the economy, especially on the financial sector institution. 

Effect on tax revenues

As we all know, taxation is a big part of the government’s revenue. In other words, the higher the tax revenue, the more the country benefits, as there is more funds for public spending. But because illegal drug money is not accounted for, the following may occur:

  • if tax revenues fall, governments may need to borrow money to fund expenditures
  • when governments borrow money from private institutions, this creates a crowding out effect
  • Crowding out effect: level of investment from the private sector decreases, as interest rates become high as a result of government borrowing
  • An increase in interest rates could lead to a fall in consumption and overall growth

Effect on money demand

When there’s a sudden inflow of money with increased spending, economic theory tells us this will lead to inflation. Take note of the Fisher Equation: where Money Supply x Velocity = Price x Output

MV = PY 

Policy makers now have to grapple with higher inflation, which may mean increasing the interest rate in the short term, which could lead to a slowdown in economic growth. Policy makers may also choose to decrease government spending, which could lead to cuts on key welfare spending, leaving individuals who rely on these services the most vulnerable.

The economy is put into disequilibrium and policy makers are unable to create effective policies as a result.

Effect on economic growth

If money laundering is well known and institutionalised, investors may lose confidence in investing in said country. This is true for foreign investment, as they see more risk and could even lead to brain drain: where potential valuable locals leave the country for better opportunities elsewhere. The long term economic prospects fall as a result, as there is no investment for capital spending, growth, and individuals who could have possibly created value.

What has the government done?

Money laundering has been a threat towards the economy as it has negatively affected the financial sector and the country’s reputation. With this growing epidemic, the government has stepped up their strategies in dealing with this criminal act with the help of financial institutions such as banks, who work by rebooting the systems in monitoring and reporting any fishy activities. The process is called Anti-Money Laundering (AML). The initiatives underway to succeed in this regard are as follows:  

KYC (Know Your Customer)

Banks can start their investigation process by collecting information from their clients. A great starting place to analyse whether these account holders have put themselves in any risks include collecting specific details about their identity, citizenship, career, the countries they invest or do business with, volume and type of activity, and especially the source of their money. Equipped with this data, customers who raise suspicions with their bank activity by doing things such as creating accounts in countries far from where they live and doing business without any valid reason, will be observed more attentively by financial authorities.

The use of technology

As technology has played such a big role in our daily lives, introducing Artificial Intelligence (AI) and machine learning could replace the old and slow manual way in personally identifying money laundering, which some may argue is highly inefficient.

AI is more capable and faster in scanning large amounts of data. For instance, Data Robot is an automated machine learning platform that can ease the bank’s investigation process for suspicious activities. As a start, this software helps to learn customer’s bank data, transaction activities from investigation, and suspicious activities which are reported to build algorithms that eliminates unlikely activities by stating out the high-risk pattern transactions. Additionally, it adjusts the suspicious activity alert by reducing false alarms and specifying risky activities going undetected. Apart from the function of classifying the characteristics of customers and transaction activity, it can also notice unusual activities for similar clients based on their traits, which is a good predictor in preventing money laundering. The usage of advanced technology will help banks to comply with the AML regulations better. 

Frequent changes on policies

The foundation of AML deference are policies that demand appropriate risk assessment, training mechanisms, and audits of control across the institution. An example of this happened in 1989, when the Financial Action Task Force (FATF) was formed to go against money laundering internationally. In 1970, the United States passed the Banking Secrecy Act that required banks to report specific transactions to the Department of  Treasury, such as cash transactions that are over $10,000 or any other suspicious activity. This information was shared along with the domestic criminal investigators, international bodies or foreign financial intelligence units by the Financial Crimes Enforcement Network (FinCEN). As a result, these laws were helpful in tracking criminal activity like money laundering. With such changes in policy, it will be much harder for criminals to launder money as they are always kept on their toes, with new changes. 


Though government and financial institutions play a main role in trying to weed out money laundering, individuals and citizens can help out too by reporting any suspicious activities around ATM machines to authorities or if we’ve heard clues through the grapevine, as we never know if that is part of the chain of money launderers. Only by mutual cooperation from various parties across societies can this criminal act stop effectively for good.


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ST Pauls Chamber, 2021, Stages of Money Laundering Explained. [online]. ST Pauls Chamber. Available at: 

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Sanction Scanner, 2021, Negative Effects of Money Laundering on the Economy. [online]. Sanction Scanner. Available at:  

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Insider, 2011, How A Major U.S. Bank Laundered Billions in Mexican Drug Money. [online]. Insider. Available at:              

Compliance Week, 2020, How Danske is cleaning up after a 200B Euro money laundering scandal. [online]. Compliance Week. Available at:                                                                

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Researcher: Yeoh Yi Ying (Janice)

Reviewer: Muhammad Bahari

Editor: Johanna Lok

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