For most people, money laundering is just a confusing term. They think that as long as it is not happening in their town or around them, it will not affect them. But that is not the case. Money laundering affects society at many levels. It significantly affects one’s life in social, economic and security terms.
The government has no way or very few old ways to track the laundered money and hence, it loses taxes associated with that money. This leads to higher tax rates for everyone else. Sometimes, the government may have to cut the financial assistance programs because of lack of funding through taxes. Unaware of the facts, sometimes business owners or bank managers assist in the money laundering and end up losing the business or the jobs. Even the investors or most tax-paying citizens don’t want to associate themselves with these businesses. And hence, the revival of the business also becomes difficult.
Sometimes, the companies through which money is being laundered lower the price which makes it difficult for legitimate businesses to compete in the market. These situations lead to loss of jobs in the market. Most of the times, the laundered money is moved underground which is a loss of asset for the government. And lastly, this laundered money can also be used to fund terrorism or hate crimes.
Till recent times, the detection of money laundering cases used to be done manually. The government has placed many regulations and compliance criterion to control money laundering. According to the stats, the US government spends nearly $20 billion per annum to control money laundering. But they are still losing over a trillion-dollar.
Fortunately, technology is helping to come up with an effective and cheaper solution. The AI algorithms help to gauge risk and also allow the banks to serve their customer better. AI can quickly go through a large amount of data. And hence it can assist the bank employees doing same and detect strange patterns. This helps to quickly detect possible suspicious activity. And then further intervention determines whether it is actually a money laundering case.
Banks or financial institutions face hefty fines if they are unable to detect the money laundering or fraud cases. And hence, they are investing more and more in Artificial Intelligence and trying to improve their algorithms so that they don’t miss the money laundering cases. They are also trying to reduce the number of false positives so that they don’t waste their time and resources chasing the false positives.
AI has shown a lot of potential in the anti-money laundering job. But a lot of AI potential still remains untapped. This simply means that people should not just assume that they have found every way to catch money launderers. Some of the ways which don’t seem practical or implementable right now might turn out to be a better solution in the future.