Money has been the most instrumental tool invented by humans to date, and it has seen big developments in the last couple of years through technological advancement concerning money transfers. However, while globalization and innovation in technology have helped in facilitating large sums of money quickly, it has also helped in rapid money laundering, which amounts to between 2–5% of GDP, equivalent to the fifth largest economy in the world according to the United Nations.

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The threat that money laundering poses was recognized by the OECD (Organization for Economic Cooperation and Development) quickly, which led to roughly 1,300 agreements of bilateral exchange of information between 34 countries that it represents. It has resulted in developing countries returning about $147 million looted from developing nations through money laundering and the freezing of USD 1.4 billion in looted assets between 2010 and 2012. Although efforts have been made to reduce money laundering, enforcing strict actions against institutions is futile. Real estate agents, lawyers, currency exchange institutions, and trust and company service providers are the few preferred means of entry for money laundering criminals, which both the public and private sectors have failed to stop.

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Apart from the OECD countries and the regulators, banks have started investing heavily in their compliance departments. The six largest banks have seen their compliance costs double from USD 34.7 billion to USD 70.1 billion because of acquiring new resources to fight financial crime. Moreover, a recent survey by KPMG has brought into light that banks estimate the risk of AML compliance growing year on year. The criminals, on the other hand, are shifting tactics at a rapid pace by making their way into P2P lending, hawala, casino gambling, abuse of diplomatic pouches, real estate, trade financing, fraud, and fake invoicing to spread the risk of money laundering in a bid to avoid the areas which are under most scrutiny.

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The impact of money laundering does not only impact the banks but also has its effect on the economy and society as a whole. Here are a few examples where money laundering has affected our economy and society:

• London property prices are being inflated by offshore criminal assets, while 60% of house purchases are being paid for in Ireland. More than half of the property in Miami-Dade Country in the United States is bought with cash, double the national average for the United States.
• Corporations with favorable tax arrangements are distorting global trade and attracting scrutiny and censure.
• International money transfer organizations like SWIFT and, to a lesser extent, Travelex and Western Union have good oversight of payments. Large portions of global trade are still ‘fictitious’—for example, shoes sold to a foreign country that doesn't actually exist except on paper—because it’s harder to detect trade-based money laundering than traditional money laundering.
• The emergence of virtual currencies means that some of the current AML defense mechanisms will be invalid and impossible to enforce in the future.

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The introduction of technology into compliance has shown a two-sided effect. On the one hand, it enhances the power, scope, and scale to investigate and manage money transfers; on the other hand, it hinders advancement. While companies have created complicated end-to-end solutions for the end-user companies, there still lies a gap where solutions can provide efficiency and optimize the current systems to generate further returns from what is already in place. In recent times, two new technologies that will help deliver efficiency and tackle money laundering have emerged: blockchain and machine learning.

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Blockchain

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Blockchain helps in the creation of a database of transactions that are tamper-proof and can be a useful technology in dealing with money laundering. The technology will help in creating an audit trail and mapping beneficial ownership. It has already been used to help investigators track illicit transactions, fraud, and theft. In addition, bankers also hope to use blockchain technology to reduce costs, augmenting or replacing traditional tools to ensure compliance.

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Machine Learning

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In the past few years, big data has been used by the majority of the banks, and the data has been automated to get insights into various trade patterns. Regulators and industry bodies accept machine learning and big data analytics as a useful addition to strengthening its compliance team. Many institutions have taken tools such as Hadoop and predictive and prescriptive analytics techniques to optimize their infrastructure and software licenses.

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Innovations like blockchain and machine learning can be instrumental in diminishing money laundering. However, to ensure legal compliance and regulatory standards, governments should work in tandem with new technology in experimenting with setting up a robust financial system.

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To learn about Prove’s identity solutions and how to accelerate revenue while mitigating fraud, schedule a demo today.