Money laundering poses a significant risk to the integrity, proper operation, reputation, and stability of society in terms of the financial system in the current context of the unprecedented evolution of technology and the ability to conduct transactions, particularly in the electronic, virtual environment, anywhere in the world, at high speed.
The financial sector is starting to undergo a significant transformation due to technological advancements. In order to ensure that anti-money laundering (AML) and countering terrorist financing (CFT) regulations are kept current as new technologies are developed, The Financial Action Task Force (FATF), the international organization tasked with preventing money laundering and terrorist financing, has already expended a lot of effort in this area.
The compliance sector is increasingly familiar with terms like artificial intelligence (AI), fintech, machine learning, regtech, and big data, but how are these technologies being utilized to stop money laundering, and what does the future hold for a compliance professional as a result?
Advantages of Technology: Big Data, Machine Learning, and AI
Big data, AI, and machine learning have allowed businesses to take a more intelligent approach to fighting financial crime while also making it faster and less expensive. Financial institutions are switching from the conventional black-and-white rules approach to a more technologically oriented, flexible, and all-encompassing program that is much more effective at spotting anomalies.
Transaction monitoring is one example of a slow, manual activity that is now automated using machine learning and artificial intelligence (AI), which can scan vast amounts of data much more quickly than humans.
Traditional trigger alerts, such as those based on a transaction exceeding a specific threshold or taking place outside the account holder's country of residency, sometimes result in false positives, necessitating human assessment to ease any worries.
But since AI can quickly spot patterns in behavior, transactions, and abnormalities, compliance specialists may spend more time analyzing the data, looking into the causes, and sharing their findings with other financial institutions or authorities.
Technology's benefits go beyond transaction monitoring. Big data has made it possible for organizations to go beyond merely tracking financial crime at the transaction level and to begin "mapping out" strings of transactions, allowing for the establishment of links and the identification of patterns in the data. This makes it easier for the organization to identify the origins of illegal behavior.
Financial institutions can establish the people, organizations, and supply chains involved in the laundering process as well as a better understanding of the trail of illicit gains from activities like drug, arms, human, and wildlife trafficking as well as slavery, corruption, fraud, and other similar crimes through the use of big data.
Digital Customer Solutions for Due Diligence
Digital identification solutions
Many institutions use eKYC (electronic Know Your Customer) as a preferred method of electronic ID verification as an efficient digital substitute for Customer Due Diligence (CDD) procedures. One of the nations that embraced the eKYC method is India, which uses the 12-digit Aadhaar ID number provided by the Unique Identification Authority of India (UIDAI).
The use of machine learning for CDD
The AML-based monitoring system is used by Brazil's Systemically Important Financial Institutions (SIFIs) in their CDD and other identity management processes for their partners and employees in order to more effectively, quickly, and accurately identify new money laundering or terrorist financing risks thanks to machine learning.
Downsides of Technology in AML
When illicit quantities are put in a bank, money laundering begins. This sets off a complicated series of banking transfers or business transactions (layering), which return the money to the launderer in a mysterious and indirect manner (integration). Due to the intricate layering procedures used to conceal parties and tiered transactions, it might be difficult to detect. The transactions pass the funds via a number of intermediaries, businesses, and financial institutions, making it difficult to determine who the actual owners are.
Anti-money laundering techniques must evolve to keep up with fraudsters' increased sophistication and cunning. Each year, banks invest about $40 billion in the fight against financial crime to prevent such things exemplified below:
- The hidden layered money behind a high volume of organized digital transactions in online marketplaces
Fraudsters have become more skilled at committing money laundering crimes by utilizing technological advancements and the burgeoning digital economy. Due to the massive number of transactions handled on those platforms, criminals may believe their actions will go undiscovered and utilize online markets to launder money. A lot of nations are moving toward faster payments, which makes it possible for criminals to transfer illegal funds much more quickly and internationally. Technology advancements have made it feasible for such a large number of transactions, and as a result, compliance teams have been forced to work harder.
- The use of unregulated alternative forms of financing, such as bitcoins.
Developments in technology and the emergence of alternative money have also been exploited for sinister ends. For example, bitcoin exchanges have opened up a new route for money laundering. In 2019, $2.8 billion in illicit funds were laundered, up from $1 billion the year before.
Exchanges must adopt Know Your Customer and Anti-Money Laundering policies that keep out criminal actors with malicious motives, protect legitimate customers, and allow them to deal in a safe and secure manner.
Technology advancement isn't always negative for businesses; it can help organizations keep one step ahead of thieves. Artificial intelligence and machine learning algorithms are now being used to identify intricate patterns in criminal activity, and early adopters of these technologies are now reaping the rewards. Though AI is not a recent development, there have been some significant improvements in recent years that have allowed the technology to outperform human decision-making abilities frequently. Businesses will use AI in conjunction with the cloud in the next years as they strive for increased accuracy, efficiency, and security.
However, in order to use these technologies safely and soundly, we need an effective legislative framework, proper supervisory monitoring, and a comprehension of not only the potential but also the limitations and hazards of these technologies among all users, including banks and supervisors. Technology itself is neither good nor terrible; people only decide that it is.
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