Innovating Transaction Monitoring Using AI

$4.3 billion, $4.2 billion, $2.2 billion, $1.9 billion—what do these sums stand for? These are some of the biggest AML fines for failing to prevent fraud and maintain KYC policies. The first and largest one was imposed on Binance (US) just at the beginning of 2024; other were imposed on UBS, Danske Bank and HSBC respectively[1][2][3][4]. The risk for financial organizations is high. Therefore, you need to implement excellent transaction monitoring measures to prevent money laundering and the resulting potential fines. How to do this? With artificial intelligence. Read on to find out more.

Table of Contents

• The Critical Role of AML and KYC Compliance
• The Power of AI-Powered Transaction Monitoring Software
  • Efficiency
  • Accuracy
  • Customizable Reporting
• The takeaway

The Critical Role of AML and KYC Compliance

AML and KYC compliance are of the utmost importance in modern banking—every year, we hear about new organizations receiving enormous fines for failing to comply with these regulations. The largest players are no exception; even they are prone to be punished, with the likes of Binance (US), ING (Netherlands), HSBC (Mexico), UBS (Switzerland, France, US), JP Morgan Chase US), and Deutsche Bank (US, UK) receiving such fines in the past few years[1][2][3][4][5][6][7].

Your organization is no exception—if your AML and KYC procedures are ineffective, you put yourself at risk, even if you have the best intentions. Therefore, you need to apply the best practices regarding KYC, eKYC, and transaction monitoring in your business, one of which is the use of modern technologies.

The Power of AI-Powered Transaction Monitoring Software

Transaction monitoring is one of the most vulnerable processes among the KYC and AML obligations. On the one hand, you do it regularly; on the other, when conducted by humans, it is prone to false positives, human error, and inefficiencies. However, this is slowly starting to change with the use of artificial intelligence.

AI-powered transaction monitoring software is a true game changer. Why? It brings a lot to the table; you will find several examples below.

Efficiency

Business and client transaction monitoring may have a distinct name, yet, truth be said, it is simply a type of data analysis. And what tech excels at data analytics? Artificial intelligence.

With the use of this technology, you can process hundreds of thousands more transactions daily than when relying only on human experts. No more wasting time on control + c and control + v, just pure digital process automation, with humans involved at later stages to verify the findings of AI.

Accuracy

Artificial intelligence and machine learning constitute a pair that is often much more insightful than humans. If you train your anti-money-laundering transaction monitoring system with historical data, it will be able to spot patterns that your employees wouldn’t. As a result, such a system can detect more potential fraudulent activities for your employees to investigate than a human-based first line of monitoring.

Customizable Reporting

You may also prompt AI to create detailed reports of your anti-money-laundering efforts, enabling you to provide all the crucial information to the regulator when an audit occurs. This way, you will ensure that your documentation is always complete, even when the law changes.

The Takeaway

AI is the future of transaction monitoring, both in the B2B and B2C sectors. With it, you will stay compliant with AML and KYC regulations, and your efforts will become more efficient, effective, and scalable, leading to lower operating costs, decreased risk and higher flexibility. Therefore, have you not implemented such solutions yet, we recommend you do so as soon as possible.

You might also read: Digital customer onboarding – Know Your Customer module in practice

References:

1. Rubin, M. (2024, February 23). Judge approves Binance $4.3 billion guilty plea; U.S. seeks to modify founder Zhao’s bond. Reuters.
2. Scarcella, M. (2023, January 5). U.S. judge accepts Danske Bank guilty plea, $2 billion pact to end Estonia probe. Reuters. https://www.reuters.com/legal/us-judge-accepts-danske-bank-guilty-plea-2-bln-pact-end-estonia-probe-2023-01-05/
3. Alderman, L. (2019, February 20). UBS ordered to pay $4.2 billion for helping French clients evade taxes. The New York Times. https://www.nytimes.com/2019/02/20/business/ubs-france-tax-evasion.html
4. Viswanatha, A., & Yap, C. W. (2012, December 11). HSBC to pay $1.9 billion U.S. fine in money-laundering case. Reuters. https://www.reuters.com/article/us-hsbc-probe-idUSBRE8BA05M20121211/https://www.reuters.com/technology/judge-approves-binance-43-billion-guilty-plea-us-seeks-modify-founder-zhaos-bond-2024-02-23/
5. Arnold, M., & Strohecker, K. (2017, January 31). Deutsche Bank fined over $600 million for Russian money-laundering scheme. Reuters. https://www.reuters.com/article/us-deutsche-mirrortrade-probe-idUSKBN15F1GT
6. R, P. (2020, September 29). JPMorgan Chase to pay $920 million to settle trading misconduct allegations. CNN. https://edition.cnn.com/2020/09/29/investing/jpmorgan-chase-settlement/index.html#:~:text=JPMorgan%20Chase%20to%20pay%20%24920%20million%20to%20settle%20trading%20misconduct%20allegations,-By%20Paul%20R&text=JPMorgan%20Chase%2C%20the%20largest%20bank,precious%20metals%20and%20Treasury%20bonds.
7. The Globe and Mail. (2018, September 4). Dutch bank ING fined $900 million for failing to spot money laundering. The Globe and Mail. https://www.theglobeandmail.com/business/article-dutch-bank-ing-fined-900-million-for-failing-to-spot-money-laundering/

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