Anti Money Laundering Compliance: On entering 2021, the majority of industries are facing an increasingly daunting number of anti-money-laundering (AML) laws and regulations. Within the last few years, regulatory bodies have been aggressively enforcing these regulations, and have also levied hefty fines for compliance failures.

In 2019, financial authorities levied money laundering fines worth US$8.14 billion. In 2020, the trend continued. According to Finbold’s Bank Fines Report 2020, global authorities charged US$13.74 billion in AML fines, with the largest contributors being three US-based banks, namely Goldman Sachs, Wells Fargo, and JP Morgan Chase.

An Overview of AML Compliance

What Exactly is Anti-Money Laundering Compliance?

Anti-money laundering compliance includes the procedures carried out for making customer background checks and the ongoing process of monitoring their activity. These procedures consist of customer details being checked against sanctions, global watchlists, and PEP (Politically Exposed Person) lists.

Anti-Money Laundering screening and KYC (Know Your Customer) verification is mandatory for several industries like financial institutions, fintechs, stock exchanges, real-estate, cryptocurrency service providers, gaming etc.

Top 4 AML Compliance Strategies

The regulation ecosystem aimed at the prevention of money laundering is also known as AML. In the European Union, the guidelines to follow for making up a compliance plan can be found in the Anti-Money Laundering Directive (AMLD5). In the U.S., similar guidelines are devised by the Bank Secrecy Act (BSA). Businesses have to draft and implement policies that enable firms to stay in compliance with these guidelines.

These set of policies and strategies are found in the AML Compliance Program of an organisation. To devise this program and comply with regulatory requirements, the following 4 strategies should be implemented by firms.

1.     Practice Due Diligence

Every existing and potential customer should go through the process of Customer Due Diligence (CDD), so that businesses can determine what threats they may pose. After accurate identity verification of legitimate customers through KYC and AML checks, a risk score needs to be calculated subsequent to. This step involves screening the prospects against sanction lists, Politically Exposed Persons (PEPs) lists and global criminal watchlists.

2.     Timely Identification of Suspicious Activity

Business owners should always be on the lookout for potential red flags that might point towards a fraudulent transaction or customer. In case suspicious funds are identified, a Suspicious Activity Report (SAR) has to be reported directly to law enforcement authorities in a timely manner to avoid facing any penalties.

3.     Training the Employees

Industries, especially in the financial sector, need to set up proper training programs for their employees so that they may be able to identify any suspicious activity that they come across. The reporting policy should also be devised in a way that once an employee reports a suspicious activity to the management, a designated AML compliance officer immediately reports it to the FIU (Financial Intelligence Unit) to find enough evidence and prove the suspicious activity.

Additionally, employees that come into direct contact with customers on a daily basis should receive regular comprehensive training, so that they are aware of necessary anti-money laundering legislations.

4.     Invest in AI-Powered Solutions

If firms invest in integrating AML verification software into their systems, the need to hire AML and KYC verification professionals will be eliminated. By automating the anti-money laundering verification process, customer identity can be rapidly, efficiently and accurately verified within seconds which enhances customer experience.

Summarizing the Key Points

The rising cases of AML compliance failures in 2020 highlighted the challenges businesses face at the hands of money launderers. New regulations in the U.S. and Europe demonstrate a shift in focus on cryptocurrency, along with a concern for new tactics money launderers are using in the FinTech industry. Similarly, transaction monitoring failures propose a need for businesses to adopt robust alert methods to make sure SARs (Suspicious Activity Reports) are sent to regulatory authorities in a timely manner.

Finally, due to the growing complexity of Anti-Money Laundering compliance laws, firms are increasingly utilizing automated solutions to stay in compliance, including the integration of artificial intelligence (AI) and machine learning (ML) models that are capable of recording and monitoring vast amounts of data.

Anti-Money Laundering Compliance

AML compliance refers to the process of ongoing monitoring and background screening of existing and potential customers to detect and prevent financial crimes like money laundering. During these anti-money laundering checks, customers are screened against sanctions, global criminal watchlists, and PEP (Personally Identifiable Information) lists for risk assessment. To prevent financial criminals from carrying out illegal activities, organisations use AML monitoring software for continuous risk assessment. These software enable automated verification of high-risk individuals in the following steps:

1. The name and DoB of the end user are entered into the system
2. The information entered is checked against sanctions and watchlists
3. Results are delivered within seconds

As the nature of money laundering schemes become more sophisticated and vast, businesses are faced with increased regulatory compliance to safeguard themselves and their customers. This extends beyond (Know Your Customer) KYC measures, to ongoing AML checks and compliance.

By following global Anti-Money Laundering monitoring policies, organisations are not only able to secure their systems,  but also enable timely reporting of suspicious cases to regulatory bodies. An effective risk-based AML program and a strong culture of compliance within an organisation can help them thrive towards fines and loss aversion.

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