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The three key characteristics to detect money launderers in the financial sector

The growing complexity of the financial sector is creating new opportunities for money launderers. As a result, it is essential that financial institutions are equipped with the appropriate knowledge and resources when it comes to identifying financial crime.

Money laundering poses a lasting threat to the global financial system, enabling criminals to appear legitimate and perpetuate such crimes. To effectively detect and prevent money laundering activity, financial institutions must remain watchful and gain a deep understanding of the characteristics exhibited by money launderers.

So, what should they be looking out for, and what are these key indicators?

1. Formation agents

Formation agents, also known as company service providers, are regulated by Her Majesty’s Revenue and Customs (HMRC) and maintains a list of approved agents. However, HMRC does not publish the list, thus preventing potential customers from easily checking the status of an agent.

Money launderers typically use formation agents, shell companies, and complex corporate structures to conceal their identities and transactions. The person who ultimately owns or manages a company are always extremely hard to identify - hiding behind complex corporate structures that often cross borders. These individuals will often use residential addresses, mailbox addresses, serviced office addresses and it’s common for such addresses to be linked to a vast number of other companies.

2. Suspicious transactions

Customers trying to launder funds may carry out unusual transactions. Money launderers employ sophisticated techniques to disguise the true nature of their activities. Firms should look out for activity that is inconsistent with their expected behaviour, such as large cash payments, unexplained payments from a third party, or use of multiple or foreign accounts.

Financial institutions should use advanced data analytics and monitoring tools to identify such abnormal transactional behaviour, enabling the detection of suspicious patterns and subsequent reporting of potentially illicit activities.

3.  Multiple current accounts

We often find that money launderers don’t like to use only one current from one bank provider. Instead, they much prefer to use multiple current accounts across many different banks and transact in round balances under set thresholds.

Up until now, banks have only been able to see their own internal data - making it difficult to detect suspicious transactions which may span across various financial institutions. Under the Small Business Enterprise Act of 2015, the UK’s largest named banks were mandated to share current account turnover data on a monthly basis. This data is now available to use in Financial Crime detection and prevention, enabling the industry to benefit from aggregate transaction data sharing for the first time.

Recent Experian research shows that money mule activity now accounts for 42% of reported first party current account fraud. Given the growth in this type of activity, third party-data and industry data sharing is going to be key for identifying potential money mule accounts. To identify suspicious transactions, banks should have access to cross-institutional data and be able to report any concerning activities to the authorities.

Moving forward

Money laundering is on the rise, and while the guidelines to combat financial crime may seem challenging, simply understanding the red flags and implementing processes to identify and combat money laundering is your best defence.

The fight against money laundering is an ongoing battle that requires constant vigilance and adaptability. Financial institutions must have a clear understanding of the traits exhibited by money launderers. Heightened awareness and proactive measures are essential in safeguarding the trust and integrity of the financial system.

By using firmographic data to build “peer group” profiles, we can better understand normal transaction behaviour for each company, looking at their age, size, and sector, and generate an alert when behaviour is outside the norm. This can then be combined with additional adverse markers that denote the characteristics commonly associated with money laundering businesses and used to better detect and prevent financial crime.

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Grant MacDonald

Grant MacDonald

Director of Financial Crime

Experian

Member since

20 Mar 2023

Location

London

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3

This post is from a series of posts in the group:

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