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Fraud and money laundering: Coordinating against criminal threats

AML Compliance Knowledge & Training

Fraud and money laundering are often connected in criminal and regulatory contexts. This proximity is reflected in the crossover of responsibilities of anti-money laundering (AML) and anti-fraud employees. However, while they face similar threats, AML and fraud departments often operate in relative isolation from each other due to their differing objectives.

Given the damaging financial and reputational effects of fraud and money laundering, financial institutions need to be able to coordinate their AML and anti-fraud responsibilities effectively to both prevent criminal activity and protect themselves against regulatory consequences.

What is fraud and money laundering and how are they connected?

Fraud is an illegal act that involves deception to generate illegal proceeds. To conceal their illicit origins, criminals must launder funds into the legitimate financial system through various methods and channels. 

Connecting fraud and money laundering

The causal connection between fraud and money laundering can inform the firms’ process to detect and prevent those crimes. Suppose a customer makes a deposit with a suspected fraudulent check, for example. In that case, a fraud department must protect itself by investigating and establishing that the funds are real and that there is no risk of financial loss to the firm it works for. That process might involve requesting information from the customer or any associated financial institutions.

A fraud department’s conclusion that suspect funds are real does not eliminate the possibility that they are being laundered to conceal their criminal origin. While no further work is necessary from the fraud department, the anti-money laundering department must investigate the risk associated with the customer and the transaction. The AML process should involve a range of prescribed customer due diligence and screening measures, as well as coordination with financial authorities. 

In this podcast, ComplyAdvantage Founder and Executive Chairman Charles Delingpole interviews Hubert Rachwalski, CEO at Nethone. Nethone is a Poland-based fraud detection company using machine learning to detect and prevent card-not-present fraud and account takeover. Charlie and Hubert discuss the intersection of fraud, AI, and money laundering. 

Listen to the full episode here.

Defining anti-fraud and AML regulations

Anti-fraud and AML are the sets of laws and regulations created to discourage, prevent, and stop those that engage in fraud and disguise illegally obtained money from it.

AML and anti-fraud departments tend to utilize the same detection tools and parameters when conducting their respective investigations, including:

  • Data and transaction monitoring software.
  • Account and customer information.
  • Peer group definitions.
  • Watch lists.

However, while anti-fraud and anti-money laundering departments both function to detect and prevent financial crime, and use similar methods, they differ in their reasons for doing so. On the one hand, fraud departments function to directly address criminal activity and protect organizations from immediate and potentially significant financial losses. On the other hand, anti-money laundering departments focus on regulatory compliance and the need to protect the financial system itself — goals which, unlike anti-fraud efforts, do not tend to directly benefit an organization financially.

Fraud and money laundering prevention 

There are important differences between the methods employed to prevent fraud and those employed to prevent money laundering. Where fraud has been detected, firms can actively prevent criminal activity from occurring by voiding or canceling suspicious transactions. 

However, in cases of AML, suspicious activity cannot always be actively prevented in the same way – because doing so may alert the bad actor; therefore, in AML, suspicious activity should instead be closely monitored and reported to the relevant authorities. This is why suspicious activity reports (SARs) are vital and a legal requirement in many jurisdictions. SARs are investigated and, over time, a picture is built up of behavior patterns, geographical location, and whether particular sectors may be more vulnerable than others to money laundering. This information helps financial authorities in the AML sector to prevent money laundering and adapt their prevention tools and regulations.

As of February 2023, statistics show that the UK Financial Intelligence Unit (UKFIU), part of the National Crime Agency (NCA), receives almost one million SARs a year. Going forward, one of NCA’s priorities is to increase the quality of the SARs where money laundering is suspected.

Fraud and money laundering detection 

Both fraud and money laundering can be detected using rules. With the latest technology in place, firms can keep up to date with regulators’ revised rules as they change. However, criminals tend to shift their patterns to avoid detection.

To discover fraud happening in real-time, transaction monitoring is a key tool. Fraud detection tends to be more time-sensitive than money laundering detection, and so, to ensure timely action, it is critical to:

  • Filter out the high number of false positives (thought to be upwards of 90 percent according to IBM) and reduce the time and labor spent investigating them.
  • Ensure true positives are suspicious.

When fraud has been detected, the customer is alerted and asked to verify the crime. If the fraud is not detected in real-time, the customer will likely spot it after the fact and report it. 

If instances of money laundering are not dealt with when they are discovered, money laundering can continue to fly under the radar for months, if not years; therefore, both fraud and AML departments must be trained to spot red flags for one another. 

Anti-fraud and AML working together

Many firms choose to coordinate their AML and anti-fraud measures to address both types of crime more effectively. By working together, fraud and money laundering departments can also take a holistic view of the criminal threats they face and streamline the overall compliance response. While the integration of AML and anti-fraud provides several benefits, it must be done carefully, ensuring compliance obligations are not compromised in an increasingly complex regulatory environment.

Firms may choose to integrate AML and anti-fraud as a single process or, alternatively, continue to work both functions separately while collaborating more closely on their respective investigations. In both contexts, firms should formalize the relationship between their AML and anti-fraud departments and set out the features of their strategy. These may include:

  • A single transaction monitoring system that integrates both fraud and money laundering rules, along with relevant policies and processes for when suspicious transactions occur.
  • Cross-training of AML and anti-fraud employees to enhance interdepartmental expertise and encourage familiarity with corresponding policies.
  • Regular meetings between each department during which employees provide feedback to their counterparts, discuss strategies, and share case information.
  • An alert remediation process that serves both the AML and anti-fraud functions and involves benchmarks for successful case resolution.
  • A workflow map charting the progression of cases and allocating responsibilities to relevant employees or departments.
  • A unified case management system allowing AML and anti-fraud departments to share and exchange files between respective investigations.

Technology that handles both AML and anti-fraud 

Technologies like machine learning are crucial in the fight against both fraud and money laundering. AI is extremely useful because it can identify AML and fraud risk factors that are too granular or unable to be detected through rules.

In AML, rules can allow for adhering strictly to regulatory requirements. AI can also be useful for certain use cases, such as:

  • Identity clustering – clustering customers into groups based on archetypes of customer behavior and assigning levels of risk to each cluster.
  • Prioritization – where customers are segmented even more finely according to their perceived AML risk.

AI can also be used to fix issues with data quality and augment customer and transaction data. For example, firms can use AI to add GPS coordinates to potentially suspicious transactions and, in this way, start to build a picture of money laundering that would otherwise go undetected.

Data and technology

AML and anti-fraud processes each require the collection and analysis of large amounts of data, but that process becomes more challenging in a system where departments are working in coordination with each other. Smart financial crime technology offers a significant advantage to firms seeking to coordinate AML and anti-fraud by adding speed and accuracy to the respective processes. 

Digital solutions and AI tools can help departments organize and align their data collection and analysis objectives and, combined with human expertise, help bridge investigatory gaps between fraud and money laundering. 

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Originally published 12 March 2020, updated 23 April 2024

Disclaimer: This is for general information only. The information presented does not constitute legal advice. ComplyAdvantage accepts no responsibility for any information contained herein and disclaims and excludes any liability in respect of the contents or for action taken based on this information.

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