Anti-Money-Laundering AML Risk Approach Explained


AML Risk Assessment helps companies understand what conditions increase the chances of a customer’s involvement in money laundering or terrorist financing. To bolster their AML Compliance programs, financial institutions are increasingly turning to advanced AML compliance software that enables a thorough analysis of customer behavior, transaction patterns, and other relevant data. This empowers institutions to adopt a comprehensive risk-based approach, ensuring more effective detection and mitigation of potential risks.

Investigators need to understand the reasoning behind a model’s decisions and ensure it is not biased against certain groups of customers. Many institutions are experimenting with machine-based approaches combined with transparency techniques such as LIME or Shapley values that explain why the model classifies customers as high risk. Financial institutions have traditionally relied on experts, as well as regulatory guidance, to identify the inputs used in risk-rating-score models and decide how to weight them. But different inputs from different experts contribute to unnecessary complexity and many bespoke rules. Moreover, because risk scores depend in large measure on the experts’ professional experience, checking their relevance or accuracy can be difficult. And, importantly, they are more accurate, generating significantly fewer false-positive high-risk cases.

What Are The Keys Risk Indicators in Money Laundering?

Refer to Appendix I – Risk Assessment Link to the BSA/AML Compliance Program for a chart depicting the expected link of the BSA/AML risk assessment to the BSA/AML compliance program. The Anti-money Laundering (AML) Service market is witnessing significant trends and opportunities. Key trends include the adoption of advanced data analytics and AI-driven solutions to enhance transaction monitoring, customer due diligence, and suspicious activity reporting.

  • Once you complete the AML risk assessment, you can rate your clients as low, medium, or high risk.
  • Usually, the anti money laundering risk assessment will result in a categorization of risk, which will help organizations to determine the level of anti-money laundering resources necessary to mitigate that risk.
  • Investigators need to understand the reasoning behind a model’s decisions and ensure it is not biased against certain groups of customers.
  • Additionally, regulatory bodies like OFAC place strong emphasis on financial institutions adopting a risk-based approach, further underscoring its significance.
  • And they can spot spurious inputs that might result from statistical analysis alone.
  • One bank discovered that a great many cases were flagged as high risk and had to be reviewed because customers described themselves as a doctor or MD, when the system only recognized “physician” as an occupation.

Such models can dramatically reduce false positives and enable the concentration of resources where they will have the greatest AML effect. Financial institutions undertaking to develop these models to maturity will need to devote the time and resources needed for an effort of one to three years, depending on each institution’s starting point. However, this is a journey that most institutions and their employees will be keen to embark upon, given that it will make it harder for criminals to launder money. The factors used to measure customer risk have evolved and multiplied in response to regulatory requirements and perceptions of customer risk but still are not comprehensive.

Assessing the BSA/AML Compliance Program

The BSA/AML risk assessment process also enables the bank to better identify and mitigate any gaps in controls. The BSA/AML risk assessment should provide a comprehensive analysis of the bank’s ML/TF and other illicit financial activity risks. Documenting the BSA/AML risk assessment in writing is a sound practice to effectively communicate ML/TF and other illicit financial activity risks to appropriate bank personnel.

Likewise, your Solicitors Regulation Authority (SRA) might want to review your risk assessment process to determine whether your organization is putting in the appropriate effort to catch and prevent money laundering. To determine which clients are most likely to be involved with money laundering or other illicit activities, the assessment model looks at key risk indicators – or KRIs. KRIs refer to known vulnerabilities or aspects of a business that might attract criminals and money launderers. Once you complete the AML risk assessment, you can rate your clients as low, medium, or high risk. This information will determine the best way to monitor transactions, validate identities, and file suspicious activity reports. Henry Ogbeide is a Ph.D. student at Newcastle Business School, Northumbria University.

Financial Markets, Financial Institutions, and Fiscal Service

Ensure that you have the appropriate number of staff available and that they have adequate training. The chief compliance officer will manage the training program and determine the qualifications the staff should have. Each of these KRIs includes several risk drivers that influence how relevant they are to your organization. If the drivers increase the risk, then the rating will be higher – and vice versa. As such, the AML assessment will need to include a risk range so that you can take appropriate action. More detailed information can be found in chapter 2 of the anti-money laundering guidance for the legal sector.

anti money laundering risk assessment

Our network includes former regulators, federal law enforcement officials, compliance officers, bankers, economists and statisticians, information technology (IT) developers, and more. Most banks are currently on horizon one, using models that are manually calibrated and give a periodic snapshot of the customer’s profile. On horizon two, statistical models use customer information that is regularly updated to rate customer risk more accurately.

Advantages of the risk-based approach

We are thought leaders in the field and support ongoing efforts around the world to improve the effectiveness of the framework for fighting financial crime. ACAMS Risk Assessment automates the sanctions risk assessment process, and draws on best practices to help financial institutions worldwide build a sounds sanctions compliance program. An effective sanctions risk assessment (SRA) measures the inherent sanctions risks a financial institution is exposed to and the effectiveness of its risk controls. Each area of sanctions risk should be allocated an inherent risk rating and control effectiveness should also be rated. Deloitte’s AML/Sanctions practice has assisted many of the world’s leading organizations in developing and implementing all aspects of AML/sanctions programs. We have one of the largest and most mature financial crime practices able to provide efficient and consistent services for our global clients.

While statistically calibrated risk-rating models perform better than manually calibrated ones, machine learning and network science can further improve performance. ACAMS Risk Assessment is web-based, allowing for timely and seamless updates to help you keep up with ever-changing regulatory requirements. Assessing the risk level of each client is an essential part of the onboarding and know your customer process. At this stage, you should complete a sanction screening to confirm that the individual is not on an OFAC or any other Sanctions Lists. Your AML process should evaluate these factors over time to see if the risks are increasing, decreasing, or stable. After you have documented the key risk indicators and gained an understanding of the areas you should focus on, you must address the issue of staffing.


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