In financial crime compliance, regulators have set expectations for financial institutions to conduct thorough assessments of name screening alerts.
According to Napier, to meet these expectations, financial institutions must evaluate and consistently update the adequacy and relevance of their client screening parameters. This involves assessing the quality of data, aligning with the institution’s risk appetite, and crafting policies to govern the review and discounting of alerts.
The Monetary Authority of Singapore (MAS) in their recent guidance, ‘Strengthening AML/CFT name screening practices’, lays out several best practices for financial institutions. It recommends setting a name matching policy that matches the risk appetite of each client, which includes evaluating legal, regulatory, reputational risks, as well as data quality, customer types, products, and operational regions. The goal is to ensure that the alerts generated are strictly those representing a genuine risk, in line with the institution’s policy and declared risk tolerance.
Moreover, setting parameters and assigning weights to various attributes like name, date of birth, and country of incorporation is crucial. These identifiers help in matching individuals or entities against listed profiles, and the corresponding match score is calculated based on how similar the customer information is to the target profile. It’s vital that the assigned weights reflect the importance of each attribute to avoid undue alerts that might not support additional attributes.
Fuzzy name matching is a critical component for an efficient client screening process. This technique includes matching phonetically similar names, names in foreign characters, transliterations, and even nicknames which might vary culturally. For instance, variations like Amy Hawkenberry vs Aimee Hockenbury, or nicknames in different languages, showcase the depth of analysis required.
Regarding token matching in sanctions screening, financial institutions should establish policies that address differences in name orders, middle name importance, and conflicts between tokens. For example, the name ‘John James’ could be considered a strong match to ‘James John’ depending on the institution’s confidence in its data entry process.
One of the most critical aspects covered by the MAS guidelines is the appropriate management of alerts. Common mistakes in alert dismissal, such as using passport number differences or P.O. box addresses as justification for dismissing an alert, are highlighted. It’s emphasized that dismissals based on such identifiers are inadequate due to their changeable or non-specific nature. Furthermore, dismissing alerts based on the source or age of adverse news without proper justification is discouraged.
For effective regulatory compliance and auditing, it’s crucial to properly document the review process and verification efforts after evaluating alerts. This documentation should include details such as the information considered, the work performed, and the identities of the preparer and approver. This ensures clarity and accountability in decision-making processes.
For advanced solutions in client screening, technologies like Napier AI’s Client Screening with a Regulatory Reporting Manager module are instrumental. These technologies help compliance teams gather and submit high-quality suspicious activity reports efficiently and securely to enforcement agencies, significantly reducing the time required for report compilation.
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