What is the connection between transaction monitoring and AML compliance?
In today’s financial environment, the reputation of financial institutions operating in the private sector is conditioned by the measures they take to ensure compliance with Know Your Customer (KYC) and anti-money laundering (AML) regulations. Are you the manager of a FinTech whose core business is conducted in North America or Europe? If so, under current legislation, you will need to implement transaction monitoring measures to identify potential financial irregularities before they affect your organization’s finances.
KYC and AML compliance is essential to the development and economic success of financial institutions active in the private sector. In the United States and Europe, private institutions involved in the financial industry are required by law to implement AML and KYC procedures that prevent money laundering operations or the financing of organized crime groups.
Has your agency not implemented a practical AML framework? If so, your activities could be scrutinized by the Financial Crimes Enforcement Network (FinCEN), which, in case of irregularities or non-compliance, will impose monetary penalties.
How do financial institutions implement transaction monitoring?
AML compliance is crucial for companies active in the financial markets that wish to operate internationally. However, to achieve AML compliance, financial institutions must first implement transaction monitoring and supervise the activities of service users in real time. Transaction monitoring begins with the implementation of KYC procedures, whereby financial firms collect personal customer data, investigate past financial behavior and assign a risk score to recorded transactions.
Once this data is collected, it must be investigated, a process that, in today’s financial climate, is generally done with the help of artificial intelligence. AI-based AML applications can analyze patterns in the collected analytical data, detect suspicious transactions five times faster than conventional tools and have a significantly lower false positive rate.
AI-based AML applications can flag high-risk customer-to-customer transactions, investigate forged transfers between accounts, and implement risk-based threshold systems developed internally by financial institutions. In addition, AI programs for KYC and AML can assist in the filing of suspicious activity reports (SARs) and are the only realistic solution for the rapid implementation of enhanced due diligence (EDD) measures.
How are AML regulations enforced in the U.S.?
KYC and AML regulations are enforced nationally by FinCEN, which acts in accordance with the rules set forth in the Bank Secrecy Act of 1970 and the PATRIOT Act of 2001. Under the BSA, companies active in the financial sector operating in the United States are required to file reports with FinCEN for any cash transaction in excess of $10,000. These transactions can include anything from withdrawals to down payments for various services.
In addition, companies involved in the financial sector are required to file a suspicious activity report for any transactions that may be associated with money laundering activities and to verify the identity of users opening new accounts.
The U.S. PATRIOT Act of 2001 was implemented following the terrorist attacks of September 11, 2001, and although it was initially intended to be a temporary piece of legislation, its implementation is still in effect 23 years later. Section 314 of the PATRIOT Act obligates financial institutions present in the domestic market to cooperate with national authorities in investigations related to national security.
In addition, Section 326 mandates the implementation of EDD for transactions conducted from high-risk jurisdictions. In addition, the PATRIOT Act prohibits U.S.-based financial institutions from maintaining nostro/vostro accounts with proven shell companies outside of U.S. supervision.
Companies that violate the regulations imposed by the Financial Crimes Enforcement Units can be penalized up to $1 million or double the value of the transactions that failed to comply with AML regulations. In addition, if the authorities conclude that the violations were intentional, the individuals involved could even be criminally prosecuted. Has your financial firm failed to achieve compliance with KYC and AML regulations? If so, the OCC could revoke your license to operate, leading to civil lawsuits. In addition, your assets could be seized temporarily or permanently.
How does AI help in transaction monitoring?
AI has progressed significantly in the last five years and is now an integral part of most AML programs used by companies active in the international financial sector. How can AI help with KYC and AML compliance? For starters, through real-time analysis of large amounts of data, AI programs can identify patterns and anomalies that other traditional financial analytics programs might have missed.
AI-based AML programs are significantly more accurate than manual checks or conventional non-AI applications. In addition, the machine learning algorithms used by AI AML software can leverage multiple data streams simultaneously, perform real-time transaction monitoring, generate risk scores for clients or transactions, and adapt the monitoring parameters used to market developments.
This last point is, in fact, the most significant advantage of artificial intelligence. AML applications that leverage machine learning algorithms are able to continuously improve and can increase their accuracy and false positive rates through the analytical data they access.AI can adapt to changes in fraud techniques used by malicious actors, use natural language processing to prevent phishing attempts at financial fraud, automate the suspicious transaction reporting process, and maintain audit trails needed for FinCEN inspections.
A reality of the modern financial sector
What is the connection between AML compliance and transaction monitoring? In short, transaction monitoring systems are an integral part of comprehensive AML strategies and serve to detect suspicious financial activities that are not normally visible through manual inspections. Through transaction monitoring, companies active in the financial sector can assess the risk score of recorded monetary transactions, automate alerts for suspicious transactions and perform comprehensive audits of digital records.
Transaction monitoring is implemented simultaneously with KYC procedures, often leverages AI functionality and is mandatory for FinTech companies, banks, insurers, private lenders or credit unions. With the help of AI, AML applications can implement transaction monitoring by performing real-time analysis of recorded financial data and adapting the rule systems used to stop illegal financial transactions according to market changes.
AI models use machine learning to keep up with new money laundering techniques, employ advanced tools to identify patterns in the analyzed data and, in general, are a necessity to ensure the protection of companies active in the financial sector.
Related Articles
