Wayne, PA, February 28, 2017 – QuantaVerse today announced that its artificial intelligence (AI) and data science-powered technology platform is uniquely designed to help banks and other regulated institutions comply with risk-based Anti-Terrorism and Anti-Money Laundering (AML) regulations, including the rule recently put into effect by the New York Department of Financial Services (DFS).
New York State’s Anti-Terrorism Transaction Monitoring and Filtering Program Regulation requires New York DFS-regulated financial institutions to “maintain programs to monitor and filter transactions for potential Bank Secrecy Act (BSA) and AML violations and prevent transactions with sanctioned entities, and certify compliance with the regulation annually to DFS.” Significant to this new regulation is that institutions must review their transaction monitoring programs to ensure they comply with regulatory safeguards. Institutions must also adopt either an annual board resolution or senior compliance officer attestation to certify compliance with the DFS regulation beginning April 15, 2018.
QuantaVerse is uniquely able to provide institutions and their senior compliance leadership with data-driven solutions to enhance their existing transaction monitoring systems. QuantaVerse employs state-of-the-art proprietary algorithms to find hidden risks in the flood of transaction data that institutions deal with daily. QuantaVerse’s data analysis is powered by artificial intelligence that helps institutions identify where their risks are today and where they are migrating.
Leveraging QuantaVerse’s AI and data science-powered platform, financial institutions can address the New York DFS regulation in the following ways:
- Quickly identify counter-terrorism finance (CTF) red flags through CTF-specific algorithms;
- Provide predictive analysis of customers who might engage in CTF typologies in the future; thereby enhancing transaction monitoring and Know Your Customer (KYC) effectiveness, and;
- Provide the Board or senior compliance officers with added assurance that their transaction monitoring program adheres to the regulation before they sign their annual attestation.
Historically, financial institutions have relied on ineffective rules-based monitoring systems that lead to excessive false positive alerts as well as case management software to track manual and time-consuming investigations. An automated, AI-based approach, however, can be much more efficient, effective and cost-effective than traditional data analytics approaches.
“QuantaVerse applauds the New York DFS for enacting these regulations,” explained David McLaughlin, CEO of QuantaVerse. “Strengthening BSA and AML compliance among financial institutions is essential to choking off the money that funds terrorism and other illegal activities. With our AI and data science platform, financial institutions’ compliance leaders and AML teams can have confidence that hidden risks are being discovered and criminals are being stopped from laundering money through their organizations.”
QuantaVerse is the emerging leader in data science‐powered risk reduction and revenue growth solutions, purpose‐built for the global banking industry. Founded by financial services industry veterans and innovators, QuantaVerse solutions employ proprietary data science algorithms, integrate and filter internal bank data and related external data – including public Internet data, unindexed deep web data and government and commercial datasets – to help the global banking industry to significantly improve their compliance with AML, KYC and BSA regulations and requirements. QuantaVerse solutions also drive revenue by turning KYC data into strategic insights about the markets and customers they serve. To learn more how QuantaVerse can help your financial institution, please contact us at (610) 465‐7320.
Report: How Financial Firms Are Using Artificial Intelligence and Machine Learning to Meet AML Demands of Today and Tomorrow
It’s a well-known fact that the global pandemic caused a radical shift in consumer banking and payments behavior. What isn’t as obvious is how financial institutions responded behind the scenes. Fortunately, a new study helps shed light on the pandemic’s impact on the adoption of new technologies for anti-money laundering (AML) efforts.
Regulators and those handling compliance at covered institutions have long accepted the pitiful state of AML program efficacy, including: An estimated $2 trillion laundered through the global banking system annually 90+% of false positives coming from transaction...
While not mandating that firms invest in technology to automate financial crime investigations, regulators are certainly encouraging it. They are noticing that advanced BSA/AML teams are using robotic process automation (RPA) bots to gather data for investigations. They are aware that those same firms are using machine learning to analyze huge data sets, identify patterns, and pinpoint where exceptions or anomalies exist.