Leverage AI analytics to optimize AML strategy

Money launderers “wash” over $2 trillion out of the global economy each year, despite the best efforts of financial institutions (FIs) and governments. Much of their success is tied to the ability of money launderers to cheat old anti-money laundering (AML) strategies by stealing the identities of legitimate consumers and using their good reputations to clean up funds. illicit, often on the scale of millions of dollars at a time. This is a change from money laundering strategies which require “money mules” to actively participate in money laundering schemes. Today, with just a few clicks, criminals are creating new ways to commit money laundering crimes, and this new link between fraud and AML strategy is significant, requiring a new approach to analytics for FIs. .

These are just some of the ideas revealed in Enhanced management of AML and fraud riskst: Analysis Guide for Generating Enhanced Alertsa PYMNTS and Featured space collaboration. The report details changes in the way money launderers and fraudsters operate and how the integration of artificial intelligence (AI)-based analytics can transform AML strategy.

Additional findings include:Featurespace - Augmented AML And Fraud Risk Management: Analytics Guide To Enhanced Alert Generation - March 2022 - Learn how banks can leverage augmented analytics to support modern AML and anti-fraud strategies

• Money launderers are changing their tactics as new technologies develop. As user experience features such as seamless connections between bank accounts and e-commerce become more commonplace, money launderers have more opportunities to create clever ways to evade AML flags based on legacy rules. . A single data breach can allow a money launderer to access a victim’s entire digital identity and use it for money laundering activities long before a consumer – or his bank – be aware.

• AI and behavioral analytics can help FIs spot money laundering activity at the transaction level. Even when a consumer’s identity has been impersonated – or a financial mule has been used to launch a money laundering scheme – sophisticated analytics can detect suspicious changes in consumer behavior before a transaction not be carried out. Featurespace - Augmented AML And Fraud Risk Management: Analytics Guide To Enhanced Alert Generation - March 2022 - Learn how banks can leverage augmented analytics to support modern AML and anti-fraud strategiesWhile many financial institutions created their AML strategy long before the age of AI, there are solutions to augment existing systems without “rip and replace” current tools when a vulnerability is identified.

• The right analytics solution can complement existing AML systems while transitioning to more modern tools. The right augmented analytics solution can deliver accurate insights that make it easier for organizations to prepare, create, and explain insights. This makes it easier for FIs and other entities to tailor transaction risk scores and reporting rules to security, user experience and operational imperatives. Additionally, access to better data can translate to better long-term business outcomes. Augmented analytics does more than improve the accuracy of transaction risk scoring and helps organizations identify risk and strengthen security – the technology also enables organizations to lay the foundation for long-term growth and product innovations of the future.

To learn more about FIs that can leverage new analytics tools to bolster their AML strategy, To download The report.