GenAI

Oracle is adding another service to its rapidly growing list of cloud offerings that leverage generative AI, with this one enabling banks to more easily detect and mitigate the risk of money laundering within their institutions.

The corporate software giant this week rolled out its Oracle Financial Services Compliance Agent, an AI-powered cloud service that banks and other industry institutions can use to run hypothetical scenario tests to gauge their systems’ abilities to sort through transactions, detect nefarious activity or anomalies and ensure compliance with regulations.

It also shows the companies where they should adjust their thresholds and controls to tighten anti-money laundering protections.

“Putting Compliance Agent in the hands of financial-crime compliance officers will help enable banks to thwart potential money laundering opportunities more quickly and economically,” Jason Wynne, global vice president of finance, risk and compliance product development for Oracle Financial Services, said in a statement.

Assessing the Risk

The new service is part of Oracle’s larger family of anti-money laundering (AML) and financial crime and compliance portfolio. A key capability of the Compliance Agent is aimed at letting financial services organizations better assess the risk profile of new banking products and evaluate the controls to mitigate the risks, including giving a statistical basis for reducing conservative bias when determining AML controls.

The Compliance Agent helps “banks that are under pressure to introduce innovative products but must do so without exposing the bank to new avenues of money laundering and incurring extensive and costly assessments,” according to Oracle.

In addition, the service can assess and reduce risks from such high-risk typologies, such as human trafficking. As an example, using the tool to run an experiment can let a bank tune controls on transaction monitoring systems to increase their capabilities to catch such suspicious transaction patterns.

Banks also can use the Compliance Agent to not only put the best controls in place but also to keep them updated, as well as the framework’s “what if” capabilities to evaluate ranges of options and select the best solutions.

Other features include a configurable simulated environment for transaction monitoring systems and reinforcement learning to evaluate scenarios and identify gaps in monitoring and recommend fixes. The service also isn’t dependent on the institution having other Oracle tools or products.

Generative AI ‘a Gamechanger’

Generative AI and large language models (LLMs), which can rapidly analyze massive datasets, recognize complex patterns and adapt to changing circumstances are being embraced by financial services organizations for their AML portfolios.

“Using gen AI in anti-financial crime is a gamechanger,” Brian Robertson, financial crime expert for enterprise AI firm SymphonyAI, wrote in a blog post last month. “If you speak with a financial investigator working in financial services, payments, or gambling, they will tell you of their frustrations at having to spend an unequal amount of time gathering and sorting data when looking for risky customer behaviors.”

The company a year ago introduced Sensa Copilot, a tool that it claims can reduce the time for investigating a new alert by 70%.

Mitek Systems, which makes digital identity verification software, wrote earlier this year that “in the ongoing fight against financial crime, generative AI has emerged as a powerful and compelling tool. Its exceptional capability to analyze real-time transactions and customer behavior data allows for effective detection of anomalies that may indicate financial crime.”

 Trillions of Dollars Laundered

This will be important, given the worldwide scope of money laundering. According to the United Nations, every year the amount of money laundered is 2% to 5% of the world’s GDP – or from $800 million to $2 trillion – though the UN added that “due to the clandestine nature of money-laundering, it is however difficult to estimate the total amount of money that goes through the laundering cycle.”

Given that, it’s not surprising that tech vendors and cloud providers are running out generative AI-based AML tools and services. Google Cloud last summer introduced AML AI to help financial services institutions detect and mitigate money laundering. Smaller vendors also are getting in on the trend, with NICE Actimize, a subsidiary of NICE Systems that has more than 1,000 customers worldwide using its financial crime, risk and compliance solutions, rolling out three new generative AI tools in February to help with investigations into money laundering and other financial crimes.