Blog

3 Lessons Learned from NAB’s Failure to Fix Financial Crime Loopholes

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.

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AML Investigation Trends in 2021 – and Beyond

Pandemic disruption in 2020 prioritized the automation of anti-money laundering (AML) investigations for compliance teams. Risk related to inconsistent investigation decision-making and reporting multiplied. The danger of penalties heightened. And now, the 2021...

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Identifying Shell Company Risk with Artificial Intelligence

While this is debated, the problem persists as legacy AML technology such as transaction monitoring systems (TMS) have little to no ability to identify and assess risk created by shell companies. And while policies, procedures, and processes, if applied correctly, can protect financial institutions from becoming conduits for some fraction of money laundering, terrorist financing, and other financial crimes, identifying shell company risk continues to be elusive.

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FIBA Conference Hosts Critical Discussion on AML Modernization in the Fight Against Financial Crime

On the final day of the FIBA conference, QuantaVerse Founder and CEO, David McLaughlin, participated on the “Customer Profiling, Use of Innovative Technologies in Onboarding and Risk Assessment” panel. David Schwartz, President and CEO of FIBA, set up the panel discussion by emphasizing the importance and impact that innovative technologies have on risk assessment and the customer onboarding process.

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AI-Powered Volume and Value Analysis Exposes Shell Companies Involved in Fraud and Corruption

The AI-powered QuantaVerse Automated Volume and Value (V&V) Transaction Analysis solution provides risk managers with better insights into variances in account activity that might indicate risks of financial crimes, or that suggest an account is being used for something other than its stated purpose.  Analysis of this nature is a growing regulatory burden driven by the expectation that FIs understand the risk profile of clients as well as their clients’ clients.

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What Should You Be Looking for in a Packaged AI Solution? (Part 2)

Packaged financial crime solutions are built from the ground up by proven AI experts working alongside experienced AML professionals. Unlike other AI for AML approaches, packaged AI solutions are quick to implement and are continuously updated by the solution provider based on input from multiple customers and regulators.

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CASE STUDY: Reducing AML Risk for a Leading Retail Bank in Europe

Serving almost 20 million customers, the bank was concerned about the risks associated with false negatives that its current AML compliance technology was missing. Intent on driving financial crime out of its operation, the bank began searching for a solution that could enhance its existing rules-based transaction monitoring system (TMS) and minimize the risk related to undiscovered financial crime.

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