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Reimagining Financial Crime Investigations Management with Technology at ACAMS Las Vegas

At this year’s ACAMS Virtual Las Vegas, @Nasdaq was joined by the Wolfsberg Group's former Co-Chair John Cusack to discuss the pressing need for banks to transform their financial crime investigations. Check out some of the key takeaways from the session.

At this year’s ACAMS Virtual Las Vegas, Nasdaq was joined by John Cusack, Editor in Chief of the Financial Crime News and former Co-Chair of the Wolfsberg Group, to discuss the pressing need for banks to transform their financial crime investigations. Managing financial crime has been a long-standing challenge for banks, who spend over $30 billion annually in fighting against financial crime. Still, less than 1% of all suspicious activity detected by banks’ monitoring systems yields information that can be used by a regulator or law enforcement agency to prosecute money laundering.

Below are some of the key takeaways from the session:

1. Effectively managing financial crime investigations is a global banking challenge

The biggest cost driver in transaction monitoring is the financial crime investigations process.

On average, the cost to produce a Suspicious Activity Report (SAR) can be upwards of $13,000. When holistically looking at how these reports are leveraged by regulators and law enforcement and the number of cases that are actually prosecuted, the return on these investments is limited. As an industry, firms must work to reduce this gap and drive additional measures to promote integrity within the financial markets ecosystem. 

It is Nasdaq’s mission to help promote integrity within financial markets – whether via surveillance, compliance or risk technology. We recently expanded our coverage into the AML investigations space, with the launch of Nasdaq Automated Investigator for AML. We are very excited about the potential to help banks gain operational efficiency and effectiveness in the fight against financial crime.

2. Automating financial crime investigations can significantly improve efficiency, enabling firms to hone in on more potential cases of nefarious activity

By applying a standardized and automated approach to AML investigations, firms can make more accurate and higher quality risk decisions at a lower cost. An automated approach can improve speed, consistency and quality of investigations – allowing human analysts to spend more time identifying real financial crime. Key benefits discussed included: 

Efficiency: Level 1 alert investigations can take an analyst between 30 to 70 minutes to complete. Automated investigation takes seconds, freeing up time for human analysts to focus on more complex cases.

Consistency: Large teams of highly skilled analysts are required to investigate, document and report any potential findings. With investigations spread across such a large number of human analysts, potential inconsistencies can arise. An automated approach to investigations can reduce regulatory risk with standardized decisions and auditable reports, which document the explanation process for every investigation. The transparency this brings is an important attribute for regulators.

Operational Performance: Implementing a uniform and automated approach to AML investigations can enable firms to better scale their investigations processes and reduce costs.

3. Looking forward: Human teams will play a critical role in the success of technology

Automation has moved up the cognitive value chain. The pace of innovation means that this will be the norm in financial crime investigations within the next 24 months. The convergence of financial crime investigations across silos is also likely to accelerate and result in a more holistic view of the behavior and entity in question.

Investigators must work alongside technology to improve the efficiency of Level 1 and Level 2 investigations and to refine risk tolerances and quality assurance processes. Investigation teams are also moving up the cognitive value chain with rapid domain knowledge and critical thinking skills needed to augment machine intelligence and focus on more complex investigations.

The ability to develop a feedback loop between human analysts and machine intelligence-driven technology will be vital to ensure ongoing management checks and validation. Data will become critical to supporting advances in federated learning and machine learning that will allow training on anonymized data, accelerate banks’ ability to utilize third-party or internal innovations and drive best practice investigative processes across the market.

To find out more about what was discussed, view a recording of the full session on-demand by filling out the form below. If you have any questions, please contact Darren Innes, Head of AML Technology at Nasdaq.

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Darren Innes


With more than 20 years of experience in RegTech focused on AML, KYC and regulatory data, Darren Innes leads Nasdaq’s expansion of its globally-recognized trade surveillance into complementary areas.

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