Arthur, welcome to Fintec Buzz. To start, could you please share a bit about your professional journey and what led you to become the Vice President of Financial Crime at WorkFusion?

Thank you! Before joining WorkFusion in 2022, I spent more than 20 years in anti-financial crime programs across financial institutions, tackling the same complex banking problems our customers face today: sanctions, anti-money laundering (AML), fraud, and Know Your Customer (KYC). My professional journey includes American Express, UBS, Commerzbank, and Rabobank. Combined with my legal and compliance experience as a practicing attorney, you could say that I have been readying myself for WorkFusion for years! I joined WorkFusion because I saw it as a game changer for the anti-financial crime industry, with pre-packaged AI Assistant Digital Workers that could complete many of the rote, mundane, repetitive tasks as well as help tackle the false positive problem.

Banks face numerous challenges with AML and Sanctions regulatory compliance. From your perspective, what are the biggest obstacles financial institutions encounter in this area?

The three biggest challenges with AML and Sanctions regulatory compliance are evolving regulations, risk mitigation, and staff management. Banks and financial institutions have struggled with the same challenges for decades. The combination of manual work, large numbers of false positives, and limited capacity combined with increasing volumes creates a vicious cycle. The shortage of full-time analyst staff, whether due to hiring freezes or the general lack of L1 analyst availability, results in FinCrime compliance teams becoming massively overwhelmed, which can lead to burnout among existing staff and difficulties maintaining effective and efficient compliance operations.

Additionally, the sheer volume of alerts that needs to be reviewed, dispositioned and investigated for AML and Sanctions compliance is enormous. And 99% of these alerts are false positives. This leads to inefficiencies as compliance teams spend considerable resources, time, and effort reviewing alerts that ultimately do not represent genuine risks, diverting attention from higher risk and more critical investigations.

Can you explain what AI Digital Workers are and how they function within the context of financial institutions?

WorkFusion’s AI Digital Workers are AI AML and Sanctions analysts that come out of the box with up to five years of experience in a specific job role. They are technology controls that mitigate risk and can integrate into financial institutions seamlessly, increasing their compliance team’s capacity. Think of WorkFusion’s AI Digital Workers as employees that have infinite capacity to automate alert reviews and document-heavy, tedious, and error-prone work.
We launched our AI Digital Workers in 2022, after in-depth conversations with how our customers were using our machine learning and automation. We learned that many had given the technology a human name and interacted with it like it was an employee. That was the beginning of packaging the technology up as personified AI solutions – they each have a human name, a human persona, and were trained to do a specific job in AML and Sanctions compliance. We have Evelyn, who does adverse media monitoring and sanctions/PEP screening alert review; Tara, who is a transaction screening analyst; Isaac, who is a transaction monitoring investigator, and many more focused on KYC and pKYC.

Our AI Digital Workers improve the quality and consistency of the work being done, help mitigate risk, improve operational effectiveness and efficiency, and help ensure a positive customer experience. They are also easier and faster to onboard than a traditional employee or outsourcing the work. They improve compliance with detailed narratives and complete audit trails. They also make work easier for analysts by taking on the document-heavy, tedious busy work that is typically done by Level 1 analysts. It turns the analyst from hunter-gatherers to true risk analysts. This helps reduce employee burnout and improve job satisfaction. For example, we have even seen U.S. Department of the Treasury Office of Foreign Assets Control (OFAC) officers doing the work of L1 analysts because they were so short staffed. An OFAC officer shouldn’t be dispositioning sanctions alerts, especially when there is technology that can alleviate that burden.

How are AI Digital Workers helping financial institutions meet compliance with regulatory bodies such as the BSA, AMLA, OFAC, FinCEN, OCC, and FDIC?

There is already a collective push toward integrating technologies to augment, liberate, and improve human intervention and judgment, which will enhance operational effectiveness and efficiency, while reducing errors. Government agencies, regulatory bodies, and financial crime oversight organizations, including the Financial Crimes Enforcement Network (FinCEN), with its AML Act of 2020 and Innovation Initiative, explicitly advocate for innovative approaches to address various challenges to mitigate financial crime and AML and Sanctions compliance risks.

An enormous amount of manual work and false positives exist within financial crime programs — onboarding, periodic reviews, risk assessments, transaction monitoring, sanctions alerts, and quality control — making it time-consuming and error-prone. For example, with manual operations, a transaction may get delayed for hours due to similarities of one on the OFAC sanctions watchlists. Consider this: Level 1 analysts can typically work 200-300 sanctions alerts per day. Yet when sanctions alert volumes spike, financial institutions can face up to 500-800 daily sanction alerts. This becomes not only overwhelming but impossible without automation.

AML and Sanctions compliance can be significantly eased through automation, reducing the amount of time-consuming and tedious tasks worked by human staff and allowing analysts to concentrate on genuine risks.

Addressing AML risks is a critical task for financial institutions. How do AI Digital Workers contribute to mitigating these risks effectively?

WorkFusion’s AI Digital Workers significantly enhance the ability of financial institutions to mitigate AML and Sanctions compliance risks by automating repetitive and data-intensive tasks traditionally performed by human analysts. These AI AML and Sanctions analysts are technology controls that organizations can use in their risk mitigation toolkit. By automating these job roles, there is increased consistency and quality of reviews, material and immaterial errors are reduced, alert surges have nearly zero impact, they avoid missed escalations and missed true positives, and avoid delays leading to poor customer experience. Ultimately, AI Digital Workers improve overall risk management and operational effectiveness and efficiency by freeing up human analysts to focus on high-risk areas.

In your opinion, why is it essential for financial institutions to innovate their AML and Sanctions compliance programs continuously to mitigate risk?

Continuous innovation in FinCrime compliance programs is essential for financial institutions to effectively mitigate risk because the landscape of financial crime is constantly evolving. As illicit activities become more sophisticated, so must the tools and strategies used to combat them. Traditional manual processes are inefficient and increasingly inadequate in addressing the complexities of modern financial crimes. Innovating with AI and machine learning allows organizations to keep pace with the rapid changes in transaction patterns and regulatory requirements and expectations, ensuring they can detect and respond to threats more swiftly and accurately. Additionally, regulatory bodies such as FinCEN and the Office of Foreign Assets Control (FCA) advocate for innovative approaches, underscoring the importance of leveraging technology to enhance compliance efforts and reduce the risk of non-compliance and associated penalties.

There is often caution among financial institutions when it comes to implementing AI. What are the primary concerns, and how can these institutions overcome them?

The primary concerns around implementing AI are data privacy, model risk management, and security issues, the potential for bias in AI algorithms, the complexity of integrating AI with existing legacy systems, and regulatory compliance. To overcome these concerns, we recommend that institutions take small steps. Ensuring robust data governance and security measures can address privacy and security issues. Implementing transparent and explainable AI models can help mitigate biases and increase trust in AI-driven decisions. Ensure you follow internal governance when planning, implementing, and deploying any AI use case. Follow your model risk management framework and testing protocols, and put analytics, monitoring, and guardrails in place to ensure the AI solution is working as intended and within acceptable parameters. Partnering with experienced AI solution providers can facilitate smoother integration with legacy systems and ensure compliance with regulatory standards.

Leveraging the benefits of Generative AI without adding risks is a delicate balance. How can financial institutions achieve this balance effectively?

Generative AI and the LLMs that support it have absorbed the mindshare of the AI market. To best achieve its promised value — particularly in financial services — organizations need to not only seek the benefits but mitigate the risk. To do this, they need to look to processes that combine the best of LLMs and complement them with traditional AI and human-in-the loop.

To go deeper, financial institutions can achieve a balance in leveraging Generative AI by implementing comprehensive risk management strategies encompassing both the technological and operational aspects of AI deployment. This includes developing clear policies and guidelines for AI usage and ensuring that all AI-generated outputs are subject to human review and validation to prevent errors and biases. Employing robust data governance frameworks will help maintain data integrity and security. Regular staff training and upskilling on AI tools and their implications can foster a better understanding and more effective use of these technologies.

Adopting a phased approach to AI implementation, starting with low-risk areas and gradually expanding to more critical functions, can help institutions mitigate risks while realizing the benefits of AI.

Could you share your personal strategy when it comes to staying ahead of trends and changes in the AML and Sanctions compliance landscape?

Staying well-informed and prepared will help you keep up with trends and changes in the AML and Sanctions compliance landscape. My strategy involves continuous learning and engagement with customers, other industry experts, and regulatory bodies. I regularly participate in industry conferences, webinars, and training sessions to stay informed about the latest regulatory changes and technological advancements. I also engage with professional networks and forums to exchange insights with peers and experts. Paying close attention to publications from regulatory bodies such as FinCEN, OFAC, and the Office of the Comptroller of the Currency (OCC) helps me understand emerging expectations and compliance requirements. Additionally, I invest time in to understand the latest advancements in AI and machine learning, as these technologies are pivotal in shaping the future of AML and Sanctions compliance.

Finally, what advice would you give to professionals in the financial industry who are looking to enhance their AML and Sanctions compliance programs with AI technology?

For professionals seeking to enhance their AML and Sanctions compliance programs with AI technology, my primary advice is to start with a clear understanding of your specific challenges and objectives. Identify the area where AI can have the most significant impact, such as automating repetitive task, aggregating data or documents, or reducing false positives needed to be adjudicated. It is crucial to partner with experienced AI solution providers who understand the unique requirements of the financial industry. Focus on integrating scalable AI solutions that deploy quickly with minimal customization.

Training and upskilling staff to work alongside AI tools are also essential to maximize the benefits and ensure a smooth transition. Maintain robust data governance and ensure transparency in AI decision-making processes to help build trust and compliance with regulatory standards. Continuously monitor and evaluate the performance of AI systems to adapt to any regulatory environment changes and improve their effectiveness over time. By following these steps, financial institutions can leverage AI to significantly enhance their AML and Sanctions Compliance programs.

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