This week I have a special five-part podcast series, sponsored by Verint on the Future of Communication in Financial Compliance on the Innovation in Compliance podcast series on the Compliance Podcast Network. My guest in this series is Phil Fry, VP and GTM of Financial Compliance Strategy at Verint. Over this series, we will take a deep dive into the current status of communications in financial institutions; how to be or not be compliant; an analysis and insight into the area; and how to avoid accentuating the negative and the human element in compliance. In this third post, we consider the topic of improving surveillance systems through data analysis and risk management.
We highlighted the challenges faced by surveillance teams in managing large amounts of data and identifying relevant information. It also emphasized the importance of proactive decision-making and efficient risk response in the face of ever-expanding regulations. One of the key issues discussed in the episode was the overwhelming amount of data that surveillance teams have to deal with. Fry mentioned that surveillance teams often find themselves looking for needles in haystacks, trying to find the data they need among thousands or even tens of thousands of calls in a day. To address this challenge, early analytics and risk analysis can be employed to provide proactive and smarter decision-making processes. By analyzing captured data, surveillance teams can focus on conversations that raise red flags or are deemed high risk, rather than being overwhelmed by the sheer volume of data.
To enhance surveillance systems, Fry suggested implementing “pre-surveillance surveillance” and adding additional metadata points. This includes considering factors such as geography, time, and the technology used during communication. By capturing this additional information, surveillance teams can gain a comprehensive view of spoken interactions, enabling them to respond to incidents and risks more quickly and efficiently. This approach also aligns with the need for compliance with regulations, as non-compliance consequences can be severe, including hefty fines and even imprisonment.
The episode also highlighted the value of insights derived from spoken interactions. Fry emphasized that conversations are a gold mine of information, and with the right transcription and analytic capabilities, valuable intelligence can be extracted. By combining speech and conduct insights into the core capture, compliance officers can have a single pane of glass view of all spoken interactions within their organizations. This includes detecting changes in sentiment, and language switches, and gaining an overview of conversation topics. The solution discussed in the episode has been trained for the financial domain, making it easier for surveillance teams to perform audio reviews and detect possible compliance breaches.
Furthermore, the episode touched upon the wide range of corporate disciplines that can benefit from this data. It is not just limited to compliance and audit teams but can also provide insights into functions such as Chief Financial Officers, strategic risk compliance, and operations. The data collected can be used to gain insights into how solutions are working and aid decision-making processes across various departments.
In conclusion, improving surveillance systems through data analysis and risk management is crucial in today’s regulatory landscape. The challenges of managing large amounts of data and identifying relevant information can be addressed through early analytics and risk analysis. By implementing “pre-surveillance surveillance” and capturing additional metadata points, surveillance teams can gain a comprehensive view of spoken interactions and respond to incidents and risks more efficiently. The insights derived from these interactions can be valuable to a wide range of corporate disciplines, making it a valuable asset for organizations. Continuous monitoring and improvement of surveillance systems are essential to ensure compliance and mitigate risks effectively.
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