Enterprise Supervision Capability Leverages Artificial Intelligence to Reduce Email Review Workload by 20%
Smarsh, enabling organizations to manage the risk and uncover the value within their electronic communications, introduced Echo Cancellation capabilities within its Enterprise Supervision application. In its pilot program with a global asset management customer, Echo Cancellation resulted in a 20% reduction in email messages requiring review, with 100% classification precision.
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“Echo Cancellation helps reduce supervision costs and improve reviewer productivity by applying artificial intelligence to the supervision system. This enables smarter, more accurate reviews of email content”
FINRA Rule 3110 requires broker-dealers to supervise all electronic communications content generated by their employees. A common problem in supervision involves repeated policy violations triggered by email messages that contain the previous thread appended to message replies or forwards. This results in large volumes of irrelevant alerts. Review teams are then required to sift through an enormous number of false-positive results to get to the relevant content that merits scrutiny.
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The intelligent Echo Cancellation algorithm identifies, classifies and subordinates redundant email replies and forwards (“echoes”) in supervision review queues. This saves time and creates efficiency for supervision review teams.
“Echo Cancellation helps reduce supervision costs and improve reviewer productivity by applying artificial intelligence to the supervision system. This enables smarter, more accurate reviews of email content,” said Santosh Shanhbag, Vice President, Product Management at Smarsh. “This advance frees up time and effort for supervision reviewers. It allows them to focus on the most important content within their archive that poses real risk to their organizations.”
Echo Cancelation provides full transparency to Enterprise Supervision users, maintaining a record of all content suppressed from duplicative review. Echoes are easily auditable with no ambiguity and can be “re-opened” at any point in time. Such remediation is useful when there is a reason to re-populate a message in the supervision queue and complete the review workflow.
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