Trade surveillance requires rigorous management of risks emanating from alerts. A manually intensive activity is time-consuming and error-prone. To increase efficacy and reduce risk of noncompliance, the solution automated research, summarizing the findings and posting closure notes in the compliance system.
The Challenge
Manual trade surveillance alert workflow
The client's trade surveillance system generates alerts based on the internal rule engine. These alerts are worked upon by risk analysts who must perform a thorough manual research on the generated alerts and put closure notes to close them.
The Objective
Enhancing surveillance analysis efficiency and resolution accuracy
- Reduce the time it takes to analyze the surveillance findings
- Increase the accuracy and consistency of the resolutions captured in the system
The Solution
HCLTech's rule-based prioritization engine and Generative AI capabilities enhance trade surveillance analyst workflow
HCLTech built a rule-based Prioritization Engine to prioritize the generated alerts and Generative AI capabilities to assist Trade Surveillance Analysts in the closure of alerts across multiple touchpoints (like noise reduction on comms data, news summarization and generation of closure notes).
The Impact
The adoption of an AI-assisted trade surveillance solution marked a paradigm shift in client's compliance workflow
- A significant dip in the time analysts needed to investigate and understand each alert
- An enriched level of precision and uniformity in the resolution descriptions entered into their system
- Enhanced ability to address the roots of compliance infractions due to more structured and insightful resolutions
