To better streamline multi-asset post-trade processing and operational reporting, Broadridge Financial Solutions Inc. (NYSE: BR), a global Fintech leader, today announced it added an GenAI-powered advanced analytics feature to its platform.
A key component of the Broadridge’s OpsGPT ® application, this new GenAI-powered functionality enables users to generate insights and visualizations directly from their trade data using natural language, eliminating the need for data migration.
“Integrating this AI advanced analytics feature into our post-trade platform delivers simplification and innovation, significantly improving risk management and operational efficiency, especially in response to growing regulatory demands,” said Danny Green, head of international post-trade at Broadridge. “The multilingual capabilities and seamless integration provide an accessible solution for broker-dealers and banks, allowing them to quickly access actionable insights without the complexity of traditional reporting tools.”
This new feature, part of Broadridge’s OpsGPT, leverages generative AI and natural language interactions to supply instant reports, data visualization and quickly generated summaries in an intuitive and user-friendly interface. A key benefit of the new feature is its ability to reduce reliance on manual reporting, replacing it with an AI-driven analytics tool that supports multiple languages, including English and Japanese, with plans for Chinese capability in the near future.
The advanced analytics feature is instrumental to international firms navigating evolving regulatory and market dynamics. By streamlining reporting tasks, the tool enables current and prospective post-trade platform users across EMEA and APAC to better manage their operations and maintain compliance, while addressing the challenges posed by faster settlement cycles and compressed margins.
The feature underscores Broadridge’s data and AI strategy and commitment to innovating to enhance user productivity, capabilities and compliance. With faster and deeper data analytics, users can swiftly identify and rectify anomalies, employing predictive analytics to anticipate and mitigate potential bottlenecks.