BST Awards 2019: Best Portfolio Accounting System—Eagle Investment Systems

At the end of the day, a portfolio is only as good as its performance. And the need for a good portfolio accounting platform that can accurately calculate, track and attribute performance, and provide the necessary insight and transparency around that performance, is critical. One provider of just that, Eagle Investment Systems, a subsidiary of BNY Mellon, wins the best portfolio accounting platform category in this year’s BST Awards, thanks to its Eagle Accounting platform, unseating SimCorp, winner of this category in 2017 and 2018.

Eagle’s clients are currently being challenged by increasing regulations and fee pressures while trying to grow their assets under management, shifting investment preferences, and greater demand for transparency from stakeholders, according to Dan Cavanaugh, head of EMEA for BNY Mellon Data and Analytics Solutions. Eagle Accounting, along with BNY Mellon Data and Analytics Solutions, helps firms to maximize their technology investments by supporting their needs across multiple business lines and geographies. At the heart of the platform is an offering that’s scalable and data-centric by design.

“The latest advances in the BNY Mellon Eagle V17 software release reflect a close collaboration with clients to extend our accounting capabilities with an added focus on the insurance and fund accounting capabilities, while also continuing to expand our derivatives coverage,” Cavanaugh explains. He adds that Eagle’s and BNY Mellon’s research and development teams are continuing to develop innovative cloud solutions, which will support increased demand for alternative instruments, derivatives, and more illiquid assets. “In the spirit of efficiency and having one view of their data, it’s important that our clients continue to access these investments on one platform,” Cavanaugh says. “Our clients can better participate and plan for future operational needs, gain more efficiency as needs and demands change, and better predict how to deploy resources.”