BNY Mellon Launches Big Data Asset Strategy View Product05.26.2016
PRNewswire– New York — BNY Mellon, a global leader in investment management and investment services, today announced the launch of Asset Strategy View, the first in a new set of ‘big data’ solutions that leverages proprietary aggregated client data to generate market intelligence around institutional investor allocations and behavior. The announcement was made at Invested ’16, BNY Mellon’s Asset Servicing client conference being held in Tucson, Arizona, from May 22-25.
Designed for large multi-strategy money managers, Asset Strategy View delivers various aggregate levels of asset owner allocations and capital flows to provide insight into market trends and investor activity. The new service collects, aggregates, and normalizes data on more than $1.7 trillion in assets, representing about 20% of the investable asset owner market in the U.S. Delivered monthly, information is broken down into 14 major asset classes and 38 detailed sub-asset classes, including data on returns and net cash flows across strategies.
Through Asset Strategy View, fund managers can gain valuable insight into where asset owners are investing and how their strategies are changing. Asset owners can use it to learn what their peers are doing and to more finely explain portfolio over- or under-performance.
“Clients are telling us how vital this information is to supporting their research and product development efforts,” said Frances Barney, CFA, head of Consulting-Americas for Global Risk Solutions at BNY Mellon. “To our knowledge, no other institutional peer group data sets deliver Asset Strategy View’s level of detail, frequency and data quality. We believe it’s a game-changer for asset managers and owners alike.”
Extending the reach of Asset Strategy View, BNY Mellon also has announced new Asset Allocation Trust Universes. Available to users of the BNY Mellon U.S. Master Trust Universe, plan sponsors will be able to use the newly expanded data to identify typical allocations for plans of similar size as well as asset allocation trends over time. Improved graphical reporting features allow users to compare portfolio results against those of BNY Mellon Global Risk Solutions’ large institutional client base.
“Both new offerings are part of our over-arching data management strategy to roll out additional solutions across the trade lifecycle. It’s not just about big data, it’s about smart data our clients can use to their advantage,” Barney added.
With $12.3 trillion in assets under measurement, Global Risk Solutions provides risk analysis, performance measurement, attribution and investment analytics services to more than 1,000 institutional investors in 30 countries. BNY Mellon’s Asset Servicing business supports institutional investors in today’s fast-evolving markets, safeguarding assets and enhancing the management and administration of client investments through services that process, monitor and measure data from around the world. We leverage our global footprint and local expertise to deliver insight and solutions across every stage of the investment lifecycle.
BNY Mellon is a global investments company dedicated to helping its clients manage and service their financial assets throughout the investment lifecycle. Whether providing financial services for institutions, corporations or individual investors, BNY Mellon delivers informed investment management and investment services in 35 countries and more than 100 markets. As of March 31, 2016, BNY Mellon had $29.1 trillion in assets under custody and/or administration, and $1.6 trillion in assets under management. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments. BNY Mellon is the corporate brand of The Bank of New York Mellon Corporation (NYSE: BK). Learn more atwww.bnymellon.com. Follow us on Twitter @BNYMellon or visit our newsroom at www.bnymellon.com/newsroom for the latest company news.
Information containing any historical information, data or analysis should not be taken as an indication or guarantee of any future performance, analysis, forecast or prediction. Past performance does not guarantee future results. The Information should not be relied on and is not a substitute for the skill, judgment and experience of the user, its management, employees, advisors and/or clients when making investment and other business decisions. None of the Information constitutes an offer to sell (or a solicitation of an offer to buy), any security, financial product or other investment vehicle or any trading strategy.
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