Waters Rankings 2019: Best Performance Measurement & Attribution System Provider: FactSet

Waters Rankings 2019

Prior to 2019, there were five different winners of this category. But for the first time, there’s a repeat winner: FactSet, which also won in 2017. StatPro, Bisam, S&P Capital IQ, Convergex are the other previous winners. FactSet won thanks to its B-One and Portfolio Analysis (PA) offerings, which arose in response to three industry trends: consolidating workflows, optimizing data sharing between front and middle offices, and client demand for vendors to provide more of a service rather than multiple, independent tools.

“What we see is that the front [office] is demanding more and more precise numbers,” says Sean Murray, director of product strategy at FactSet. “The B-One tool is designed to deliver precision, and the portfolio analysis tool is designed to deliver that precision to the front [office].” He adds that even small blips in the data—as small as mislabeled dates—can be detrimental, particularly in the growing space of passive investment, where returns are already smaller.

The last 12 months have seen a flurry of updates to the tools, namely the two becoming one through the introduction of a unique workflow. Clients need only provide data once. From there, the data runs through the calculation engine, essentially the legacy B-One component, while synchronizing to the PA tool.

Second, Murray says a lot of time was spent on enhancing FactSet’s distribution technology. Some clients asked for a tool that would let them simply view results, he says, rather than power the results process, giving way to the new Portfolio Insights tool, a distribution tool that sends B-One results throughout a firm and directly on front-office desktops, and is packaged within Portfolio Analysis.

Looking ahead, Murray identifies the wealth space as a growth sector for the company. In terms of product development, the company will continue to be centered on attribution, and he predicts a strong emphasis will be placed on building out risk analysis and expanding existing multi-factor models.

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