The New Reality: Persistent Automation for Fund Management

This is the year for big data. Across industries, firms have unprecedented amounts of both public, and private information sets—from user profiles and consumer habits, to business outputs and proprietary algorithms. But access to data, or information at large, does not guarantee a valuable yield.

Jonathan Shaw, managing editor of Harvard Magazine notes, “The [data] revolution lies in improved statistical and computational methods, not in the exponential growth of storage or even computational capacity.” Data is ubiquitous but not intrinsically valuable – it needs to be smartly processed, not just farmed.

For hedge funds, data processing is the quiet, invisible process that moves through the trade life cycle—accessed from external entities like exchanges and brokers, modified and adjusted in execution, and at times, frozen in snapshots for an increasingly complex group of investors and regulators. More operational credibility and regulatory compliance is required than ever before, with increased scrutiny of the secret buy-side manna that goes along with it.

Smarter data management can be expensive and time-consuming as funds seek to keep up with regulatory, compliance, and transparency requirements while navigating through a sea of market opportunities. Good fund management starts and ends with precise, accurate data management. Truly taking advantage of data, and smarter computational methods, requires not only shedding the skin of outdated models, but categorically understanding a whole new data ecosystem, with new methods of processing, through selective automation and augmented observation. Once that new data ecosystem has been embraced, fund managers can spend their time mastering alpha generation and capital building initiatives.