Ernst & Young’s 2017 Global Hedge Fund and Investor Survey showed that 78 percent of hedge funds currently use or expect to use alternative, or non-traditional data, in their investment process. That number is up from 52 percent the year before.
In today’s connected world, there is no ignoring alternative data as a gold mine for insights that could give investment firms a competitive edge, especially when used in conjunction with traditional data. Satellite images, social media platforms, online retail sites, smart phone applications, sensors, geolocation and the weather outside (to name a few) all provide vast amounts of data that, while not always quantifiable, can influence investment decision-making.
For investment firms grasping for alpha in the midst of margin pressures, alternative data presents a compelling opportunity. But, despite the growing recognition of its potential value, myriad challenges keep some firms from going all-in on alternative data.
Although the number of alternative data providers is growing fast, most have been in business for only a few years, which makes it difficult to perform due diligence on the data source. Alternative data is unstructured, which makes it difficult to evaluate the quality of the data, not to mention uncover the competitive insights that will justify the cost.
Compounding these challenges are regulatory considerations – privacy, copyright, insider trading and due diligence rules that can take alternative data off the table completely. “Compliance is far and away our largest expense as a company,” said Dan Hess, founder and CEO of independent research provider Merchant Forecast, on a panel at SS&C Deliver. “If you are flirting with the gray areas, it’s a non-starter. Either you’re taking every step to do things the right way, or you’re not.”
The key is leveraging the right tools and expertise to analyze alternative data and find the needle in the haystack. Hiring data scientists or working with third-party data and research firms can help investment firms make sense of alternative data and apply it in a way that benefits their customers. Technological advancements in natural language processing, machine learning, artificial intelligence and deep learning provide unprecedented capability to process tremendous amounts of unstructured data.
Although alternative data is costly and complex up-front, the returns can be worth it. More and more firms are making the case for alternative data and looking for ways to embrace it as part of their research strategy. “Some of these products cost a couple million dollars a year but can save millions per year,” Hess said. “If you can help your customers, that’s an easy case to make. It’s not necessarily a matter of how much it costs but how you are adding value to your customers.”