Unlock investment potential with firms' internal data

For decades, top asset managers maintained an edge thanks to exclusive insights beyond traditional sources like stock exchanges. Now, this advantage is within their own organisations.

Hedge funds and others have improved their ability to predict financial results and commodity trends using what’s known as alternative data – derived from combined credit-card transactions, phone-tracked retail foot traffic, and satellite imagery of agricultural fields.

Eventually, as such data became standard across the asset management sector, they turned into basics rather than standout factors. 

As a result, asset managers redirected resources to unearth new, lesser-known data sources that could give them an advantage over competitors.

With the advent of large language models, this gap has closed even more. Top investment companies are utilising AI to gather all available public data, with experts suggesting the next big competitive advantage will emerge from examining their own research, communications, and past decisions for insights competitors can't reach.

AI excels in "organising unstructured data," said Jacob Bowers, a vice president of quantitative research at BlackRock, during the Future Alpha conference in New York on Tuesday, noting that "some of the most valuable unstructured data comes from within."

The once cutting-edge publicly accessible data has now been "commoditized" by AI, Bowers pointed out. 

BlackRock, the largest asset manager globally with $14 trillion in assets, has already focused its internal agents to identify potential investment indicators in communications among investment professionals and archived opportunity reports, he added.

There’s a significant reserve of data in long-standing asset managers. A 2019 report from the consultancy Opimas anticipated funds would eventually monetise their data for additional revenue, and Robert Frey, a former managing director at Renaissance Technologies now running a fund of funds, mentioned to Business Insider that his former company’s greatest advantage was its extensive data library, built over years of trading.

AI has increasingly simplified the process for funds to unlock this source of advantage.

Andrew Gelfand, a quantitative specialist at Balyasny focused on identifying investment potentials, stated at the Future Alpha conference that the company had earlier attempted to leverage unstructured data within its infrastructure, but recent AI advancements made the endeavor much more rewarding.

The $33 billion firm mandates analysts to input their research and observations into a system accessible by his team, providing AI with extensive text to analyse for investment signals.