The role of investment research in the age of AI - Funds Europe
The role of investment research in the age of AI - Funds Europe
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“Will we still need research analysts in the future?” This is becoming an increasingly common question in our ind
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“Will we still need research analysts in the future?” This is becoming an increasingly common question in our industry.
Financial analysts consistently rank among the occupations most exposed to AI technologies. According to a recent survey by the research company, Focaldata, the finance and insurance industry is ranked second – behind only tech – as the industry achieving the biggest AI productivity
AI is already helping analysts gather information, summarise documents, draft reports and even build components of financial models. If machines can increasingly perform many of these tasks, what happens next?
Research is not just gathering information
There was a time when simply getting reliable issuer information was a competitive advantage. As information ballooned, the job became filtering, summarising and prioritising an ever-growing volume of news, data and commentary. AI is the latest chapter in that technological evolution.
Today, information gathering, spreadsheet population, transcript summarisation and first drafts of research notes can all be significantly accelerated.
But those tasks were never the ultimate purpose of investment research.
Research is about producing insights that lead to better investment decisions. Generating excess returns increasingly depends on interpreting information differently. Technology may alter how information is gathered and processed, but not the need for judgement in capital allocation.
Modelling has become easier
One area where AI is already changing behaviour is financial modelling. For many analysts, building a model from scratch was a rite of passage. Manually entering numbers forced analysts to understand a business, highlighted inconsistencies, revealed key drivers and encouraged deeper investigation. Importantly, it taught analysts which assumptions really mattered.
AI can now automate much of that. The opportunity is to spend the regained time on evaluating future s