State Street introduces machine learning tool

State Street has launched a machine learning solution to help investment professionals wade through the plethora of research reports they receive on a daily basis.

Through the combination of machine learning and human expertise, the new Quantextual Idea Lab uses machine learning algorithms to combat the information overload. It consumes research reports, classifying them by investment themes and assets, and suggests new, relevant materials based on the user's specific needs, preferences and previously read materials.

The automated solution then overlays the experience, knowledge and conclusions of Quantextual's own research team to improve the algorithms' ongoing performance and accuracy. Users can also then annotate research reports and share them with colleagues.

"Today, the speed, sophistication and volume of information far outpaces our ability to consume it. Efficient intake of research is essential for identifying investment opportunities and managing risk. With limited time investors may overlook or delete important research insights. Those who can make sense of large amounts of information quickly will front run peers," State Street Global Exchange head of Quantextual Research, Stephen Lawrence said.

Lawrence said Quantextual enables the transformation of curated ideas into decisive and strategic action to the benefit of investors.

"As more investment firms shift to a model of covering research costs out of their own P&L's, an additional benefit of Quantextual is that it allows them to systematically review research consumption, to help them optimize their research spend," he said.

Read more: investmentmachine learningState StreetP&LQuantextual ResearchState Street Global ExchangeStephen Lawrence
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