On March 6, 2018, S&P Global announced it would acquire Kensho Technologies, an artificial intelligence and analytics company, for approximately $550 million net of cash acquired, in a mix of cash and stock. Kensho had built machine-learning, natural-language-processing, and data-visualization tools used across Wall Street and by parts of the US national security community, and its systems were designed to answer financial questions and surface patterns in large, messy datasets.
The press release positioned the deal as a way for S&P Global to strengthen its core capabilities in AI, natural language processing, and data analytics, embedding Kensho’s technology across its market intelligence, ratings, and indices businesses. At the time it was widely reported as one of the largest acquisitions of an AI company by a financial firm.
Kensho continued to operate as S&P Global’s innovation hub, and several of its tools - including entity linking and document-extraction systems for financial text - were folded into S&P’s products. The acquisition is a marker of the moment when established financial-data incumbents began buying AI capability rather than building it slowly in-house.
Why business readers should care: the Kensho deal illustrates the “buy not build” path that large financial-data companies took into AI. Owning the data was no longer enough; the value increasingly sat in the models that could read, link, and reason over that data at scale.