TECHNOLOGY STRATEGY
“ Whereas, when you search for company documents, type matters: a 10K, a company presentation – these provide complementary sources of information. Also, across these and other document types, perspective matters.“ Our clients want to separate the perspective of the company from those of analysts who may be covering the company and news coverage. With a multicomponent agentic system, each type of data can be handled as it should and combined in the ways the user needs.”
While the tech world often obsesses over speed, Amanda insists that, in finance, being right is better than being fast – though ASKB manages to achieve both.
“ With ASKB, Bloomberg is focused more on accuracy than speed – something our clients seem to appreciate, regardless of whether they’ re an equity analyst, portfolio manager, or credit analyst,” Amanda says.
“ That being said, it certainly does speed up users’ financial analysis and investment management workflows and how they discover insights on the Bloomberg Terminal.
“ ASKB is made up of multiple AI models to help get answers to your questions. In response to your queries, ASKB calls and orchestrates different AI agents and tools that our team has built to discover and distill information and content from across the Bloomberg Terminal.
“ These different individual agents and tools can access Bloomberg’ s comprehensive and high-quality library of more than 400 million documents... Different AI agents perform a variety of tasks in parallel, including discovering information, synthesising data and running calculations.”
The goal is to eliminate the swivelchair effect, where analysts spend hours jumping between applications to manually synthesise research.
By providing contextually accurate, timely answers – down to the exact page and paragraph of the source document – Bloomberg is turning the AI into a bridge between a question and a fully-formed investment thesis.
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