Bloomberg’s cross-firm chatbot API service can save companies time as they share information. But they are also expensive, and present firms with a fresh dilemma – how to deal with the deluge of data the bots provide them with.
Launched earlier this year, the cross-firm chatbot service allows for firms’ internal information to be shared with counterparties. A two-way API, using natural language processing, provides structured data and context to Instant Bloomberg (IB) chats. This reduces the need for data to be manually replicated between chat streams.
READ MORE: Bloomberg beefs up communications with cross-firm chatbots
To have full access to every chat, costs could reportedly reach US$1 million a year – prohibitively expensive for many firms. Weighing up the benefits of additional data and market colour, alongside efficiency gains, against that price, could be a difficult call.
Those who do opt-in are now looking for the best way to process these resulting swathes of data. They are faced with a familiar buy-versus-build quandary: pay a vendor to process that information for them to use in their operations, or build a mechanism themselves?
Building an AI tool in-house is an expensive job, and one that could end in a net loss if Bloomberg decides to offer a similar service themselves later down the line.
Bloomberg declined to comment on future projects.
It is often said that AI and automation are revolutionising the trading world. But access to such tools is far from democratised.
A secondary impact of the offering is a change in the role of junior traders, who no longer need to conduct repetitive manual tasks copy-pasting data between chat systems. This comes amid widespread cuts to junior banking roles; in early October, JP Morgan’s chief analytics officer Detek Waldron told CNBC that the firm was planning to reduce its ratio of junior bankers to senior managers from 6-1 to 4-1 as its use of AI increases.
Once again, a cost-versus-benefit formula for AI and automation
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