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Financial giant Bloomberg has introduced a new service called Intra-Firm Chatbots to enhance clients’ digital transformation efforts. This service allows Bloomberg Terminal users to incorporate proprietary chatbots into IB chat rooms exclusively for members of the same firm. Intra-firm chatbots assist in surfacing crucial information from internal systems within IB, aiding in-house business intelligence discoverability.
IB Connect, a suite of services, facilitates seamless integration between Bloomberg Terminal and firms’ in-house workflow tools, thereby improving collaboration among colleagues.
The Intra-Firm Chatbots service offers two-way integration, linking a client’s applicable IB chat rooms with their internal systems. It employs natural language processing to organise unstructured IB data and makes the enriched information available to the client’s Intra-Firm Chatbots. Clients can use a provided software development kit to customise these chatbots according to their firm’s tech stack and internal workflow.
Bloomberg offers two types of client chatbot capabilities via IB Connect: Q&A Intra-Firm Chatbots and Notification Intra-Firm Chatbots. Q&A Chatbots enable two-way communication to fetch actionable intelligence from clients’ systems, while Notification Chatbots provide timely alerts and business intelligence within the IB environment without disrupting ongoing team communication.
Back in April, Bloomberg had unveiled BloombergGPT, a specialised LLM tailored for the finance industry. With training based on 700 billion tokens from both Bloomberg’s vast financial data archives and public datasets, this 50-billion parameter model is designed to enhance existing NLP tasks like sentiment analysis, news classification, and query-related tasks in the financial domain.
However, it has limitations, including being monolingual (English only) and potentially carrying biases and toxicity, issues common in LLMs. Unlike its multilingual counterparts like BLOOM and GPT-3, BloombergGPT’s singular language focus could limit its training input diversity.
