Digital transformation has brought huge efficiency gains to workflows all along the trade lifecycle. One critical part of the chain of actions that has been ripe for improvement, however, is now benefiting from Bloomberg’s enhanced application of artificial intelligence.
Natural Language Processing (NLP) technology embedded into the Instant Bloomberg (IB) messaging service is automating the real-time recognition and deployment of actionable insights contained in messages that enter trading professionals’ inboxes. This is enabling them to work with more counterparts, increase business generation, further streamline their workflows and reduce operational risks.
Making communication more effective
Financial professionals are in constant communication with their counterparts and colleagues as they navigate markets every day.
Much of this business is high-touch, involving many conversations across chat rooms. Further, the technology that financial professionals use is often very fragmented with proprietary tech stack applications to manage everything from order and execution workflows to post-trade analysis, research, and settlement processes.
It is not an effective way of communicating, especially when firms are trying to do more and cover more as markets are becoming more interconnected in today’s age of macro-economic drivers. The challenge this setup creates in the flow of information from conversations to trading applications and execution may increase operational errors and missed opportunities.
Automating these processes has been difficult, however. Much of the flow of information in these communications is conversational and unstructured. Making this information readable by machines has largely eluded firms, until now. NLP has made it possible to identify content, such as the security size, side of the market and intent related to an inquiry, within chat room text that can be digitized for use within users’ internal systems and applications.
NLP technology is now available to IB users, helping them extract nuggets of useful and actionable information from the stream of chats that go across its network every day. These kernels of intel are converted into a data format that firms can use to streamline their workflows, gain business insights and reduce operational error.
Identifying information in real time
Since its inception 20 years ago, IB chats have evolved to carry communications about everything from trading workflows and requests for quotes (RFQs) to pricing and research that helps inform trades in bonds, loans, foreign exchange, derivatives, and other OTC-traded securities.
Until now, actioning information contained in chat text has been the manual task of individual users who are copy-and-pasting, switching applications manually and looking for conversation excerpts from many open chatrooms before they enter that content into their proprietary systems like pricing engines, trade analytics, and other applications.
With the application of NLP, however, IB can do this automatically, far more effectively, and far quicker. The model is applied across a user’s chatrooms to identify information that it can digitize, send it to the user’s internal applications, then enrich it with context and metadata that will help progress the conversation or even trigger other automated tasks.
For instance, when a counterparty asks for a price on a specific security, NLP-enhanced IB Connect solutions can instantly recognize that as a request and capture the characteristics of that security, the buy-side comments and any other associated information. IB will send that information to the appropriate application, in this case a pricing engine, which can then provide insights to give context to any response sent back to the counterparty.
All of this happens in real time, prompting immediate responses that can be actioned in two ways. Outputs can be directed to fast API solutions that connect into firms’ proprietary systems, enabling them to complete their workflows within their own environment. Additionally, the information gathered through NLP is routed into the Bloomberg Terminal, where it will be used to streamline and support a multiplicity of workflows, including price discovery and trade negotiations, post-trade analysis and settlement functions.
Open channels for informed conversations
This process considerably reduces the time it takes for professionals to find business opportunities within their IB conversations, which for many can comprise hundreds of permanently open chatrooms, all alerting users to new messages by the moment. It also reduces the risk that users will miss critical inquiries and may reduce operational error when handling responses to various chatroom inquiries.
Using the latest IB Connect solutions, firms can also send content to their own traders so that they can use it to better inform their conversations with trading counterparties. This staging or “idea drawer” concept provides a powerful to-do list that helps sell-side traders become more effective in their dealings with the buy side.
One other addition to IB Connect solutions that will further empower users is the creation of IB chatbots, which will be on hand to offer users contextual information from their own applications and deliver it directly to chat environments. This further reduces the need to switch between applications, cuts out a lot of repetitive tasks, and, crucially, enables individuals to instantly access data and information that will inform the conversations they are having with their clients.
Further, with Bloomberg’s continual investment in IB functionality, firms can benefit from the integration of new technologies into its messaging tool.
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