Sell-Side Technology Awards 2023: Best sell-side analytics product—Bloomberg

Overview

Trading desks are tasked with growing revenues by either executing more transactions or by capturing more margin per transaction―ideally both. The way for them to achieve this objective is to use data and analytics to their advantage. Technology that automates repetitive decisions can free traders to focus on more time-consuming trades and complex relationships. Collecting data to build analytics also solves a problem for the head of desk, who needs to track return on investment on decisions.

The solution

Bloomberg’s Sell Side Analytics solution provides decision analytics for pre-trade, in-trade and post-trade data to help desks make more informed decisions. These are delivered through applications and API-based services. Bloomberg provides data transparency and analytic explainability through dashboards. The analytics are then integrated into trading apps, such as an RFQ pop-up window to ensure traders have the right information to make quick, informed trading decisions. Finally, the analytics can be used by automation engines to scale workflows.

Secret sauce

The differentiation of the Bloomberg sell-side enterprise analytics offering is two-fold:

• The analytics are built on top of a dataset that stitches together market data, securities data, pricing and desk-specific trading flow, which provides a wide base to build event-driven analytics and more advanced predictive analytics via machine learning techniques.
• The analytics are seamlessly integrated across workflow applications and automation engines, which provides a rich user experience at scale.

Recent enhancements

Real-time chat feeds now include conversational metrics generated from NLP trading models. Analytics based on the content, frequency and duration of a conversation allow desk managers to track client service metrics and salesperson engagement.

A recently released AI solution helps sell-side desks better understand liquidity that is unique to each trading desk, based on desk relationships with counterparties and what those counterparties’ trading interests are.

Future objectives

Bloomberg continues to invest in machine learning to deliver analytics to trading desks as a means of improving the price discovery process and time it takes traders to respond to RFQs. It is currently enhancing its quoting engine to incorporate client-specific factors such as historical hit/miss ratios, or profitability. This will allow banks to automatically tailor their quotes to a given counterparty, allowing them to better service individual clients.

Why they won

Over the last three years, one category across these awards and the annual Buy-Side Technology Awards has attracted by far the most entries: best analytics product. This is the most competitive and difficult category to win bar none, and yet it’ll come as no surprise to industry practitioners that Bloomberg has emerged top this year, thanks to its outstanding Sell Side Analytics offering, designed to support firms’ pre-trade, in-trade and post-trade analysis, and by so doing helping them to make the most judicious trading-related decisions.