Bloomberg adds AI coding assistant to BQuant to accelerate financial Data Analysis. 2 November 2026 Bloomberg has introduced BQuant Assistant, a conversational AI coding tool integrated into its BQuant analytics platform, enabling financial professionals to use natural-language instructions to develop investment strategies, query financial datasets and build analytical applications without requiring extensive programming expertise. Available through BQuant Desktop and BQuant Enterprise, the assistant operates within the platform's existing Python development environment, supporting users across investment research, quantitative analysis and portfolio management. It can generate and debug Python code, construct queries using Bloomberg Query Language (BQL) and PyBQL, and create data visualisations using open-source libraries including Plotly and Jupyter Widgets. The new functionality provides access to Bloomberg data spanning more than 22,000 fields across equities, fixed income, foreign exchange, commodities, derivatives and other asset classes. These include pricing, fundamentals, valuations, risk metrics, estimates and economic indicators. Unlike general-purpose coding assistants, BQuant Assistant draws on Bloomberg's own documentation, example notebooks and technical libraries to provide responses informed by the platform's analytical workflows. Users can also ask the assistant to explain existing code or suggest modifications to ongoing projects. The assistant can insert and execute code directly within an active BQuant notebook, although users must approve proposed actions before the system reads from or writes to their projects. Execution takes place within BQuant's secure sandbox environment. "Financial professionals are working with increasingly large and complex datasets, but turning an investment idea into a repeatable analysis can still require significant time and specialized coding knowledge," says Shawn Edwards, Bloomberg's Chief Technology Officer. Extending BQuant's Analytical Capabilities BQuant has evolved into an established environment for combining Bloomberg's financial information with proprietary datasets and open-source analytical tools. The platform was named the Best AI Solution for Historical Data Analysis in A-Team's AI in Capital Markets Awards 2025, recognising its capabilities for handling large-scale financial datasets and supporting quantitative research. Its development has included Bloomberg's collaboration with Man Group to integrate ArcticDB, the Python-native database designed for high-volume time-series analysis. The latest enhancement also complements Bloomberg's broader efforts to make financial data accessible through AI-driven workflows. These include ASKB, its conversational interface for the Bloomberg Terminal, and Bloomberg Enterprise Model Context Protocol (MCP), which provides AI agents with governed access to licensed market data. As Tony McManus, Global Head of Enterprise Data and Indices at Bloomberg, recently discussed with Market & Alt Data Insight, Bloomberg's Enterprise MCP initiative emphasises the importance of metadata, semantic context and entitlements in supporting reliable institutional AI applications. BQuant Assistant extends this approach into the analytical development process, potentially broadening participation in quantitative research while allowing experienced developers to automate routine coding tasks. Bloomberg announced general availability for BQuant Enterprise and a limited beta release for BQuant Desktop at the end of October 2026.

Bloomberg introduces BQuant Assistant to help financial professionals accelerate data analysis and coding workflows. Oct 28, 2026, 07:00 ET Domain-grounded conversational AI coding assistant added to BQuant Desktop & BQuant Enterprise NEW YORK, Oct. 28, 2026 /PRNewswire/ - Bloomberg today introduced BQuant Assistant, a domain-grounded conversational AI coding assistant built into BQuant Desktop and BQuant Enterprise. Integrated within the BQuant development environment, BQuant Assistant gives financial professionals who are Bloomberg Terminal subscribers the ability to use natural-language prompts to write code, build dynamic applications, and accelerate financial data analysis workflows. BQuant Assistant brings conversational AI directly into the same Python environment where users build investment strategies, dashboards, and quantitative financial analyses. BQuant Assistant can answer customers' questions about BQuant, generate Python code, assist with querying Bloomberg's vast datasets via Bloomberg Query Language (BQL), help users debug and iterate on their work, and build code for data visualizations. BQuant Assistant can also search the BQuant Help Center and draw from relevant example notebooks, libraries, and how-to guides when answering your questions. This grounding in the BQuant environment enables BQuant Assistant to generate context-aware responses about your projects, workflows and code, thereby providing more relevant support for financial data analysis than a general-purpose coding assistant. BQuant Assistant can also respond with code suggestions and, subject to the user's approval, insert and run code directly in their active project within the secure BQuant sandbox, so users can quickly move from question to result without switching context. Users retain full control over these actions because BQuant Assistant identifies the action it proposes and requests approval before reading from or writing to a notebook. "Financial professionals are working with increasingly large and complex datasets, but turning an investment idea into a repeatable analysis can still require significant time and specialized coding knowledge," said Shawn Edwards, Bloomberg's Chief Technology Officer. "BQuant Assistant brings AI-driven coding that is informed by Bloomberg's understanding of financial data and quantitative workflows directly into the workflows our clients already use to build investment strategies. By helping every BQuant user - from a portfolio manager sketching out a first query to a quant engineering a multi-asset signal - easily move from a natural-language question to working code, data retrieval, and visualization, we are making it easier for clients to test ideas, refine analyses, and build investment strategies within BQuant." With BQuant Assistant, users can: * Generate BQL and PyBQL queries to retrieve and analyze Bloomberg financial data spanning equities, funds, fixed income, FX, commodities, indices, derivatives and other asset classes, across more than 22,000 fields including, but not limited to, reference, pricing, returns, derived analytics, fundamentals, valuations, sustainable finance data, risk metrics, estimates and economic data. * Create code for screens and universes across equities, fixed income, foreign exchange, commodities, indices, exchange-traded funds and other asset classes. * Insert, run, debug and iterate on PyBQL or Python code in an active notebook, subject to user approval. * Ask questions about Bloomberg libraries, BQuant workflows, and client-facing product documentation. * Discuss financial concepts and generate code to help implement appropriate models or techniques for a workflow. * Receive recommendations for data visualizations and generate code using open source libraries such as Plotly and Jupyter Widgets. * Select existing code and ask BQuant Assistant to explain it, helping users develop their Python knowledge while working. BQuant Assistant will be generally available in BQuant Enterprise, and in limited beta in BQuant Desktop at the end of October 2026. The introduction of BQuant Assistant follows a series of recent announcements by Bloomberg related to other AI-enabled solutions also meant to help investors and their firms get more value from the company's high-quality financial data. These include ASKB, the Bloomberg Terminal's conversational AI interface, and Enterprise Model Context Protocol (MCP), an AI access layer for Data License Plus (DL+), Bloomberg's next-generation Data License offering. About BQuant BQuant is a suite of advanced data science solutions designed specifically for financial markets. Its Python-based technology stack combines Bloomberg data and analytics with open source data science libraries and pre-built example projects, enabling users to build and test financial analyses, investment strategies, visualizations and market dashboards. Users can also publish their work as interactive BQuant Published Applications that can be shared with permissioned colleagues across their firm. BQuant is available in two versions: BQuant Desktop and BQuant Enterprise, both of which will include BQuant Assistant. Included with a Bloomberg Anywhere subscription, BQuant Desktop provides enabled Bloomberg Terminal users with programmatic access to Bloomberg data and analytics in a secure sandbox environment where they can quickly develop and refine different strategies and get new ideas to market fast. It helps users develop and refine quantitative analyses while reducing the time required to extract, normalize and manage raw data. BQuant Desktop users can publish interactive applications for colleagues at their firm and save those applications to Bloomberg Launchpad. BQuant Enterprise is a fully managed, cloud-based analytics platform that extends BQuant with large-scale compute, broad programmatic access to Bloomberg data, internal data integration capabilities and collaborative development options. Designed for rapid development, automation and deployment, BQuant Enterprise empowers teams to get to market faster with greater operational agility and innovation. Firms can connect proprietary data sources, integrate enterprise Git platforms, reuse internal code through private Conda channels, schedule projects and use enterprise storage and results-distribution capabilities to support production-oriented workflows. About AI at Bloomberg Since 2009, Bloomberg has been building and using artificial intelligence (AI) in the finance domain - including machine learning (ML), natural language processing (NLP), information retrieval (IR), time-series analysis, generative models, and agentic AI architectures - to help process and organize the ever-increasing volume of structured and unstructured financial information. With this technology, Bloomberg is developing new ways for financial professionals and business leaders to derive valuable intelligence and actionable insights from high-quality financial information and make more informed business decisions. About Bloomberg Bloomberg is a global leader in business and financial information, delivering trusted data, news and insights that bring transparency, efficiency and fairness to markets. The company helps connect influential communities across the global financial ecosystem through reliable technology solutions that enable customers to make more informed decisions and collaborate more effectively. For more information, visit Bloomberg.com/company or request a demo. SOURCE Bloomberg