Bloomberg has introduced BQuant Assistant, a finance-domain anchored conversational AI coding assistant built into BQuant Desktop and BQuant Enterprise. BQuant Assistant is integrated into BQuant development environment and enables financial professionals with Bloomberg Terminal subscription to use natural language prompts to write code, build dynamic applications and accelerate financial data analysis workflows.
Financial-domain anchored conversational AI coding assistant added to BQuant Desktop and BQuant Enterprise.
BQuant Assistant brings conversational AI directly to same Python environment in which users develop investment strategies, dashboards and quantitative financial analyses. BQuant Assistant can answer customer questions about BQuant, generate Python code, help querying data from Bloomberg extensive datasets via Bloomberg Query Language (BQL), help debugging and iteratively improving work, and generate code for data visualizations. BQuant Assistant can also search BQuant Help Center and draw from relevant example notebooks, libraries and guides. By anchoring in BQuant environment, BQuant Assistant generates context-aware answers about users projects, workflows and code, providing more relevant support than general coding assistant.
BQuant Assistant can provide code suggestions and after user approval directly insert and execute code within active project in secure BQuant sandbox, allowing users to move quickly from question to result without switching context. Users retain full control as assistant indicates proposed action and asks permission before reading or writing in notebook.
"Financial professionals work with ever larger and more complex datasets, but turning an investment idea into repeatable analysis can still require much time and specialized programming knowledge," said Shawn Edwards, Chief Technology Officer at Bloomberg. "BQuant Assistant brings AI-driven coding based on Bloomberg insight into financial data and quantitative workflows directly to workflows customers already use to develop investment strategies. By helping every BQuant user from portfolio manager drafting first query to quant developing multi-asset signal easily move from natural language question to working code, data retrieval and visualizations, we make it easier for customers to test ideas, refine analyses and develop investment strategies within BQuant."
With BQuant Assistant users can generate BQL and PyBQL queries to retrieve and analyze Bloomberg financial data for equities, funds, fixed income, FX, commodities, indices, derivatives including more than 22,000 fields covering reference, pricing, returns, derived analytics, fundamental, valuations, sustainable finance, risk figures, estimates and economic data, create code for screenings and universes, insert, execute, debug PyBQL or Python code after approval, ask questions about Bloomberg libraries, workflows and product documentation, discuss financial concepts and generate code to implement suitable models, get recommendations for visualizations with Plotly and Jupyter Widgets, select existing code and ask assistant to explain it to expand Python knowledge.
Launch follows series of recent Bloomberg AI-driven solutions including ASKB conversational AI interface of Bloomberg Terminal, and Enterprise Model Context Protocol MCP AI access layer for Data License Plus DL+.
About BQuant
BQuant is range of advanced data science solutions specifically developed for financial markets. Python-based technology stack combines Bloomberg data and analytics with open-source libraries and pre-built example projects. Users can develop and test financial analyses, investment strategies, visualizations and market dashboards. Users can publish work as interactive BQuant Published Applications and share with colleagues. Available in two versions: BQuant Desktop included with Bloomberg Anywhere subscription and BQuant Enterprise fully managed cloud-based platform with large-scale computing, broad programmatic access, internal data integration and collaborative development.
