Finance

Accelerating question-to-analysis-to-execution workflows

Use AI as an interface embedded in existing professional workflows to reduce time from an initial question to analysis and next actions by enabling natural-language querying and faster insight discovery.

Why the human is still essential here

Humans decide what to ask, how to frame the problem, and what actions to take (including compliance checks and risk approval); AI shortens cycle time but doesn’t replace governance or judgment.

How people use this

Natural-language screening to watchlist

Type a plain-English screen (e.g., "EUR IG utilities with widening spreads and positive earnings revisions") and turn the results into a saved list for follow-up analysis.

Bloomberg Terminal / Bloomberg ASKB

NL Q&A to Excel-ready analysis

Ask for key drivers and sensitivities and have the AI pull the relevant series into spreadsheets and outline the next analytical steps for a model update.

Bloomberg Excel Add-In / Microsoft Copilot for Excel

Research-to-trade workflow handoff

Move from an AI-assisted market or company answer to pre-populating a trade ticket (instrument, size, constraints) for human review and execution within the trading workflow.

Bloomberg Terminal (EMSX) / Bloomberg ASKB

Ask-to-analytics shortcut inside the trading terminal

A trader asks a market question and the assistant returns the relevant analytics, charts, and monitor functions to run immediately, reducing time spent navigating menus and screens.

Bloomberg Terminal / ASKB

Draft model narrative and IC materials from analysis outputs

After pulling numbers and running scenarios, AI helps turn tables and charts into a first-draft investment memo and slides, keeping the analyst focused on judgment and checks.

Microsoft 365 Copilot (Excel/PowerPoint) / Bloomberg Excel Add-In

Chat-to-code for backtests and signal prototyping

A quant turns a hypothesis into reproducible code faster by having an assistant scaffold backtest notebooks and data pipelines, then iterates and deploys the workflow after review.

GitHub Copilot / Databricks

Community stories (1)

LinkedIn

we’re all experimenting with AI

we’re all experimenting with AI

And if I’m honest, many people I speak with carry some frustration


The hallucinations

The confident tone masking thin sourcing

The three-bullet summaries

The questionable source material

The answers that sound right but lack provenance or context


In finance, that simply doesn’t work.


When capital is moving probably correct isn’t good enough.


That’s why I’m excited about Bloomberg launching ASKB


Not because it’s chat with your data

But because it’s conversational AI grounded in a deep, historical, structured financial (and non financial) data with transparent source attribution.


For me, that matters


It means:

 Asking complex company or market questions in natural language

 Seeing exactly where the answer comes from

 Moving from question  analysis  execution quicker


It feels like intelligence embedded directly into how professionals already work


If horizontal AI changed how we search, vertical AI (trained and grounded into real financial data & workflows) may change how we build conviction in our decision making


ASKB feels like a step in that direction


Learn more about ASKB and Bloomberg Al: https://bloom.bg/

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Nadia HumphreysGlobal Head of Sustainable Finance Data Solutions, Bloomberg
Feb 25, 2026