Machine Readable News

Turn unstructured data into actionable insight and manage risk with our comprehensive news feed solutions. From leading news analytics with ultra-low latency delivery, to deep historical news archives and feeds that leverage AI and natural language processing (NLP) capabilities, our solutions can optimise your programmatic workflows.

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Why choose Machine Readable News?

When you work with a high volume of trusted news that is normalised, integrated, tagged and further enriched – adding to the depth and breadth of our real-time and historical news coverage – your possibilities are endless.

Transform real-time news into a feed your machine understands. Within milliseconds, our news solution applies natural language processing (NLP) to deliver sophisticated news analytics; whether you’re looking to inform event-based trading on economic releases and exclusive M&A news breaks, optimise quantitative investment strategies using sentiment analysis or conduct market surveillance based on raw news and associated metadata. Plug-and-play search and symbology APIs strip out the noise and help you get to what you need fast, at low cost.

Plus, LSEG’s programmatic news feed solution is the only one in the industry that’s powered by award-winning, trusted Reuters News.

Our solutions

Our solutions support a variety of uses including macro and corporate actions, event-based trading, algorithmic and quantitative investment using sentiment and buzz metrics, and risk and market surveillance based on company news, flagged with select topic codes. With a range of packages to choose from, we offer flexibility to ensure you can add value to your business decision-making.

Features & Benefits

Seize opportunities

Capitalise effectively on fleeting trading opportunities with our exhaustive real-time news coverage across industries, asset classes and geographies.

Speed up your research and backtesting

Advance an idea from inception to backtesting and analysis to production with historical textual news archives, analytics and tick history.

Optimise your strategies to generate alpha

Develop and maintain your trading strategies and models by deriving better quantitative signals and sentiment to improve returns.

Proactively detect and manage trade risk

Uncover exogenous factors that expose your organisation’s resiliency by flagging potential insider trading and suspicious activities.

What we offer

Our Machine Readable News in more detail

Exclusive access to Reuters News

Reuters is on the ground, wherever news breaks. Our news feeds feature the world’s largest, most trusted news organisation with 2,500 journalists reporting from 200 worldwide locations, generating 4m+ stories and exclusives each year.

Comprehensive coverage

Deepen your own analysis using our global news coverage across political, economic and commodities. Plus major exchanges and newswires – PR Newswire, Business Newswire and GlobeNewswire – and over 46,000 companies in real-time and historical archives.

Discover the most relevant stories for you as all sources are provided in a normalised data model enhanced with financial topics and themes.

News analytics

Enrich your trade signal detection, help human decision making or power market surveillance with news analytics. Our feeds provide analytics to measure sentiment, significance, relevance, novelty, readership to better inform your research and trading activities.

Sentiment indicators

Understand sentiment in the high volume and variety of unstructured, real-time news and social media content. Incorporate scores on entities, countries and markets, including from cryptocurrencies and ESG-related sources, directly into your quantitative or qualitative process.

News delivered how you want it

Access up to 25 years of historical news archives, real-time news in milliseconds and delayed point-in-time data delivered in JSONs format – streaming, request-response as well as bulk files.

With our plug-and-play search capabilities, it’ll be easier and much quicker to pinpoint the needle in the haystack.

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