Systematic Analysis of Unstructured Data for Finance

RavenPack Analytics transforms unstructured big data sets, such as traditional news and social media, into structured granular data and indicators to help financial services firms improve their performance.

The product serves to overcome the challenges posed by the characteristics of Big Data - volume, variety, veracity and velocity - by converting unstructured content into a format that can be more effectively analyzed, manipulated and deployed in financial applications.

Whether your objective is generating more alpha, managing risk more effectively, cutting false positives in market surveillance or generating trading ideas, RavenPack Analytics can improve your performance. See how by selecting your profile below.

Asset Management
Build or subscribe to factors that deliver orthogonal alpha across all asset classes.
Brokerage & Market Making
Detect and instantly react to unscheduled events that may impact your performance.
Risk & Compliance
Monitor accumulation of adverse sentiment, detect headline risk, or reduce false positives from market abuse alerts.
Provide unique aspects to quantitative and fundamental research; control for news and social media in academic research.
Software / Data Vendor
Build an innovator position by adding powerful Big Data analytics to your offering.
Attract attention to your content by adding unique analytics to your website or article.
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RavenPack’s proprietary technology instantly categorizes unstructured content,
like text, into orderly data, consisting of:
Entities - such as companies, commodities, organizations and places.
Relevance of entities in the source data.
Events or themes entities may be involved in.
Novelty of events and density of events or entities.
Sentiment for entities implied by events or themes.
Read more about our technology