Fundamental Investing

Enforcing investment thesis by incorporating unstructured data in investment process


Unstructured Data Has Limited Utility

Most alternative data sources are unstructured and cannot be incorporated into an investment thesis until parsed into a structured format.

Without Security Mapping, Data is Useless

Lack of compatible security mapping indicators make using both structured and unstructured data from alternative sources difficult for asset managers to use.

Data Is Too Noisy

Most alternative data refers to massive datasets that contain large amounts of extraneous data, known as noise. For effective use in an investment thesis, the information must be intelligently filtered to remove or minimize the noise and create a clear and meaningful dataset.


Connect Any Textual Data

Accern’s AI-Powered Natural Language Processing engine connects any and all textual data feeds and parses that data into a structured format. Some dataset examples include Premium News Feeds, HTML Pages, and PDF Documents.

Derive Insights Usable for Investment Theses

Accern’s AI-Powered Natural Language Processing engine can derive over 60 insights from each relevant article to be incorporated into an investment thesis. Our insights include entities, events, sentiment, reliability, and impact.

Flexible Delivery Options

Accern delivers structured information to fit an analyst’s work-flow. Delivery options include restful API, streaming API, scheduled data delivery, e-mail notification, SMS notification, and visual reports.


Quicker Insights With Data Diversification

Fundamental Analysts and Portfolio Managers gain a competitive edge by incorporating alternative data sources in their investment theses, resulting in faster and better decision making.