Solution:

A text analytics solution built on NLP technology performs much of the heavy lifting when it comes to uncovering valuable information from earnings calls.

NLP can automatically synthesize and summarize these calls and extract signals around sentiment and targeted events. Analysts can easily navigate transcripts by key language drivers such as headwinds and tailwinds. They can view clustering of positive and negative sentiment—or trends over time and across one or multiple companies—to uncover themes that are otherwise missed in traditional analysis.

This information serves as a much needed supplement for analysts, whether or not they are able to listen to the calls, by providing them with deeper insights around management commentary.

One of the Symphony products available for demo is an out-of-box, cloud-based platform trained on financial data including earnings call transcripts and SEC filings.

With demoing, an investment management company can see what true NLP is capable of doing. More importantly, it distinguishes NLP-based text analytics from other, similar sounding tools marketed to finance which rely heavily on Bag-of-Words, text mining, and machine learning. Some of the key areas for comparison are accuracy, speed, quality of extractions, and workflow integration.

Demoing also serves as an “idea-starter” for additional customization. The Insights Platform is able to dive deep into the domain expertise of the company to model their platform according to the client’s proprietary way of looking at things.

Outcome:

• Analysts expand their coverage exponentially of the companies that they follow closely, looking at competitors, suppliers, and companies’ customers to gain additional insight.
• Adding NLP makes for a more informed investor and better decision making. More relevant data to make better decisions.