How Natural Language Processing is transforming the financial industry

The exponential growth in data from the Internet, social media and personal devices is providing enterprises with unprecedented opportunities to use digital information to improve their businesses.

To an extent, sophisticated analytics programs can help businesses utilize their data by searching for and revealing patterns hidden in structured data, such as spreadsheets and relational databases. But these sources only account for 20 percent of all available data. The real challenge for enterprises is getting value from a sea of social media posts, images, email, text messages, audio files, Word documents, PDFs and other sources that make up the other 80 percent of data that can’t be understood by computers—information otherwise known as unstructured data.

To extract value from unstructured data, companies across industries are turning to Natural Language Processing (NLP).

NLP enables computer programs to understand unstructured text by using machine learning and artificial intelligence to make inferences and provide context to language, just as human brains do. It is a tool for uncovering and analyzing the “signals” buried in unstructured data. Companies can then gain a deeper understanding of public perception around their products, services and brand—as well as those of their competitors.

A growing number of businesses are now using NLP. In fact, a recent report by research firm MarketsandMarkets predicts the NLP market will reach $13.4 billion by 2020, a compound annual growth rate of 18.4 percent.

Financial organizations in particular have applied NLP to obtain actionable insights from digital news sources. For example, NLP can help:

Gather real-time intelligence on specific stocks. A financial services provider can write a query using IBM’s AlchemyData News API that will create a real-time alert if analysts upgrade or downgrade a stock, thereby offering clients a valuable trading edge.

Provide key hire alerts. Everyone knows when a large enterprise hires a new CEO, but company share price and performance can also be affected by the hiring (or departure) of talented marketing, sales, development and finance executives. The News API can deliver instant alerts regarding crucial changes to a company’s management.

Monitor company sentiment. While major news, such as an earnings report or an acquisition, affect how investors view a company, so too can the general tone of the news coverage. Using NLP tools such as AlchemyLanguage per the Watson Developer Cloud, financial services providers can track mentions of companies and discern negative or positive sentiment in news coverage.

Anticipate client concerns. Banks and other financial institutions can use NLP to discover and parse customer sentiment by monitoring social media and analyzing conversations about their services and policies.

Upgrade quality of analyst reporting. With the ability to access relevant, filtered information, financial services analysts are able to write more detailed reports and provide better advice to clients and internal decision makers.

Understand and respond to news events. Individual companies and industries as a whole are subject to national and global events and government or judicial decisions. Using IBM’s AlchemyData News API, financial services companies can monitor news about, say, an oil spill for clients with holdings in that industry.

Detect insider trading. Financial services providers can use NLP queries to track the incremental sale and purchase of insider shares that otherwise might fly under the radar.

The financial services industry is dependent not only on information, but also on information delivered as close to real-time as possible. To access and analyze relevant information in the rapidly expanding universe of unstructured data, financial services providers are turning to natural language processing to help them make decisions and provide sound advice and quality products to clients.