The financial sector consolidations over the past decade left many firms with volumes of knowledge trapped in legacy systems—but only a surface-level understanding of the valuable data they acquired.

Understanding how to best leverage the fruits of their consolidations—data—is where many are now focusing their attentions and IT budgets. An event I attended last month, “Demystifying Financial Services Semantics: The Business Value of Data and Semantics” hit the point home: Big Data has arrived, and while not without challenges, it presents a world of opportunity.

Financial institutions are looking to linguistics and semantics as the best option for managing and taking advantage of their unstructured data, using it to better understand customers and competitors, to identify impactful market trends or simply to automate the process of answering common customer questions.

As one Chief Data Officer put it:“We are the stewards of one of our firms’ most important assets, data, and we have been charged with bringing meaning to the data. I believe semantics offers a consistent, long-term capability and change in how data will be managed.”

The ability to understand words in context is where semantics has proven to excel above all other technologies—here’s how:

• It allows organizations to better leverage the variety of data typical of financial institutions: risk analysis, transaction data, customer service feedback and socially generated content is a mix of structured and unstructured information that any financial institution can leverage for corporate and market intelligence.
• It breaks down the data silos acquired and built over time.
• It supports a unified view of information for competitive advantage. In a highly competitive environment, using linguistics and semantics can help companies learn more about customers based on their activities and preferences, noticing even the weakest signals and patterns in information. This new-found insight benefits many day-to-day areas of operations including: marketing, sales and product development efforts.

We are seeing customers take advantage of semantic technology by not only analyzing customer data to understand and benefit from customer feedback, but also through automated, virtual assistance.

Big Data presents a challenge for many industries and financial institutions are stepping up to that challenge, whether through the development of the Financial Industry Business Ontology (FIBO), or through Big Data projects geared toward implementing a framework to support the Dodd-Frank Act and data transparency.

Big Data is here to stay, and it is clear that having the ability to understand words in context using a semantic intelligence platform is critical for driving the new revolution.