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Entity Extraction

Linking In-house and Third-party Data to Streamline Success

Are you bumping into the walls of siloed data? Whether your company is grappling with legacy systems that don’t integrate or datasets from third-party sources without common keys, there are ways to create matches in the data that paint a more robust view of your customer, prospect, or person of interest.

Consolidating your in-house data

Between their mergers and acquisitions, businesses and organizations are growing at an exponential rate, forcing them to mash together customer records across a variety of systems that may not play well together. Customers expect a seamless, first-class experience, but that’s challenging to deliver when you’re operating with disparate systems of in-house data. And with so many available options, customers won’t hesitate to take their business elsewhere if their expectations aren’t met.

Let’s say you’re a financial services institution offering investments, loans, and deposit accounts. Your marketing department cross-promotes these products, offering the convenience and savings of centralized banking. However, on the back end, these accounts are serviced on separate systems from past mergers that have little or no integration.

Companies at the forefront of digital transformation are realizing that keyword-based search is becoming obsolete when searching for information about people. They’re now using explainable artificial intelligence (AI) to accurately verify names of people and organizations against vast databases to understand where customers exist in their ecosystem. This enhances the customer experience and keeps data organized and easy to consume, no matter how fast it’s growing.

Tech-driven due diligence

To go beyond basic information for their screening efforts, many companies are contracting sources of data from a variety of third-party sources – all of which have different datasets and formatting.

The team at Vital4 wanted to provide their clients with a top-tier solution: pulling together the information they couldn’t get anywhere else. They could dig up information about negative news and politically exposed people in various languages, but, a traditional keyword-based search didn’t provide the accuracy that Vital4 needed.

In order to create the most robust product, Vital4 brought together masses of data sources, but the information was siloed and data sources were disconnected. Vital4 needed a solution to connect the dots, so they could search for people and deliver a more detailed profile through a unified dataset.

Vital4 chose a solution that offers two capabilities to enhance its search: intelligent fuzzy name matching and AI-powered tagging of people and businesses in articles. With this technology, the team can not only search for people by name or organization, but they can also search through variations, including nicknames, abbreviations, criminal records, and even initials. The rich profiles of aggregated data returned on these people give Vital4’s clients many more insights faster and more efficiently.

The industry-leading data linking solution

Linking in-house and third-party data gives new life to your information, making it work harder and transforming it from a siloed nuisance into a mission-critical differentiator. Babel Street Text Analytics (formerly Rosette), has the capability to seamlessly link data using machine learning and name matching techniques. 

Find out how to transform your data into actionable insights.

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