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Discover why our clients always know more 

Enterprise Data Management

Enterprise Data Management

Confirm a single source of truth by connecting people, applications and processes with reliable data and analytics.

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Text Analytics

Text Analytics

Extract and analyze the most important data on entities, people and products.

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Compliance Management

Compliance Management  

Avoid conflicts of interest by organizing your compliance management and independence processes.

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Delivering intelligent solutions faster so our clients know more.

Solutions are created for the unique needs of each client, supported by the three suites of the Kingland Platform.
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Kingland Innovates to Meet Market Need

From A-Team Insight:

Kingland Innovates to Meet Market Need for More Effective and Efficient Data Usage

Company reached out to 30 firms to ensure it is servicing clients' key needs

Kingland is responding to financial institutions’ growing desire to use and manage their data to better effect and greater efficiency with the provision of solutions including artificial intelligence (AI) and text analytics. It is also focusing on firms’ ongoing challenges around core functionality such as entity data management for Know Your Customer (KYC), enterprise risk management, understanding large volumes of data, and delivering on cost programmes.
Fueling_Indy_Homepage

Fueling Independence Compliance Across the Enterprise 

How can companies keep up with changes when a new regulatory alert is issued every 7 minutes?

Understand relationships, analyze information, and make go or no-go decisions on potential compliance issues. Learn how you can do this and more globally and building regulatory jurisdiction into your monitoring and reporting process across the enterprise. 

Unstructured-Data-DataManagementInsight

From A-Team Insight:

Kingland Increases Accuracy of Text Analytics for Unstructured Data

Data Management Insight says Kingland continues to push the technology envelope with latest enhancements

The improvements to NER training increase accuracy in identifying organisations and people that are intuitively highlighted by text analytics within documents. In this case, targeted retraining of the NER models has increased the accuracy of stock models from 60% to nearly 90% in aggregate over numerous source document sets. .

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