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Banking and Capital Markets

Understand Clients. Manage Risk.

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Identify, Assess and Monitor Risk

Kingland helps clients identify new opportunities across complex global hierarchies and identify emerging risks about customers. Operations and technology teams can efficiently manage data connections, hierarchies and data quality, extracting and analyzing data from any source. Fine-tuned for the financial industry, the platform removes time-consuming burdens of data management and errors from manual ad-hoc processes. 

Backed by nearly 30 years of solving complex risk and data management challenges for the financial industry, Kingland brings unique and deep experiences to enterprise-sized, data challenges.  

Banking

 

Reliably and consistently solve complex enterprise data challenges

Data Management 

Leverage secure and diverse amounts of data to create new opportunities and enhance the customer experience. 

Risk Management

Collect and analyze real-time insights and early warnings by connecting external, unstructured data with risk analysis regarding corporate entities, individuals or portfolios. 

Client Data

Integrate client data sources for managing relationships, enabling individuals to quickly retrieve structured and unstructured data and multiple types of data (e.g., legal entity, securities, hierarchies,natural persons, and more). 

 

 

 

Security
Data
World

"We have 27,000 securities on the base with 5 million data points and we have a confidence rate of over 99%. That's really important because [it's critical] the dealers know information they're using to sell product to their client is accurate."

Managing Director
Financial Services

Ready to accelerate your data project?

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More Information 

FairyTale

CDO Leadership: Yesterday's Fairy Tale is Today's Reality

See how Chief Data Officers are thinking about enterprise data management programs. Keep in mind that all data doesn't have to be centralized and in a golden copy. These big, scary and disruptive projects can be managed well by thinking differently. 

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DTCC uses Text Analytics to Reduce Data Mining from Files in SEC's EDGAR System

Text Analytics Delivers Results for DTCC

DTCC, a U.S. financial services firm, used artificial intelligence to remove the manual data entry in its central repository of mutual fund data and operations rules which house approximately 27,000 securities and more than 5 million data points. The result: a significant reduction in the time it takes to process and update the mining of data from prospectuses and other documents filed in the SEC's EDGAR system.  

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Data Quality: Can I Trust My Client Data?

Data Quality: Can I Trust My Client Data?

In order to trust your client data, you need to understand these four primary diagnostic areas - completeness, conformity, consistency and duplication. Discover how you can improve your data quality and the management of your enterprise data. 

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