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Data Quality Intelligence

Learn about the importance of high data quality and how Asset Control provides clients with insights for sustainable quality improvement

Improving Data Quality

Get Insights to Improve Data Quality

  • Visualize and slice & dice suspect data based on instrument characteristics to identify where your data weaknesses are
  • Identify concentrations of data issues over time and across similar instruments so that different sources or different vendor hierarchies can be considered
  • Monitor and report data quality KPIs; identify root causes for drops in levels

Monitor Data Risks and the Effectiveness of Controls

  • Use Business Intelligence on Key Risk Indicators and control statistics that cover the entire data flow
  • Use Machine Learning and Statistical Analysis to identify anomalies in configurations such as rules, thresholds, ownership settings, and more
  • Assess compliance to processes and procedures using processing metadata, including audit trails

Reduce TCO by Improving Operational Efficiency and Reducing Data and Processing Costs

  • Analyse the performance of data checks (true/false positives) so that they can be improved, and unnecessary work can be reduced in the future
  • Use Machine Learning to improve data checks, for example by learning automatically which fields are mandatory for specific instruments
  • Reduce workload using Machine Learning automation, for example to check the consistent application of rules and thresholds

Meet Internal and External Data Quality Requirements

  • Monitor and report on Key Performance Indicators and Key Risk Indicators for any given time interval
  • Report on work performed, manual activities, performance, and compliance to processes and procedures
  • Support Data Quality Frameworks and Data Incident processes
Streamline Operations

Key Strengths

Continuous improvement is made possible with Data Quality Intelligence

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Data Quality Intelligence

  • Improve data quality
  • Identify, analyse, monitor, and mitigate data risks
  • Verify the effectiveness of data controls
  • Demonstrate accuracy, completeness, and timeliness of data
  • Reduce TCO
  • Meet data quality reporting requirements

More Insights into Data Quality

FRTB: Cloud to Cloud

In this report, authored by Asset Control and Vector Risk, we discuss resolving the challenges of data intensity and computational complexity.

Back to the Roots

Our CTO, Mark Hermeling, takes you ‘Back to the Roots’ as he reviews why data lineage is key for financial service firms as it becomes hard-wired into regulations and data quality frameworks

Download Our Data Quality Intelligence Guide

An overview of Asset Control’s solution, Data Quality Intelligence (DQI). DQI captures performance and data risk metrics at each stage of the data journey from acquisition through to distribution, providing full monitoring and control of each process along the way.

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