Britische Rückversicherungsgesellschaft

Versicherungsanbieter

A specialist insurance and underwriting company improved data quality for company analysis and regulatory reporting.

Business objectives & project requirements

  • Improve data quality to support decision making at all levels of the business.
  • Meet or exceed regulatory reporting requirements.
  • Determine the relevance of data stored in core systems and remediate any issues.
  • Implement tighter, more automated controls for capturing data in order to preserve data quality. Enable data entry monitoring to safeguard the quality of data used in analysis and reporting.
  • Cleanse data in anticipation of data migration.
  • Track the validity, accuracy, and correctness of data and monitor source system data quality.

Initial data challenges

  • Insufficient quality of data being captured and consumed (initially issues with 18% of the company’s data).
  • Low confidence in numbers used for analytics and reporting to shareholders and regulators.

Solution & benefits

Data quality improvements of up to 99%: Working with tens of thousands of records, Ataccama reduced data quality issues to 1%. This improvement allowed the company to take control of data being used for risk assessment, other internal purposes, and regulatory and shareholder reporting.

Business buy-in: The value of the data quality initiative was recognized not only by IT and data experts in the company, but also by business users and executives.

User-friendly solution: Ataccama’s user-friendly dashboard enabled business users to have a quick view and clear understanding of the contents of their data and issues in need of fixing.

Fast implementation of new rules: In the course of one day, several new rules can be implemented and the results seen immediately.

Product

The organization utilized the Ataccama ONE platform module for Data Quality Management. Ataccama ONE DQM is a powerful, business rule-driven platform module for complex data curation that enables you to transform, standardize, cleanse, validate, correct, and enrich your data, and prevent incorrect data from entering your systems.

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