U.K. Insurance

Learn how a specialist insurance and underwriting company tackled data quality challenges to ensure that only high quality data was used for company analysis and regulatory reporting.

Business objective

The insurance company aimed to improve data quality to support decision making at all levels of the business, in addition to meeting or exceeding regulatory reporting requirements. They sought to institute tighter, more automated controls around their data, and emphasized checking newly entered data to ensure its appropriateness for analysis and reporting.

Initial challenges

The insurer’s data challenges centered around the quality of data captured and consumed in their business. Ataccama initially identified issues with 18% of the company’s data. This low data quality left the company insufficiently confident in numbers they used for analytics and reporting to shareholders and regulators.

Project 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: Implement data quality rules to check the validity, accuracy, and correctness of data, and monitor source system data quality.
  • Improve decision making by improving data quality as a whole: Prior to implementing Ataccama’s DQC product, Neon had been making risks, claims, and other financial decisions based on data of uncertain quality.

Solution & Products

Neon leverages full Ataccama’s suite for data quality and governance:

  • Data Quality Center (DQC) – a powerful, business rule driven engine for complex data management that enables you to transform, standardize, cleanse, validate, correct, and enrich your data, and prevent incorrect data from entering your systems.

Running on top of the DQC engine, there are two user-friendly applications for data stewards and business users:

  • Data Quality Issue Tracker (DQIT) – allows data stewards to resolve various data quality issues that cannot be managed [or fixed/settled] automatically and require their approval or other manual intervention.

  • Data Quality Dashboard (DQD) – enables data stewards and business users to monitor data quality continuously, see its current state, track trends, and use this insight to make informed business decisions.

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 has been 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.

Take the first step to data quality—it’s free

Find out what’s in your data,—from incorrect or missing values to duplicates and more, with our sleek, collaborative cloud application for data profiling—Ataccama One Profiler.

Prefer to work locally? Download our DQ Analyzer—a powerful and market-popular desktop application for advanced data profiling—and join our 20,000+ active users.

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