VISUALIZE | INSIGHTS THAT POWER INNOVATION

Smart business decisions begin with quality data

Everything starts with data. Every data point—large or small—can have value because insights gleaned from analyzing data can drive decision-making, inspire new products, and even birth new businesses. However, if data is wrong or incomplete or out-of-date, then insights could be faulty. Products or services derived from defective data could fail to win customers, leading to business failures and economic harm.

During our Verisk Velocity session, The Path to Data-Driven Success Amidst Change and Uncertainty, we examined how maintaining and improving data quality is vitally important to every enterprise, in particular the insurance industry.

Data Literacy Is Everyone’s Responsibility

Here are some of the key takeaways:

System modernization is a priority: Research shows that 41 percent of top-performing companies are making data and analytics a strategic priority as they seek to streamline operations.1 Businesses are phasing out legacy computer systems in favor of nimble new platforms capable of executing digitally driven data management objectives. Migrating away from outdated systems also means leaving behind tedious manual entry, decreasing support from third parties, and avoiding the challenge of finding IT talent versed in older technology.

Mergers need careful oversight: The risk of introducing errors is enormous whenever two companies with disparate systems merge. When carriers combine data sets, even tiny variations in how policy and claims systems are recorded can produce serious processing errors.

Educating employees about data is essential: Research shows that 84 percent of top-performing companies are concerned about the quality of their data.2 Data literacy has become a valuable skill for all employees in an enterprise. Understanding how to use data to assess situations and craft solutions is vital regardless of job role or level.

Evaluating data quality is vital: Every activity that relies on data must first ask if the data is valid, complete, timely, and accurate. Does the data have the correct coding? Is there enough—or too little—data? Is the database up-to-date? Do the results make sense? About 77 percent of companies believe their profitability is affected by inaccurate data, so identifying problems early is crucial.3 Ensuring data quality is the essential component of ISO’s product offerings, whether insurers are performing loss cost reviews, claims analysis, or predictive modeling.

To learn more about how ISO’s products and services power high-quality data and to get a preview of future innovations, please watch our Verisk Velocity session on demand.

Download our white paper, Charging down the path to data-driven success.

Read our Visualize articles Why data management must be a top priority for insurance mergers and acquisitions and Data literacy is everyone’s responsibility.

  1. Forbes webinar, “The Data Differentiator, How Improving Data Quality Can Improve Your Business,” September 2017, <https://i.forbesimg.com/2017/9/14/Data_Differentiator.mp4>, accessed on October 21, 2020.
  2. Forbes
  3. Schultz, Thomas. “The State of Data Quality,” Experian Data Quality, September 2013, <https://www.edq.com/data-quality-infographics/state-of-data-quality/>, accessed on October 21, 2020.

Richard Morales

Richard Morales is senior manager of ISO statistical data standards and services at Verisk. He can be reached at Richard.Morales@verisk.com.

Mike Lenczewski

Mike Lenczewski is senior director of the ISO strategic actuarial operations division at Verisk. He can be reached at Michael.Lenczewski@verisk.com.

Dennis Huang

Dennis Huang is ISO actuarial director, analytical data management, at Verisk. He can be reached at Dennis.Huang@verisk.com.


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