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Thomas Schutz, Experian QAS North America
Thomas Schutz, Experian QAS North America
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3 Must-Haves for Insurance Data Quality

The increasing number of channels is hurting data quality within insurance organizations, 94% suspect their customer and prospect data might be inaccurate in some way.

Insurers face a multitude of challenges as they operate through new channels. While independent agents and call centers are still an important connection point, insurers are moving to online and mobile channels to satisfy policyholders.

While these new channels are exciting endeavors, they do increase the speed of business and create unique challenges. One issue is around the collection of contact data. Insurers are no longer relying on trained staff to enter information; they have to ensure the accuracy of self-entered information from policyholders.

Unfortunately, the increasing number of channels is hurting data quality within insurance organizations. According to a recent Experian QAS study, 94% of organizations suspect their customer and prospect data might be inaccurate in some way. On average, respondents think as much as 17% of their data might be inaccurate. Even worse, 27% of respondents are unsure how much of their data is inaccurate, showing some organizations are not monitoring data quality as carefully as they should.

Insurers need to come up with ways to improve data accuracy across channels, but especially in digital channels that are not necessarily controlled by the carrier. Contact data collected across channels aids in rate quoting, risk analysis, marketing campaigns and overall business intelligence. It is crucial that information is accurate as it is being collected.

One method for improving data accuracy is to eliminate the possibility for human error. Human error is the main cause of poor data quality, with 65% of respondents in the recent study citing this as the main cause for data inaccuracies.

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There are several ways insurers can combat this issue.

1. Identify data entry points — Insurers need to understand how information enters their system and through what means. Consider all channels and data entry points so a full data workflow can be created. Then prioritize projects based on high volume channels or excessive data quality errors.

2. Utilize automated verification processes — Software solutions can be implemented in various channels to prevent inaccurate information, like poor address and email contact details, from entering the database. Incorporating software solutions is the only way to ensure information self-entered by untrained users is accurate. Figure out what data is most important to the business and evaluate and prioritize available solutions.

3. Incorporate technology that continues to clean information over time — insurers should regularly monitor their databases. Even with software tools at the point-of-capture, regular database maintenance is required. Regular cleansing allows insurers to review information and make sure installed tools are still effective in managing data to the expected level of quality.

By taking these simple steps to improve data quality, insurers can be confident that new channels are not only convenient for consumers, but also supplying accurate and reliable information to the business. While it is no longer a choice to operate in digital channels, insurers can take steps to ensure accurate data capture and make certain that new processes are not hurting information quality or staff efficiency.

About the author: Thomas Schutz is SVP and GM for Experian QAS North America, serving as the company's top executive for all strategic business decisions in the United States and Canada. He be reached at thomas.schutz@qas.com.

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