2 Keys to Accuracy in Policyholder Analytics

Thomas Schutz' last article: 3 Must-Haves for Insurance Data Quality

Insurers rely more on information and analytics in today's big data world than ever before. While insurers have always relied on analytics to determine risk and underwrite policies, now they are challenged to better understand policy holders.

In today's competitive landscape, consumers are making policy purchases faster. Many are going online to do research and price comparisons before ever speaking to an agent. This creates a new strain on insurers to influence purchases quickly, across multiple channels.

Insurers are relying on data and intelligence to help target marketing communications and identify new opportunities. According to a recent Experian QAS study, 79% of organizations say customer profiling is important or very important to their overall business strategy.

In addition, 82% of companies now have an analytics department tasked with improving customer intelligence and encouraging customers towards specific offers.

Unfortunately, many insurers currently lack the data required to operate in this capacity. The main challenges cited by analytics teams are outdated information, linking different sources of information and inaccurate data. In fact, on average, companies believe that 25% of their data is inaccurate.

With that level of inaccuracy, insurers are left paralyzed, unable to compete and make relevant offers and decisions based on target audiences or individual consumers.

To improve business intelligence efforts, there are two data management practices insurers can incorporate to better access accurate information.

1. Capture data accurately across channels

Accurate information is essential to using data in meaningful ways. Unfortunately, much of the data inaccuracy exists because of incorrectly entered information and differences in data collection across channels.

Insurers should look to put contact verification in place to ensure accurate and standardized information enters the database. Stakeholders should identify the most important data elements and then put processes in place to ensure those details are automatically verified. Those capabilities should be rolled out wherever the insurer is collecting information, whether it is online, in an agent portal or in the call center.

2. Link policy holder records

To gain meaningful intelligence, insurers must link information across departments and channels into one record for each policy holder. Customer information is often spread across multiple departments and databases, dividing intelligence and making it difficult to make informed decisions.

To merge databases, insurers should first define the meaning of a single record. For some, each individual consumer should have a record, for others it might be the household or family. However, organizations should define how they want data to be organized and then set identification criteria. Then, insurers should utilize matching software to identify those duplicates. Software alleviates some of the manual, time-intensive efforts and allows for better matching given today's volume of data.

The consumer is changing and insurers need to be smarter to present compelling offers and better serve their policy holders. Insurers should look to improve data management practices to generate better intelligence and engage in meaningful interactions, no matter the channel.

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 can be reached at [email protected].