Big Data in Insurance

Learn how to avoid failing big data initiatives in insurance

Mark PriebeOctober 12, 2017

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Big data has been the next big phenomenon in the insurance industry for years, but only a few insurance carriers have been able to successfully turn big data into insights. For many, big data continues to be an elusive target they hope to leverage in some distant future. But for now, nothing has changed and it is still business as usual throughout most of the industry.

Failing Big Data Initiatives in Insurance

Recently Insurance Business Magazine conducted an interview with BJ Schaknowski, senior vice president and chief sales and marketing officer at insurance software service provider Vertafore. One reason he gives for insurers not leveraging big data is that they are not “working with a provider [who can take] really good data that may not have been available historically and put it into a very consumable format.”

As the buzzing of big data’s promise increases, the reality is that there is no pause in the amount of digital information that is being generated. As noted above, most insurers are struggling to wrap their hands around successful big data initiatives. So, rather than giving up on the promise of big data due to challenges like the disconnection between IT teams and business needs, they should look for a solution that mediates this disconnect. But, not all insurers are equal, neither are all solution providers. Identifying the right vendor that can translate technical jargon into business context is the most efficient starting point. Ideally, this would be a data governance solution that bridges the two worlds so the business user can understand their data and then use it to solve business problems.

How Data Governance Fits into Big Data

Data governance often means a variety of things for different organizations across different industries. Considering how much data is delivered to insurers, you often have to think about data governance as the process that delivers data that can be trusted and used to make business decisions on a repeatable basis.

When insurers look for a data governance solution to help them leverage their big data, identifying a solution that delivers complete transparency into all aspects of their data assets, from the data available, its owner/steward, lineage and usage, to its associated definitions, synonyms and business attributes is critical. Full visibility will allow insurers to gain valuable insights into not only the details of their data assets, but the attendant risks associated with its use across business applications.

Additionally, it’s just as important to find a solution that is easily navigable and not overly technical. This helps keep all users in mind – from your data scientists to business analysts, who both have equal needs for data, but at varying levels.  It should put important, trustworthy information right at the fingertips of all users within an insurance organization. However, leveraging big data in the insurance industry goes beyond data governance. Insurers will need an all-inclusive big data platform that also includes data quality and analytics capabilities.

All-Inclusive Platform

A big data platform includes a data quality solution can help ensure data errors do not occur. The solution should include a standardized, auditable, and automated end-to-end data quality framework to remain vigilant and catch errors before they impact business.

An analytics component can help insurers extract insights from their data. This allows them to make faster, smarter business decision and improve the customer experience, leading to more money and less customer churn over time.

Insurers need to be on the lookout for a comprehensive, big data platform that includes data governance, data quality and analytics capabilities. The first insurers to implement this type of platform will enjoy a huge competitive advantage within the industry.

To learn more about how data quality and analytics can help wrap around a successful data governance framework to avoid failing big data initiatives in insurance, check out the data sheet below.

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