Insurance's 3 big data challenges

Data is powering the new economy and is the main driver behind much of the transformation of industry and society. According to multiple sources, 90% of the data in the world has been created in just the last two years. In measuring the volume of data, we have blown past exabytes and are now calculating volumes in zettabytes (a trillion gigabytes). Soon we will be talking about Yottabytes and Brontobytes. As valuable as this data explosion has been, it has brought along some major challenges. Insurance, just like every other industry, is grappling with three big challenges.

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Rows of colored co-ax cables are seen feeding into computer servers inside a comms room at an office in London, U.K. on Dec. 23, 2014.
Simon Dawson/Bloomberg

Managing the Real-Time Data Flow
Insurers already find it difficult to manage data at rest – the data they collect or acquire and store in databases. Managing the cost, cleansing and organizing the data for transactions and analysis, and governing data usage all require significant resources, technologies, and skills. Layer in real-time data that is beginning to flow from the edge, generated by sensors and devices connected to the things (and people) that are insured, and the management challenges grow by orders of magnitude. Managing data in motion and determining where data should reside (edge, cloud, on-premises) will be tremendous challenges in the decade ahead. And the sheer volume, velocity, and variety of data will make governance and usage much more complicated.

Securing Digital Data
Data security is a huge issue today, with regular headlines regarding breaches of massive amounts of sensitive data from big (and small) organizations. Software and resources for security are already a big line item in many insurance CIO’s budgets. Digital data spread across the connected world will make that task even more difficult, requiring the significant deployment of automation and AI technologies. Insurers must be aware, not just of the potential for data theft, but also of the new possibilities of data alteration. For example, photos of property or vehicle damage could be altered to show a greater degree of damage or damage where there really is none.

Regulation on Data Usage
We are in the early stages of a great debate over who owns data, who has rights to use it, and how data may be used. The global tech giants that have built their businesses on data are under intense scrutiny regarding these issues. Insurers have the additional consideration of industry regulation dictating how data can be used in the industry. Government and industry regulations will continue to evolve, which in itself creates a challenge for insurers.

Of course, there are other challenges like acquiring and training talented individuals that can address these three areas and harnessing AI technologies to make sense of all the data. Both of these areas are vital and the subject of much research and debate, but they rest upon the foundational issues of managing, securing, and regulating data.

This blog may sound discouraging, but there will be solutions and opportunities related to these challenges. Perhaps the most important strategies insurers can adopt is to focus on recruiting, training, and retaining highly skilled data professionals, and partnering with world-class organizations that have the technology and resources to tackle these challenges and enable insurers to capitalize on the power of data and analytics.

This blog entry has been reprinted with permission from SMA.

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Data strategy Unstructured data Data quality Data acquisition
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