The Data Tsunami: Recognizing The Risk In Property Casualty Data Transformation

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25 September 2022

The Challenges Developing and Implementing a Data Strategy


Overall, property casualty insurance is a data-intensive industry. Data is essential to daily operations and reliable functioning of the insurer. Insurers that employ data and the associated analytics can make smarter decisions faster than ever before. New data sources are being developed almost daily, and leading insurers are taking advantage of these to improve all aspects of their operations.

With the tsunami of data available, P/C insurers have a significant opportunity to leverage the expanding data assets they own and can access. For property and casualty insurers—who have either fallen behind or have chosen not to make the business investment in data—it means that charting the course to achieve this transformation is fraught with obstacles that can jeopardize the voyage. As insurers build their business data strategies, they must understand the perils and respond to the challenges that can impede progress.

With the growth in digitized products and services, new digital experiences that reduce the need for customers to physically visit an agent or advisor, and the advent of new insurance ecosystems, insurers are becoming larger creators and consumers of data. The growing need for advanced analytics and AI/ML-based solutions further heightens the data race. The good news is that the increases in manageable and accessible data can feed advanced analytics engines and AI/ML initiatives to fuel growth and innovation. However, this will create challenges for organizations that do not have an effective business data strategy or the capability to execute one.

Data is often viewed as a by-product of insurance operations and historically was only valued for policy administration and reporting. This is traditionally the case for internal scenarios (for example, operational and regulatory reports to ensure payments processed completely), or for external client-facing scenarios such as policy output. This is a growth-limiting view of the value of data, which increasingly is the platform for innovation and growth, not merely insights.

This report highlights the importance of data as an asset in insurance and describes some of the common cultural and technical challenges facing data strategy and data monetization initiatives. A subsequent report will suggest tangible next steps to overcome these challenges and highlight key considerations for an insurance line-of-business data strategy to support analytics and product innovation.