Data is one resource that insurance companies have in abundance. However, it’s not just the data—but what insurance companies do with it—that can have the most profound enterprise effects. Collecting, understanding, and operationalizing data insights is a multi-step process that requires adequate resources and investment. Business leaders that support this process can reap the benefits in return. It can pay out dividends to combine data with data science professionals, third-party providers, and corporate culture willing to iterate the findings
Data science, analytics, and big data initiatives are crucial for insurers in 2019 and beyond to generate operationalizable data insights. One-quarter of insurers already use big data tools like Hadoop and NoSQL; these rank among the most-piloted capabilities for all insurers. Nearly 50% of P/C and 40% of L/A carriers have predictive analytics deployments. Likewise, big data deployments are a key priority for L/A carriers—40% have planned deployments.
Various organizational models can foster successful data science programs succeed—whether by a centralized data science team for data science or federated data groups in business units. The essential feature of successful data programs is support from the top.
Competition for funding, resources, and priority can be fierce at insurance carriers; compelling ROI bolsters business buy-in. However, it can be difficult to quantify the benefits of data science programs with traditional metrics. It may be necessary to monitor alternative metrics (e.g., KPI trends in areas where data initiatives have operationalized) to understand the value of these programs.
It is also crucial that data science initiatives align with enterprise goals—but even if data science initiatives sync with business strategy, operationalizing the results is what generates real value. Carriers will realize the most significant business benefits when data models incorporate into standard business workflow.
Read more about role of data and data science in insurance—including benefits, challenges, and strategies—in Novarica’s latest brief: Data Science in Insurance: Expansion and Key Issues.
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