Big data is bringing big benefits to organizations that dig in deeply to analyze oft-hidden patterns and other useful information buried in their claims data, particularly highly predictable workers compensation exposures. The companies are discovering unknown correlations that guide more informed risk management processes to reduce claims frequency and severity.
In some cases, these evaluations are performed on behalf of corporate risk managers by their insurance brokers, which have upgraded their Risk Management Information Systems (RMIS) tools to afford big data analytics. A voluminous amount of unstructured, semi-structured and structured data is fed into such systems to discern unusual claims activity or repeat scenarios, which then directs actionable tactics to mitigate and reduce the underlying exposures.
“In the insurance space, it is in the claims area where there is probably the greatest volume of data for loss prevention purposes,” said Claude Yoder, head of global analytics at insurance broker Marsh.
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