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Big data, predictive modeling, and predictive analytics pose numerous challenges to many industries. But Insurance companies face exciting and profitable outcomes in creatively addressing them and refining these capacities.
The Insurance industry is challenged by big data, a collection of data sets so large and complex that it has become difficult to process using on-hand database management tools. Despite the challenge, commercial insurance is becoming more efficient by creating increased automation for decision-making.
For example, predictive models capture relationships among many factors to allow the assessment of risk or potential risk associated with a particular set of conditions, guiding decision-making for successful transactions.
Complementing this, predictive analytics encompasses a variety of statistical techniques that analyze current and historical facts (data mining) to make predictions about future events.
Without a doubt, the world of big data constitutes a paradigm shift for Insurance companies. Developing capacities to deal with big data, predictive analytics, and predictive modeling is the singular current focus for strategic Insurance companies today.
Download this article for a look at these most important trends in modern Insurance analytics.