Person cutting a branch off of a tree. Overhanging trees can increase the frequency and severity of a claim. Armed with this information, insurers can choose to either provide rating for this new risk or use the information to engage with the customer proactively and recommend that they trim overhanging branches as a loss avoidance measure. (Photo: bogdanhoda/Shutterstock.com)

Last year was the second-costliest ever for the insurance industry, with roughly $120 billion in losses caused by natural disasters alone. With the tally from Hurricane Ian already estimated to be over $70 billion, this year may shape up to be another one for the record books. Against this backdrop of catastrophic losses, rising costs and heightened competition from all corners of the marketplace, property and casualty (P&C) insurers need to find ways to streamline their operations, improve the accuracy of their risk forecasting and drive stronger customer engagement.

To get there, they are going to need more powerful data and better predictive analytics.

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