If insurers could somehow forecast the future, what a safer, more productive, and more profitable future it might become. Loss prevention departments could greatly reduce both claim frequency and severity, while growth could be focused to mitigate catastrophe risk.

While we await a crystal ball, all kinds and sizes of losses are taking place. The good news is that tools are now available to help shine a light on important issues within the insurance industry. Big data and predictive analytics have held a firm foothold in underwriting and actuarial departments for years, and many are finding they also have a place in handling Workers’ Compensation claims. As models are refined, more insurers are learning how to improve outcomes and their bottom line.

The key to successfully incorporating a predictive model is to target opportunities where data can give a claims organization the biggest lift, with the lowest-hanging fruit clearly being claim severity. At the National Council on Compensation Insurance 2015 Annual Issues Symposium, 32 states reported an increase in average annual Workers’ Compensation claim severity between 2009 and 2013, and this is a trend that deserves attention. From claim assignment through settlement, identifying claim severity early and accurately can help put claims departments in the driver’s seat, allowing a proactive and informed approach to claims handling.