Most insurers, new and old, have already started to use emerging technologies to drive greater efficiency. This is particularly true in the back office, where automation through robotics offers major operational improvements. Take the example of renewals, where there are big peaks and troughs during the year. The spikes in workload mean human error can creep in, while staff overtime costs also make it an expensive process.
Using Robotic Process Automation (RPA) tools, on the other hand, reduces errors, lowers costs, and increases speed. And applications such as Blue Prism remove the need for the same data to be inputted several times into different systems.
Elsewhere, machine learning tools are also increasingly being used for claims. This is especially true for lower value claims. A machine learning application can teach itself to analyze claims received and place them into one of three buckets: pay, don’t pay, or refer. An effective approach is to give the machine learning tool a batch of historic claims to analyze and decide upon – and then to compare those results to those already delivered by your human underwriters. By making any refinements needed, the algorithm should soon be in line with the human decision-making process. Once that’s the case, it can then deal with claims much more quickly, efficiently, and at a far greater scale than a person can, so freeing up valuable resources for other tasks.