By: Kevin May, CSO of Gigaforce Inc.
The insurance industry, like all other industries, has faced the challenges of the last two years and is now trying to figure out what the new “reality” really means. Working from home, dealing with the schooling of kids, adapting to new ways of communicating with our colleagues, and so many other issues had to be addressed as we navigated these uncharted territories. However, what seems to be the largest issue that every company is facing is ”The Great Resignation” and the inability to fill roles essential to the success of the organizations. As companies consider their options, the utilization of technology to streamline processing rises to the surface as the leading option. Let’s keep in mind that technology doesn’t necessarily replace people, but it allows staff to handle issues that require their expertise while letting the technology handle those mundane tasks. Those technologies consist of Robotic Process Automation (commonly referred to as BOTS), Artificial Intelligence (AI), Machine Learning (ML), and Distributed Ledger Technology (DLT). Very much like the structure of our own bodies, each of these technologies plays a specific role in accomplishing a broader goal.
At the core of the issue, the technologies are addressing the excess expense in the operations of insurance carriers, reinsurers, brokers, and business partners that comes from the need to exchange data and documents, provide real-time communication, move money efficiently, and create a transparent auditable process. We need to keep in mind the goal is to solve business problems, not promote a certain technology for the sake of the technology.
Let’s look at two use cases where these efficiencies are being realized for greater profitability.
Carriers have lost people over the last two years and need to manage the increased workload that has come with the post pandemic experience. Many times, the carriers are outsourcing those files to their recovery partners to supplement their efforts. However, both are having issues with staffing impacting cycle times, subrogation recognition, recovery cycles, and the inability to process money in a timely manner, especially between the recovery partners and the carrier. As we know, maximizing recoveries at the least recovery cost adds significant dollars to the bottom line in order to keep premiums competitive. It impacts all of us!
Artificial Intelligence/Machine Learning is being used to identify subrogation claims at the First Notice of Loss and throughout the claims process. BOTS are being used by the recovery companies to reduce the costs passed onto the carrier and to improve recovery cycles while the DLT allows for transparency and efficiency of processing data and money (i.e., through the use of smart contracts). The combination of these solutions drives out the expense and improves the amount of net recovery a carrier realizes.
Each organization is interested in having insight into those areas where there is mutual interest. This may involve the claims experience of the policyholder or involve the reinsurer relationship. It also may involve understanding the loss exposure between the reinsurer and their cedents requiring resources to compile data which is not accomplished in real-time as desired.
DLT allows for the secured real-time exchange of data between parties while AI can be used to help compile the information. BOTS can be used to replace the routine manual processes the parties incur through these processes.
These are only two of many use cases that can be addressed to improve efficiency and allow staff to concentrate on those issues that require their expertise. The post-pandemic world is much different than early 2020. It requires a different perspective on how to solve problems and an understanding of how technology can help improve results.
Here’s to your profitability!