The popping up need for insurance company is to effectively use their underwriting resources. This practice alone can boost the productivity and profitability of any insurance company. Robotic Process Automation(RPA) could make a way to resolve the underwriting leakage by potentially utilizing the underwriting resources in a far more effective way.
Underwriting is a key process of handling risk in the financial world. The underwriter’s vetting inspection process exposes unacceptable risk applicants and also inspects the policy holder’s trustworthiness to determine the premium for providing coverage. Underwriting leakage occurs when the underwriter is unable to predict the risk and takes too long to underwrite a policy, resulting in high turnaround time. Also, in the case of low-risk policies, manual underwriting incurs a high cost for physical survey and inspection resulting in an increase in expenses more than the premium collected. This leads to financial loss and process inefficiency. The changing trend is the amount and collection of information available for analysis and the technologies used to aggregate and analyze the data. This is where robotic process automation comes in.
Hence, the best underwriting team will have a heady mixture of data analytics, intelligence rules, and expert knowledge which is capable to resolve this underwriting leakage. The honeycomb structure below represents the factors for underwriting leakage.
According to the U.S. Bureau of Labor Statistics, between 2012 and 2022, the number of underwriting jobs in all industries will decline from 106,300 to 99,800 - a drop of 6%
Overloading underwriters in insurance industries with both low and high-risk tasks may lead to human error due to overstress. Thus, achieving maximum productivity will be impossible as firms will fail to make the best use of time and skilled underwriting resources.
Carrying out robotic process automation may enhance the underwriting process by fully automating the process for low risk and repetitive tasks and partially automating the process for high-risk tasks. Hence, underwriters are still required to play their role of decision-making and analyzing the intelligence rules for high-risk tasks, thus reducing the underwriting jobs to 6% and not 60% or even higher, says a report.
Let’s take a scenario in insurance industries where RPA is used to underwrite a policy. The policy is analyzed and then categorized into low risk or high risk. Fully automating the underwriting process in low-risk policies will overcome human underwriters for a higher proportion by reducing the repetitive tasks and increasing the number of policies issued. Therefore, through robotic process automation, this increases customer satisfaction and also boost the insurance company’s reputation. Moreover, in auto underwriting, the knowledge database will leverage and continuously auto-updates the data in a single repository through deep learning. This gives insight into the policy risk for future quick decision-making of premium and coverage.
Even in case of high-risk tasks, automation can be utilized for underwriting resource allocation by using the intelligence rules that will decide which types of risk cases can be allocated to each stage of underwriters depending on their skill set. Further, the knowledge database also provides better suggestion for exposure. This reduces the stress level of underwriters and better utilizes them for more complex decision-making.
What RPA can do?
Effective implementation of RPA will subsequently reduce repetitive tasks and overstress for underwriters. It also makes use of expert knowledge in the knowledge database for more accurate understanding of risk and establishing exact premium amounts. Better consumer interaction can be achieved for any insurance company by providing self-services which help the customer to check policy status and also to provide their updated information for underwriting consideration.
Additionally, this also increases customer satisfaction by instant policy issuance in case of low-risk policies and policy issuance with less turnaround time of a few hours instead of days and weeks in case of high-risk policies. This, in turn, will save time for insurers and enhance the underwriting process.
In the sprouting digital era, automation in underwriting enhances the data analytics process which not only decreases financial loss, but also potentially leads to standardized underwriting process with proper inspection management and also figures out more accurate risk assessment. Leveraging robotic process automation will consequently reduce underwriting leakage and also effectively use the expert underwriting resources and their intelligence. This robotization act will elevate the productivity and profitability of the insurance company.