Underwriting Process in insurance industry

Example of RPA in new business & underwriting process

  • Underwriting is a lengthy process of collecting information from numerous sources and evaluating risks that are associated with the policy that is in hand. Underwriters help the insurance company approve applications by evaluating risks of customers, their homes, or vehicles. This information varies from one applicant to another. It takes, on average, 2-3 weeks to complete this process when the Insurance domain is concerned. Believe it or not, but 18.8 million people across the globe have reported that they failed in completing this data collection task.
  • Underwriting is the perfect use case for RPA implementation as it is a lengthy process, needs accurate results, and is a sequential process. To illustrate the role of RPA, let us take an example of Auto Insurance. An auto Insurance Underwriter requires data to should get collected from the public records regarding the owner of the auto. That can include
    • Checking if the driver is insured: This data can get transferred to the Auto Insurer’s CRM, which can later be retrieved if the auto insurer shares the database with the similarly-sized auto insurers.
    • Checking for claims within the Comprehensive Loss Underwriting Exchange (CLUE) that the customer might have filed with previous Insurance companies. This data can get transferred to the Auto Insurer’s CRM.
    • Checking if the auto Insurer is eligible for the application or does he have some criminal records or is violating the company’s policies or compliance. That requires the Robot to check with the public data of arrests, charges, a conviction in the motor-vehicle related incidents.
  • Now, the moment an Auto Insurer fills the application, Robot can fetch the details from the application, run it first with the internal database and create an Auto-Insurer CRM under the relevant category. It can then check the records of the applicant against the public data for any discrepancy of violation of the policies. Finally, it can quickly check if the applicant is eligible for Insurance within a short duration of time. That would fast-track the process, and the underwriter can quickly analyze the risk and help the insurance company make the decisions faster and with 100% accuracy.
  • This example covers just a small data in the Insurance domain. Imagine how many applications an Insurance company receives daily on Vehicular Insurance, Personal Insurance, house insurance, and a lot more categories. Robots can accurately gather real-time data from both external and internal sites very fast, and this process could make to run as per the requirements automatically. It not only ensures the data accuracy of 0% error but also helps in freeing up 30-40% of the capacity that gets delivered within a limited time.

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