Insurance company extends life insurance policies with use of RPA

Extending life insurance policies is an important task for insurance companies. However, the process of checking and extending these policies requires time and attention and it’s a very repetitive task. We offer an RPA solution that automates the process of mutating life insurance policies. Next to offering faster processing times, our solution also increased the employee moral significantly.

8 weeks delivery time

Use case: Extending life insurance policies

The client we worked with is a large insurance company. One of the tasks of the employees within this company is to extend life insurance policies that are about to expire. A task of utmost importance, one might say. The process is as follows. First employees check the current status of the policy and whether the policy needs to change. Then all denied policies are reported in an application called Keylane Axon. For all policies which are still in progress, various details need to be checked, such as the type of policy or the age of the client. After running all these checks, it is allowed to prolong the policy for one year.

Imagineably, carrying out these steps is very time-consuming, especially since one of the applications (Keylane Axon) is rather slow and forms a bottleneck in this process. Also performing the checks is a task that is prone to human error. Over a time period of a few months, a large number of policies has to be extended. The repetitive nature of the task is one that causes employees to be dissatisfied.

Months to ROI
Hours saved annually
Of effort automated
Implementation time (weeks)

Our solution: Saving hours and increasing satisfaction

After implementing our RPA-based solution, the repetitive process of extending life insurance policies is automated and performed by the digital workforce! Our goal was to offer a solution that is less sensitive to human error and reduce the workload of employees. We did this by building a robot that initializes two applications (Keylane Axon and an internal application) and then performs the following tasks:

  • Check whether changes in the policy are needed
  • If yes, check current status of the policy
  • If denied, create a failure task in QIS
  • If in progress, check client details (such as age or policy type)
  • Prolong policy and create task for next year

Our robot is able to automate 80% of the process and save over 2000 hours on a yearly basis! 

The implemented solution offers faster processing times, error reductions and cost savings, but more importantly, it increased the employees’ satisfaction.

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