Automated reinsurance capacity check

Case study

Automated reinsurance capacity check

The reinsurance process is crucial to the continuous success of insurance companies. It involves substantially high transaction values that run into billions of dollars every year. In spite of being vital, in financial and operation terms, insurance companies have not made adequate investments in technology and data systems.

As a result, the manual processes related to data analysis and contract administration have become increasingly difficult and lead to inaccurate outcomes. Automating labor-intensive processes may help in implementing a robust reinsurance program that is responsive and at par with today’s technology needs.

Requirements

Our client is a $6 billion, international insurance intermediary firm that specializes in insurance/reinsurance broking, MGA services, and insurance underwriting. They wanted to improve their reinsurance capacity check process before taking risks with insurance companies.

Challenges

Some of the challenges involved in the reinsurance process are:

  • Manual reinsurance capacity evaluation process was repetitive and highly prone to human error.
  • Manual calculation of the total value of the reinsurance contract was inaccurate or missing and time consuming.

Solution

Earlier, the reinsurance capacity check process involved manually extracting client information and order value, from emails. The data would then be fed into the Capacity Checker system to validate the available reinsurance capacity.

Imaginea came up with an RPA solution, coupled with OCR (Optical Character Recognition) capabilities. This enabled the automation of the reinsurance capacity check process. RPA bots were provided access to mailboxes to process and extract the data using UiPath’s OCR engine to populate relevant fields in the reinsurance capacity check system.

The bots use keywords to extract the required information from emails, and then upload data into the reinsurance capacity check system. The data is validated against the capacity checker logic. After data validation, the bot sends an automated email based on a standard template stating the capacity check result. For example, the result would be marked as ‘can be taken up’ if the data is valid for reinsurance. Based on this result, brokers can take a decision. The diagram below illustrates how data is extracted and processed through our solution:

Tech stack

How our solution helped

95% automation of the reinsurance capacity check process led to 60% reduction in TAT (Turnaround Time).

Overall approach

We decided to use reusable worklets for automation. These worklets are tiny independent testable workflows that can be easily integrated into any process. The worklets were used to replace manual intervention in the identified processor lines of the reinsurance capacity check process. We defined the ‘why, what and how’ of the processes that can be automated:

  • The first step was to identify the process and determine the RPA goal. Here, the goal was to reduce the turnaround time for the reinsurance capacity check process and the possibility of human intervention.
  • Identify the steps in the process that can be automated. There were three manual data entry steps from source to destination. Hence, these steps were identified to be automated.

Results

  • Substantial reduction in reinsurance capacity check processing times.
  • Automation drastically reduced human error to less than 2%.
  • Brokers are now able to focus on their core activities, instead of manually creating reinsurance quotes.

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