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4 Checks & Tests to Improve Reinsurance Quality

August 23, 2016 / Reinsurance

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In my previous post I discussed two reasons why investing in reinsurance quality control processes are necessary. One, being that major decisions in the industry are made based on data and two, reinsurance is heavily dependent on historical data. Charles, my colleague also discussed this by comparing the Rio Olympic Games to the reinsurance industry.

We know why it‘s important but what can you do to ensure utmost data accuracy? What do your quality control processes look like, and how can you implement them effectively to improve your business?

As a reinsurance consultant, my day to day involves assisting both insurers and reinsurers in improving the quality of their data.  For professionals in the industry, here are four essential checks and tests you should consider incorporating into your reinsurance quality control processes.

These components are based off of our three-step methodology – Assess, Improve, Maintain - used to ensure the accuracy of our clients’ reinsurance treaties and data.

 

Trend Data Analysis

An analysis of data trends is essential for achieving quality data. It gives you the opportunity to locate issues that have not only created data errors but could also impact future compliance and calculations.  The key to this part of the quality control process is conducting an analysis not only from a historical perspective but also on an ongoing basis.  As I mentioned before, reinsurance heavily depends on historical data to make informed decisions so it is important that ALL DATA is accurate, as well.

Let’s walk through an example of poor data quality that you could potentially identify during a Trend Data Analysis.

Example 1: Incorrect Rates loaded into Reinsurance Administration System

Let’s assume that the Premium Rate Table indicated in the Treaty documentation is as follows:

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Upon importing these rates into the reinsurance administration system, a coding issue was noted. Instead of inserting the premium rates noted above, they were shifted up by one year for all ages in all duration as illustrated below:

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We’ve seen this problem (or similar data issues) occur. What are the results of this data error?

 As a result, the premium rates for each issue age will be used incorrectly. Unfortunately, the issue will go on until it is identified – which is why a full data analysis is so important.

Data Integrity Test

The next component to consider for quality control is a data integrity test. The purpose of this is to assure the accuracy and consistency of data over its life cycle. Reinsurance analysts can have more confidence in quality of data, once they ensure data integrity is under control. Here are some examples of how we determine data integrity during this part of the process:

  • Validate if all fields are being translated correctly into the life administration system.
  • Identify the existence of any duplication in the reported transactional data.
  • Examine if there is any mistranslation of data that is not consistent with your data dictionary.

Treaty Compliance

Another key component of reinsurance quality control is confirming treaty data compliance. When looking at a reinsurance treaty, this involves reviewing the ceding company’s operations and procedures. The goal is to make sure all policies within the reinsurance treaty parameters are ceded.

PRO TIP: Grab this quick question checklist to determine compliance during this component of your quality control process including:

  • Has the policy duration and reinsurance duration been calculated accurately?
  • Is residency covered under the treaty?

Download the full list of key questions here!

Premium Calculation Test

Premium calculation testing allows you to identify any premiums that are not being calculated appropriately. The key to this kind of quality control is to create different test scenarios that will be defined for Basic/Rider coverages and Individual/Joint cessions.

 Here are some scenarios you can test:

  • Evaluate the accuracy of Net Amount At Risk (NAR), Face Amount, Ceded Amount.
  • Verify if the right Rate Table and Rate Factors have been used for cession premium calculation.

For a FULL LIST of scenarios to test, download our pro tips for reinsurance quality control here

At the end of the day implementing quality controls in your reinsurance operations  will give you more reliable data to work with and increase your long term business profitability.

Need help building a quality control process or lacking the resources to execute? Start improving your processes by downloading our pro tips below!

Written by
Farzaneh Mashhadian