With the 2016 Rio Olympics well underway, all eyes are on athletes from around the world. While we get to see the performance of their lives, we can sometimes forget about everything that goes into it beforehand. Training is an obvious factor that prepares athletes for the Olympics, but another key factor you may not think of is data. In fact, the Rio Olympic Games are expected to be the most data-driven games so far. Almost every aspect of the games will rely, to some extent on data capture – but what I find particularly interesting is the way it is used to help improve athletic performance and create a better user experience for the audience (you and me).
The relationship is similar to the one that reinsurance professionals have with data. Using it helps reinsurance businesses perform better, which ensures that the stakeholders involved (direct writers and the reinsurer) have a positive experience. Just as data integrity is crucial to Olympic athletes, it is absolutely critical to reinsurance business as well.
Data integrity starts with the reinsurance treaty
In reinsurance, effective and efficient data integrity starts with the understanding of the treaty and making sure there is compliance with the agreement. Similarly, athletes need to understand the Olympic rules for their sports. Although the majority of reinsurance within the North American market is self-administered, the responsibility of ensuring the validity of data being transferred falls upon both the direct writer and the reinsurer.
Relationships between direct writers and reinsurers are critical to data integrity
Needless to say, the relationship between the companies is critical to the success of the business. The reinsurer needs to be comfortable with the administrative processes, systems being used and the knowledge and expertise of the folks administering the business. Given that the industry deals with such large volumes of data, those administrating the business should be experienced and knowledgeable in doing so.
How can inaccurate data compromise your business?
Imagine what would happen if athletes were given the wrong data about the track they were about to race, the stats of the team they were competing against or the height of the diving board? Having inaccurate data could compromise their chances of winning a medal. As reinsurance professionals we too strive for gold as inaccurate data could have major financial impact and compromise the risk of the reinsurance block.
Despite efforts to ensure the accuracy of data including reviews, audits, and analysis of data received from the ceding company, treaty data can still be misfiled, misunderstood or even go missing. In an environment where products are ever-changing, are harder to find, and companies are competing for profits and market share, the stakes are too high not to ensure data integrity. The possible financial impact is real and what may seem to be a minor clerical error could end up costing millions.
So what are examples of risks associated with compromised data?
Incorrect name verification and D.O.B can impact the retention amounts as well as potentially affect claims management.
Incorrect premium rate tables being used can cause the over or under payment of premiums to the reinsurer. This could potentially go on for many durations where principle and interest are a factor.
Incorrect use of quota-share percentages can impact claims and premiums.
Ceding business mapped to incorrect treaty codes can create a financial impact and cause unnecessary administrative headaches (e.g. allowances).
Not conforming to the issue age parameters as stated in the treaty can lead to business being covered that should have fallen outside of the scope of the agreement.
To mitigate these risks, processes need to be put in place to identify and correct before you find yourself in the 15th or 20th policy duration. The ability to identify and correct data in a timely fashion will decrease the likelihood of losses and enable management to make sound business decisions, which should contribute to more profits.
How do we minimize these risks?
Every day our reinsurance analysts and administrators work to substantially minimize the risk of data errors. For example:
- During our comprehensive review of the actual treaty and amendments, we capture and validate all critical data to confirm compliance within the agreement (from the treaty setup to the payments of premiums).
- We also validate the time period in question and test if the allowances tables, factor tables, quota share percentages and retention tables are correct according to the terms of the paper treaty.
If you rely on data (whether you are a reinsurance professional or an Olympic athlete) you need to have processes in place to identify inconsistencies or discrepancies. Here are four essential checks and tests to incorporate into your reinsurance quality control processes.