Have you ever tried booking a flight or vacation that was advertised for a great price, only to find out at check-out that an error occurred with their system and it was showing the wrong price? What about something as simple as going to a restaurant and getting served the wrong meal despite being specific when you ordered? In both instances, at some point in the process, the wrong data was transmitted in the system, creating a disappointing experience for you.
Now imagine this data mishap occurring in a reinsurance setting. What would happen if treaties were set up incorrectly and policies weren’t being administered according to treaty parameters? This could lead to incorrect Net Amount At Risk (NAR), product mapping, reinsurance premium rate and allowance percentages. And if you aren’t already thinking it… THERE COULD BE HUGE FINANCIAL IMPACT that compromises your ability to manage risk effectively.
That is why data quality and compliance is so critical to all parties involved in reinsurance. So how can you reduce the risk of major financial disasters and ensure data accuracy? By investing in quality control processes. Here is why.
1. Decisions are made based on data
Actuaries and managers in insurance industries are making decisions based on data they receive from administration units. Poor data quality can leave room for errors and potential mismanagement for both direct writers and reinsurers. Actuaries could potentially estimate incorrect mortality ratings, loss ratio or severity patterns. Inaccurate data could also impact the results of reinsurance experience studies and business analysis, and again lead to misinformed business decisions.
2. Reinsurance heavily depends on historical data
Not only is current data expected to be accurate but also historical data. The reinsurance industry relies heavily on historical data to make decisions around portfolio development, profitability of business, pricing and valuation. Again emphasizing the importance of data integrity and quality controls from day one. Making it a high priority ensures that at any given time anyone accessing the data has confidence in its accuracy.
Evidently having inaccurate data can lead to major negative consequences on numerous aspects of your reinsurance business. The way to reduce risk or mitigate damage if errors have been found, is to put in place proper quality controls. So what does this consist of? Find out here: 4 Checks & Tests to Improve Reinsurance Quality.
In the meantime, get a better understanding of our three step methodology - Assess, Improve, Maintain– that we use to ensure our clients have accurate treaty data.
How can you improve your data to ensure accuracy, consistency and improve overall reinsurance quality? We have 16 Pro Tips to do exactly that. Get them below!