When Artificial Intelligence comes up, it often conjures up thoughts about robots, lost jobs, and complex systems that - at first glance - can seem impossible to grasp. However, a large component that can be overlooked is the time dedicated towards teaching artificial intelligence and machine learning what you want it to. As we’ve emphasized before, the people and expertise behind the technology play a crucial role in driving the direction of usage, training, implementation, quality assurance and more.
Across the industry, insurance professionals are looking for new ways to innovate their processes, services, and solutions for better management and business outcomes. Agile project management/methodology can be used to generate new ideas, elevate productivity, and accelerate product innovation.
Tackling a reinsurance treaty can be a comparable experience to tackling an obstacle course. You’re not sure when a surprise will pop up, there is little consistency between obstacle courses and it can be down right frustrating when you can’t find what you are looking for.
What are the risks of having inaccurate treaty data in your reinsurance administration system? Are those risks top of mind for actuaries? While the impact of inaccurate treaty data might not be apparent on a day-to-day basis, over the long term, they present serious risk for insurance companies.
As life reinsurance professionals, we know that reading and interpreting a treaty is no easy task. While treaty language has progressed over the years, to a more standardized language, the older agreements are still relevant in today’s reinsurance eco-system. On any given day, reinsurance analysts could be working with treaties that look very different from one another. The lack of consistency makes it increasingly harder to accurately interpret the intentions of treaties. When intent and clarity are not clear, misinterpretations occur which can put your company at risk. Find out what happens when treaty language is misinterpreted, why it occurs, and how to prevent it from happening.
The reinsurance industry relies on processing accurate treaty data. Yet, in many cases, treaty information is misfiled, misunderstood, or even missing. Which is a huge risk because if your organization is processing erroneous data, it can lead to large financial adjustments. Reviewing treaties allows you to validate that reinsurance is being processed accurately and identify errors that could be causing financial issues. So when is it the right time to conduct a treaty review? Like many things in life, there is never a 'right' time. It really depends on a reinsurance company's current state, business strategy, operations and processes to name a few. Based on our experience, we've identified the most common scenarios reinsurance companies approach us to conduct treaty reviews below.
Now that you've had an introduction to the Frasier method including what to consider when using it and when errors commonly occur, I'm hoping the concept is a little less scary to you. As I mentioned in my previous blog, reinsurance analysts usually fear the Frasier method because of the potential for errors. But what is the best way to address a fear? Take it head on (at least for some!). When it comes to Frasier, this means getting an understanding of where the most common errors can occur.