Triangulation reports are at the heart of Insurance domain, and are consumed by key stakeholders like Underwriters and Actuaries for technical analysis. Good triangulation analysis results in accurate Premium calculations, optimal Reserving and more. It differentiates the best from other good players in the industry.
Traditional Insurance products might offer Actuarial Return reports or Triangulations as part of their off-the-shelf features. But, usually they are less flexible with limited control options for the user. Alternately, claims data can be pulled out and analysed in Microsoft Excel. While this approach might offer more control to the technical user, it is usually more laborious and still somewhat old-fashioned considering the mighty powerful tools available in today’s Data Science market.
With these factors in mind, below are a few interesting questions that confront us.
- Are old-fashioned legacy products and methods being still applied in a field that is swiftly undergoing disruption?
- What if the Triangulation reports can be made dynamic at the user’s fingertip for instant access?
- Can triangles be linked with dimensions like State, Industry, Claim Type, Cause, Litigation Status and the many other useful pieces of information that we have in our repository? That would allow users to slice and dice the triangles and compare loss developments for different parameter combinations.
- Can the user be enabled to drill into a particular cell in the triangle and see what claims, damage types etc. exactly make up that total loss figure in that cell?
- Will the user be able to sort / filter this data behind the scenes to further interrogate the factors that total up to that loss figure? That would tell why exactly losses spiked up in certain periods, and what resulted in estimates being downsized in others.
- Would it be possible to easily switch across different variants of the same triangulation data – absolute loss for each period, running total of loss over the years & percent of running total? While underlying data is the same, each view provides ease for answering certain types of questions.
- Can the user start with a yearly view by default and then be able to drill down from there to a quarterly or monthly view by row or column?
- Is it possible to connect all of these features to a Live database so the user will not have to manually refresh data periodically for recurring analysis?
A lot of questions, to be sure. If you are accessing Proclaim’s Data Services, there is a single resounding answer to all of these questions; YES. Proclaim has taken its Power BI Insights implementation to the next level with the launch of Triangulation. At any point in time, Triangulation dashboard reflects data as of the previous day. It goes hand in hand with many other dashboard templates launched in recent months. While the other dashboards deal with financial figures rolled up at Claim level, Triangulation breaks them down to individual estimate and payment transactions and allows for much deeper technical analysis.
When the going gets tough, more precise data-driven insights can keep you ahead of the pack!