By Philippe Torres
Toronto, ON (Jan. 7, 2015) – Distilled to its minimum, ratemaking involves just three basic activities: segmenting the Book of Business, setting rate assumptions, and simulating the proposed rating environment.
Variations on this basic form of the activity are repeated, day in and out, by actuaries and data analysts, with the results gone over with a fine toothed comb. Obviously, anything that improves the efficiency of ratemaking or any of its associated activities would be a great boon to all involved. But first you have to identify the problems.
The place to start looking is with the actuarial staff. This is where limitations, restrictions and inefficiencies in ratemaking are first felt. When actuaries have difficulty fleshing out “what if” scenarios, drilling down into the re-rated Book of Business or experience frustrations performing dislocation analysis, it is a sign that things are not all they should be. But if the problems are first seen at the actuarial level, they quickly percolate up to the top, making it more difficult for insurers to identify new market segments, to know when to reduce exposure in less profitable areas, or when to eliminate offerings altogether.
Consider the following list as a starting point for discussion. Our research has identified these as the main hindrances to smooth sailing in the P&C rating development process.
- Difficulty in Segmenting the Book of Business: Actuarial databases are often sets of “flat” data files, created and maintained using a programming language such as SAS. There is something to be said for a stripped down approach. Unfortunately, this one is not terribly friendly to segment extractions or performing further analysis.
- Heavy Programming: The rate development process typically requires a great deal of programming. This results in delays and reduces the number of ratemaking cycles undertaken over any given period of time.
- Missing Components and Poor Analytical Environment: Very often, the rate development framework is missing a piece. For example, analysts typically do not have access to an analytical environment for Dislocation Analysis. They cannot easily drill down into the re-rated Book of Business. The ability to test rating assumptions or rate changes may be entirely lacking. When a piece is missing, the insurer is forced to make an educated “best guess” at the expected experience with new rates or rules.
- Incomplete Set of Historical Data: There may be important new rating attributes that do not exist in the historical Book of Business – because they were never captured by the support systems in the first place. This lack of completeness forces more programming to circumvent data limitations while supporting new rating assumptions.
- Islands of Rating: Sometimes impressive rating technologies already exist in the enterprise, but they are not being leveraged by the rate development process. A rating engine may exist, but only for production rating, for example. As a result, actuaries are forced to re-create functionality and rules that are already deployed elsewhere.
Do any of them sound familiar? You are not alone. These are very common problems in ratemaking, and most insurers have to admit to experiencing one of more of them at different times.
With the problems identified, what is the solution? The solution lies in focusing on the actuarial experience and “rebuilding” it, re-imagining it, leveraging it with a sophisticated addition to the analytical framework called an on-level analytical application. It has a number of distinguishing characteristics, each designed to ease the ratemaking process. For starters, it includes an analytical environment that is absolutely driven by the metadata. It is also a fundamentally visual environment that reduces, sometimes completely eliminating, the need for programming. Moreover, it adapts to the rating engine and corporate cultural practices already in place.
This is some of what is delivered by the new class of analytical tools called on-level analytical applications, visual tools that greatly simplify previously complex ratemaking tasks, opening up new possibilities in the P&C rating development process.
For further details on how an on-level analytical application addresses the most common limitations in ratemaking, read the white paper: Three Characteristics of Successful Insurance Analytics Rating Solutions.
About the Author
Philippe Torres is a founding partner of InEdge, a solution provider specialized in Insurance Analytics. Prior to co-founding InEdge, Philippe’s over 25-year career has included work at Sybase and then Sun Microsystems as a Solutions Architect. He has unique expertise in the areas of analytical solutions, the personal lines and general insurance industries, as well as R&D in the field of data warehousing and Analytics.
InEdge is a leader in Insurance Analytics solutions. Experienced at quickly leveraging data, InEdge seamlessly and powerfully creates business advantage for its clients. Since its creation in 1994, InEdge has designed and implemented some of the most sophisticated analytical applications available today. Our clients add up to an impressive roster of Property & Casualty and Life Insurance companies. Our Analytics solutions improve and make easier decision-making at all levels for our clients.