I gave a presentation on a holistic approach to ratemaking using predictive models yesterday to the Lebanese Insurance Association (ACAL, the acronym for the association in French). Over a hundred people attended, and there certainly seemed to be interest in the topic.
A common response though was that Lebanon isn’t yet ready for that, because rates are so low and nobody is prepared to change their approach. I accept that changing the “way things are done” in a fundamental way takes time and courage, but I expect that some players will start collecting the data, doing the analysis and improving their pricing in the next few years. By 2013, the market here will not be the same. The advantages across general insurance, banking, sales and cross-selling are simply too great. The techniques available are fantastic and can be implemented quite easily.
Insurance companies can generate a competitive advantage through accurate ratemaking, systematic risk-adjusted pricing, and careful analysis of policyholder price sensitivity at renewal dates. Single variable techniques can provide valuable insights into risk factors, but do not perform well in the presence of multiple drivers of risk.
Generalised Linear Modelling (GLM) is the preferred approach for robust, multivariate analysis of claim severity and frequency modelling. GLM can model several rating factors simultaneously, including interactions between different rating factors on risk. It is used extensively in the UK, the US and other highly competitive and developed insurance markets.
Judgement and experience are required when assessing different models and interpreting the diagnostic tests used to ensure accurate and robust results. A good model can make dramatic improvements in the separation of high and low risk policyholders.
These advanced approaches all have increased data requirements. Companies looking to reap the rewards of improved ratemaking will need to develop the databases and systems to store exposure, claims and rating factor data. There is a range of software available to perform the statistical analysis, from expensive purpose-built systems to freely available, open-source statistical platforms.
Successful implementation of an advanced rating system depends on commitment of key staff to the project and the inclusion of marketing, underwriting, legal, IT and actuarial skills in the project team. Market characteristics and reluctance to change are constraints to the adoption of advanced techniques. These have been faced and overcome in many other markets. It is only a matter of time before insurers must use these techniques even to maintain their competitive position. Early movers will enjoy an improvement in their competitive position, market share and profitability.