The Center of Excellence Non-Life offers cutting edge expertise in methods, tools and models for Non-Life companies, combined with a deep knowledge of market best practices, acquired via our various assignments and surveys. Aside from our assignments, we also propose advanced trainings and tools.
Reacfin can help you to improve profitability through pricing that’s based on deep analysis of the underlying risks and portfolio. Taking into account your strategy (eg. focus on margins or looking for premium, reducing the risks, …) we will help you designing the ideal pricing structure.
Non-Life Centre of Excellence can provide support at all stages of the pricing process, from the data analysis to the final commercial price settings.
Reacfin has developped user-friendly tools and solutions to support insurance company in the different phases of the pricing set up. – see OnlineApp section
You want to extract key variables among the huge sets of available covariates which are now at disposal in insurance companies has become a huge challenge? Reacfin can help you on these aspects using advanced machine learning techniques.
A priori pricing
You want to avoid anti-selection effects ? You want to get the best business at the right price? You want to be competitive on specific risks?
Non-life Centre of Excellence team has abilities to build advanced predictive models on complex datasets. Our team is familiar with both machine learnings (Regression Tree, Random forest, Gradient Boosting Methods, Neural networks…) and traditional statistical models (Generalized Linear models, Generalized Additive Models, Generalized Linear Mixed Models, Advanced Credibility techniques for experience rating).
Geographical analyses the effect of geographical area on risk through a range of sophisticated spatial analysis methods and smoothing techniques.
A posteriori pricing
Reacfin can also support insurance companies in development of a posteriori pricing models using credibility techniques or developing Bonus-Malus scales.
Commercial price settings (and pricing optimization)
In the dispersion analysis phase, the impact of potential pricing decisions on volume, profitability and other key performance indicators are compared. The customer behavioral models (eg. Elasticity and/or conversion models if available), the technical models and the competitor prices are combined together in order to design the most appropriate rate using different scenarios.