Add to ORKGThis paper uses a method proposed by Boskov & Verrall (1994) for premium rating by postcode area. The aim is to analyze geographical variation in claim frequencies in order to estimate the local risk in each geographical area and to build homogeneous rating regions. The method accounts for spatial correlation in an hierarchical Bayesian framework and uses computer-intensive MCMC methods for statistical inference
Generalized additive models for location, scale and, shape define a flexible, semi-parametric class ...
Generalized additive models for location, scale and shape define a flexible, semi-parametric class of ...
Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, M...
Territory design and analysis using geographical loss cost are a key aspect in auto insurance rate r...
The average insurer typically utilizes some form of territory ratemaking in its algorithm; thus. in ...
Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology ...
Spatial models, such as the Besag, York and Mollie (BYM)model, have long been used in epidemiology a...
Pricing using a Generalised Linear Model is the gold standard in the auto insurance industry and rat...
In this paper models for claim frequency and claim size in non-life insurance are con-sidered. Both ...
Clustering methods are briefly reviewed and their applications in insurance rate-making are discusse...
This work compares several hierarchical Bayesian techniques for modelling risk surfaces by multivari...
The third-party motor insurance data from Sweden for 1977 described by Andrews and Herzberg in 1985 ...
In this paper models for claim frequency and claim size in non-life insurance are considered. Both c...
We analyze telematics data from a Belgian portfolio of young drivers who underwrote a pay-as-you-dri...
An important prerequisite for running a successful insurance business is to predict risk. By forecas...
Generalized additive models for location, scale and, shape define a flexible, semi-parametric class ...
Generalized additive models for location, scale and shape define a flexible, semi-parametric class of ...
Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, M...
Territory design and analysis using geographical loss cost are a key aspect in auto insurance rate r...
The average insurer typically utilizes some form of territory ratemaking in its algorithm; thus. in ...
Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology ...
Spatial models, such as the Besag, York and Mollie (BYM)model, have long been used in epidemiology a...
Pricing using a Generalised Linear Model is the gold standard in the auto insurance industry and rat...
In this paper models for claim frequency and claim size in non-life insurance are con-sidered. Both ...
Clustering methods are briefly reviewed and their applications in insurance rate-making are discusse...
This work compares several hierarchical Bayesian techniques for modelling risk surfaces by multivari...
The third-party motor insurance data from Sweden for 1977 described by Andrews and Herzberg in 1985 ...
In this paper models for claim frequency and claim size in non-life insurance are considered. Both c...
We analyze telematics data from a Belgian portfolio of young drivers who underwrote a pay-as-you-dri...
An important prerequisite for running a successful insurance business is to predict risk. By forecas...
Generalized additive models for location, scale and, shape define a flexible, semi-parametric class ...
Generalized additive models for location, scale and shape define a flexible, semi-parametric class of ...
Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, M...