Add to ORKGIn our study case of a French insurance motor portfolio, we found that Gradient Boosting models have a stronger predictive performance and a higher pricing ability to adjust the premiums to both high risk and low risk profiles. And finally, we conclude that these models can be used to support and improve GLMs and their pricing results as Machine Learning continues to settle in the actuarial modeling paradigm.Máster Universitario en Ciencias Actuariales y Financiera
Most non-life insurers and many creditors use regressions, more specifically Generalized Linear Mode...
Insurance is a policy that eliminates or decreases loss costs occurred by various risks. Various fac...
One fundamental function of an insurance company revolves around calculating the expected claims cos...
In our study case of a French insurance motor portfolio, we found that Gradient Boosting models have...
International audienceAs the level of competition increases, pricing optimization is gaining a centr...
Free competition in the insurance markets increases the competitiveness and lowers the premiums. If ...
Mestrado em Actuarial ScienceO pricing na atividade seguradora está a tornar-se cada vez mais intere...
Abstract Insurance companies using risk modelling mainly focus on the mastery of Genelized linear m...
Boosting techniques and neural networks are particularly effective machine learning methods for insu...
This thesis explores the use of machine learning techniques in an effort to increase insurer competi...
Pricing models for car insurance traditionally use variables related to the policyholder and the ins...
We recently conducted a research project for a large North American automobile in-surer. This study ...
International audienceNon-life actuarial researches mainly focus on improving Generalized Linear Mod...
Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries....
Pricing an insurance product covering motor third-party liability is a major challenge for actuaries...
Most non-life insurers and many creditors use regressions, more specifically Generalized Linear Mode...
Insurance is a policy that eliminates or decreases loss costs occurred by various risks. Various fac...
One fundamental function of an insurance company revolves around calculating the expected claims cos...
In our study case of a French insurance motor portfolio, we found that Gradient Boosting models have...
International audienceAs the level of competition increases, pricing optimization is gaining a centr...
Free competition in the insurance markets increases the competitiveness and lowers the premiums. If ...
Mestrado em Actuarial ScienceO pricing na atividade seguradora está a tornar-se cada vez mais intere...
Abstract Insurance companies using risk modelling mainly focus on the mastery of Genelized linear m...
Boosting techniques and neural networks are particularly effective machine learning methods for insu...
This thesis explores the use of machine learning techniques in an effort to increase insurer competi...
Pricing models for car insurance traditionally use variables related to the policyholder and the ins...
We recently conducted a research project for a large North American automobile in-surer. This study ...
International audienceNon-life actuarial researches mainly focus on improving Generalized Linear Mod...
Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries....
Pricing an insurance product covering motor third-party liability is a major challenge for actuaries...
Most non-life insurers and many creditors use regressions, more specifically Generalized Linear Mode...
Insurance is a policy that eliminates or decreases loss costs occurred by various risks. Various fac...
One fundamental function of an insurance company revolves around calculating the expected claims cos...