Actuarial sciences and data sciences, R applications and theoretical reflexions.
Discussing data processing with R as weel as life or non-life actuarial models, with particular attention given to dependance structure modeling
Oskar Laverny is an actuary which has a taste for dependance modeling, copula and machine learning. He studied non-life reserving issues early in his carrer, mainly under solvency II, but he also studied (hierachicals) archimedeans copulas, with application in various fields : non-life reserving, Best-trade issue in reinsurance, simple pricing issues, solvency II underlying assumptions, life contengencies…
He also loves to program stuff : He did some Cpp, some web, but mostly he’s working with R and latex these days. He is of course a linux enthousiast and manage some arch and debian systems on a day-to-day basis.
Actuarial scientist diploma, 2018
French Actuarial Institute
Master's degree actuarial sciences, 2018
Bachelor in actuarial sciences, 2016
Bachelor in mathematics, 2015
After having specified the specificities of the French builder’s insurance and analyzed the problems posed by additional specific reserves to this line of buisiness, we recall basic models, deterministic and stochastic, used in non-life insurance. Having transcribed the main models in a larger mathematic framework, we present new models shaped for the tri-dimentional issue of French construction insurance, including the estimation of variability in every point of view. Then, through several different approaches, we derive Solvency II reserve risk estimators in those models, and conclude with an analysis of these estimators on a certain portfolio, shaped toward the standard formula.
A simple package that implement a one-year bootstrap in the Braun model, with extension to a mutli-year reserving case (french decenial insurance). Work done in the framework of my master thesis.
A shiny app that estimate and give some statistic about a bivariate copula given a bivaraite dataset.