Personalization as a promise: Can Big Data change the practice of insurance?

Our recent article, “Personalization as a Promise: Can Big Data Change the Practice of Insurance?” with Larence Barry just got published in “Big Data & Socierty” (but a working paper version is still available online)

The purpose of this paper is to measure the impact of technologies from the Big Bang. data on thehe pricing ofhe products car insurance. The first part describes how the aggregated view buildsuit by statistics enables highlighting invisible regularities at the individual level. Despite a very granular segmentations in automobile insurance, the approach remained classificatory, hypothesizing the risk identity of individuals from the same class. The second part highlights the reversal of big data-induced perspective in the’analysis ofgiven ; awith theur volume and the new algorithms, the aggregate viewpoint is questioned.. The hypothesis of class homogeneity is becoming increasingly difficult to test. maintain, especially since predictive analysis boasts the ability to predict the rs results at the individual level. The third part is studying the’influence of telematics boxes able to import the new pinsurance aradigm automobile. However, a reading of the most recent research articles on a pricing automobile including this new monter that the epistemological leap, at least for now, has not taken place.

Modeling Joint Lives within Families

With Olivier Cabrignac and Ewen Gallic, we recently uploaded a research paper, entitled “Modeling Joint Lives within Families

Family history is usually seen as a significant factor insurance companies look at when applying for a life insurance policy. Where it is used, family history of cardiovascular diseases, death by cancer, or family history of high blood pressure and diabetes could result in higher premiums or no coverage at all. In this article, we use massive (historical) data to study dependencies between life length within families. If joint life contracts (between a husband and a wife) have been long studied in actuarial literature, little is known about child and parents dependencies. We illustrate those dependencies using 19th century family trees in France, and quantify implications in annuities computations. For parents and children, we observe a modest but significant positive association between life lengths. It yields different estimates for remaining life expectancy, present values of annuities, or whole life insurance guarantee, given information about the parents (such as the number of parents alive). A similar but weaker pattern is observed when using information on grandparents.

The paper is online on https://arxiv.org/abs/2006.08446.

INF7100, prédictions

La troisième (et dernière) partie de mon intervention sur la science des données, dans le cadre du cours INF7100 portera sur une introduction aux modèles prédictifs. Le plan sera le suivant

  • 311: Corrélation pdf video (8:35)
  • 321: Régression Simple pdf video (30:01)
  • 322: Régression Multiple pdf video (37:16)
  • 331: Lissage pdf video (37:35)
  • 341: Régression Quantile pdf video (32:00)
  • 351: Classification (analyse discriminante, régression logistique) pdf video (27:29)
  • 352: Courbe ROC pdf video (22:52)
  • 361: Application de la Régression [je ne sais pas si j’aurais le temps de faire l’application]
  • 371: Application de la Classification (images) pdf video (18:15)