Data Science for Insurance

Learning Goals

The student will obtain a general understanding of the nature and relevance of Big Data for today’s Insurance Industry as well as a knowledge of common risk measures and the main statistical tools to handle dependence in the insurance and financial fields.

Program in pills

Data Management. Principles of data design. Data hunt, design, implementation. Risk and copula theory: Definition of risk, risk factors, and loss distributions, Basics of multivariate modeling with copulas; risk aggregation and correlation fallacies.

Area

Multidisciplinary, Ethical-Judicial-Social Knowledge and Applications

Curriculum Foundations
TAF Type

Curriculum Industry
TAF Type

Curriculum Health
TAF Type

Curriculum Economy
TAF Type

C

SSD

SECS-S/01

ECTS

6

Semester

2

Lecturers

Roberta Pappadà
Felician Leonardo