IAA Colloquia 2017

Ci-joint un prospectus relative aux 3 colloques organisés cet année par les sections de l’IAA.

Ne manquez pas cette opportunité de rencontrer des actuaires du monde entier pour échanger sur les derniers développements scientifiques de notre profession.

A journey into data science for Swiss actuaries - delivered by data scientists

We are announcing a series of trainings directed to the Swiss actuarial community and focused on Data Analytics related topics. The series consists of 4 one-day workshops in which participants will gain hands-on experience in some of the main data analytics methods & use cases applied to insurance industry topics. A key aspect is that these workshop-style sessions are not intended to be of a scientific lecture style, but rather a pragmatic series of sessions, in which participants will work with their own laptops and gain a good understanding of the relevant methods by doing (programming, modelling, etc.) and their application to insurance specific problems. Basic programming skills are therefore required. We intend to run these workshops in a friendly environment where questions are not only allowed, but highly appreciated.

All seminars will be held at Swiss Re, Mythenquai in Zurich.

Weiterbildungsreihe "Produkte après-midi"

Thema: Produktlandschaft Lebensversicherung: gestern, heute und morgen

Ausbildungszyklus "Pension Assets"

Vermögensbewirtschaftung für Verantwortliche in der 2. Säule

3 Nachmittage mit 6 Themenblöcken

Walter Saxer Versicherungs-Hochschulpreis 2016

Einladung zur Preisfeier

30th International Summer School of the Swiss Association of Actuaries (2017)

30th  International Summer School of the Swiss Association of Actuaries (2017)

Topic: Insurance Management: Trends, Challenges and Solutions

Excursion du Groupe des Dames

Lors de cette visite nous aurons le privilège d’assister aux débats du Conseil national depuis les tribunes.

Machine Learning in Insurance Analytics

Machine learning methods are very powerful statistical tools to analyze high-dimensional and complex data and to improve statistical models in insurance. We present two simple methods: the regression tree (supervised learning) and the K-means clustering algorithm (unsupervised learning). We illustrate these methods with different examples in insurance pricing, telematics data, individual claims reserving and mortality modeling.


Actuarial Pricing and Reserving using R

Michel Denuit, UCL, Louvain-la-Neuve, Belgium
Julien Trufin, ULB, Bruxelles, Belgium
SAV-CPs: 15

International Congress of Actuaries

The European Actuary

Université de Lausanne - Séminaires DSA