Insurance Data Science Conference 2019

ETH Zurich, Switzerland

The second Insurance Data Science Conference at RiskLab (ETH Zurich) follows on from its first edition at Cass Business School (London) and five iterations of the R in Insurance conferences. This one-day conference is an exciting international event that brings together industry and academia in the fields of insurance and computer sciences.

The aim of this conference is to share and present the latest developments in the fields of insurance data science, statistical learning and machine learning. This includes technological developments, and mainly focuses on applications in insurance pricing, reserving, risk assessment and modeling, customer analytics, capital management, catastrophe and econometric modelling.

The two keynote speakers Joachim Buhmann (Professor of ETH Zurich) and Ronald Richman (Chief Actuary at AIG, South Africa) will be sharing their view of machine learning in insurance; a panel discussion with Sabine Betz (Swiss Association of Actuaries and Deloitte), Jeffrey Bohn (Swiss Re) and Volker Reinthaler (AXA) will be illustrating the future potential of this field; and we will have more than 30 contributed talks from industry and academia presenting the latest developments.

We are looking forward to seeing you at ETH Zurich on 14 June, 2019!

Objectives

Get together of leading experts from industry and academia
Sharing of new ideas and applications
Real life examples of data science in insurance

Key dates

10 March 2019

First programme
11 March 2019

Registration opens
11 April 2019

We are fully booked!
14 June 2019

Insurance Data Science Conference

Registration

Sorry, we are fully booked!

Programme

Conference Programme: Download Conference Programme
Abstracts: Download Abstracts of the Presentations
Call for Papers: Special Issue of the Annals of Actuarial Science on ‘Insurance Data Science’. Conference participants are especially invited to submit a paper to this special issue.

Organizer

Local organizers

Prof. Dr. Patrick Cheridito (ETH Zurich)
Prof. Dr. Mario Wüthrich (ETH Zurich)
Dr. Bastian Bergmann (ETH Zurich)
Ms. Galit Shoham (ETH Zurich)

Scientific committee

Katrien Antonio (KU Leuven and University of Amsterdam)
Patrick Cheridito (ETH Zurich)
Christophe Dutang (Université Paris Dauphine)
Guojun Gan (University of Connecticut)
Markus Gesmann (Lockton Re, London)
Ioannis Kyriakou (Cass Business School, City, University of London)
Davide de March (London)
Pauli Rämö (Mirai Solutions, Zurich)
Ronald Richman (AIG, South Africa)
Jürg Schelldorfer (Swiss Re, Zurich)
Giorgio Alfredo Spedicato (Unipol Group, Milan)
Andreas Tsanakas (Cass Business School, City, University of London)
Mario Wüthrich (ETH Zurich)

Recent Posts

Insurance Data Science: Call for abstracts open

3 Dec 2018 2 min read Announcement

The 2nd Insurance Data Science conference will take place at ETH Zurich, 14 June 2019. Following the launch in London at Cass Business School in 2018, we are inviting you to submit proposals for talks by 15 February 2019 to: [email protected] We are looking for abstracts in the fields of insurance data science, statistical learning and machine learning. This includes technological developments, and mainly focuses on applications in insurance pricing, reserving, risk assessment and modeling, customer analytics, capital management, catastrophe and econometric modelling.

Notes from the 1st Insurance Data Science event

24 Jul 2018 2 min read Events

The first Insurance Data Science event was held at Cass Business School last week, 16 - 17 July 2018. The conference followed on from five iterations of the R in Insurance events, which have the aim of bringing together practitioners and academics together to discuss and exchange ideas and needs in the sector. Expanding the remit from R in Insurance to Insurance Data Science has also attracted talks on Python and Tensorflow.

Welcome to Insurance Data Science

25 Nov 2017 2 min read Announcement

When we started the R in Insurance conference in 2013, we had the aim of bringing practitioners of industry and academia together to discuss, exchange ideas and needs from both sides. R was and is a perfect glue between the two groups, a tool which both side embrace and which has fostered the knowledge transfer between the two. However, R is just one example and other languages serve this purpose equally well.