Schedule of Seminar IA|BE : Artificial Intelligence
|On Tuesday 24 September:|
|9:30 - 10:00||Reception|
|10:30 - 11:00||From needs to solutions by Philippe Afendulis, Wikitree|
|11:00 - 11:30||The insurtech landscape by Dave Remue, Fin-Tech|
|11:30 - 12:00||Actuaries 2.0.by Kris Claessens, Thewave|
|12:00 - 13:30||Lunch break|
|13:30 - 14:00||The end of myths by Jerome Fortias, BrightKnight|
|14:00 - 14:30||The market of solution providers by Pascal Deschryver, IBM|
|14:30 - 15:00||D & A driven insurance by Sudaman Thoppan, Allianz Benelux|
|15:00 - 16:00||Coffee -Tea Break|
|16:00 - 16:30||Fraud detection using analytics by Tim Verdonck, KU Leuven & UAntwerpen|
|16:30 - 17:00||D&A in changing industry by Isin Ozaksoy, Reinsurance Group of America|
|17:00 - 17:30||The view of EIOPA by Julian Arevalo, EIOPA|
|17:30 - 18:00||Closure - Cocktail|
From 10:30 to 11:00
From needs to solutions by Philippe Afendulis, Wikitree
Don't try to find out how AI can help you. Ask yourself what your needs aren and AI will help you !
From 11:00 to 11:30
The insurtech landscape by Dave Remue, Fin-Tech
How insurtechs and insurance companies can enhance each other. Update on regulators in Europe and beyond working towards a harmonised approach in AI.
From 11:30 to 12:00
Actuaries 2.0.by Kris Claessens, Thewave
Maturity of different AI domains for insurance and the impact over time of AI on insurance profiles.
From 13:30 to 14:00
The end of myths by Jerome Fortias, BrightKnight
For a mature and pragmatic approach to AI.
From 14:00 to 14:30
The market of solution providers by Pascal Deschryver, IBM
Deploying a D & A solution in an insurance company, from theory to practice.
From 14:30 to 15:00
D & A driven insurance by Sudaman Thoppan, Allianz Benelux
AI still at its infancy, the next challenges to come and what is in it for insurance companies.
From 16:00 to 16:30
Fraud detection using analytics by Tim Verdonck, KU Leuven & UAntwerpen
Financial institutions increasingly rely on predicitve machine learning models to detect fraudulent transactions. Two main challenges when building a supervised tool for fraud detection are the imbalance or skewness of the data and the various costs for different types of miscalissification. We discuss techniques to solve the imbalance issue and present a cost-sensitive logistic regression algorithm.
From 16:30 to 17:00
D&A in changing industry by Isin Ozaksoy, Reinsurance Group of America
Adjusting to change and the role of Advanced Analytics.
From 17:00 to 17:30
The view of EIOPA by Julian Arevalo, EIOPA
Big Data Analytics in motor and health insurance: a thematic review.