Conference Programme
Insurance Data Science - Monday 16 July 2018
[08:30-09:00] Registration
[09:00-10:00] Keynote 1: Gareth Peters
[10:00-11:00] Session 1: Pricing / Claims modelling
- Sparsity with multi-type lasso penalties - Tom Reynkens
- Statistical analysis of weather-related property insurance claims - Christian Rohrbeck
- Claims frequency modelling using telematics car driving data - Mario Wüthrich
[11:00-11:30] Coffee
[11:30-12:30] Session 2: Lightning talks
- Machine learning for actuaries: An introduction - Valerie du Preez
- Truncated regression models for the analysis of operational losses due to fraud: A high performance computing implementation in R - Alberto Glionna
- Using Random Forest to estimate risk profiles and probability of breakdowns - Lara A. Neira Gonzalez
- Simulating economic variables using graphical models - Aniketh Pittea
- RShiny at Qatar Re: A business case study - Marc Rierola
- PnC reinsurance modeling using Python and TensorFlow - Pauli Rämö
- 'KSgeneral' : A package for fast, exact, Komogorov-Smirnov goodness of fit testing - Senren Tan
[12:30-13:30] Lunch
[13:30-14:30] Session 3: Capital and exposure modelling
- Statistical learning for portfolio tail risk measurement - Michael Ludkovski
- Reverse sensitivity testing: What does it take to break the model? - Silvana M. Pesenti
- Using R for catastrophe modelling of cyber risks in (re)insurance - Benjamin C. Dean
[14:30-15:00] Session 4: Panel discussion
[15:00-15:30] Coffee
[15:30-16:30] Session 5: Business Case Studies
- SFCR automated analysis using scraping, text mining and machine learning methods for benchmarking and capital modelling - Aurelien Couloumy
- Machine learning and fairness for commercial insurance - Oliver Laslett
- Getting value out of machine learning - Javier Rodriguez Zaurin
[16:30-17:30] Keynote 2: Eric Novik
[18:00-22:00] Reception drinks & Dinner
- Ironmongers' Hall
A PDF version of the full programme can be downloaded here
Please see below the programmes of previous R in Insurance conferences: