- Sparsity with multi-type lasso penalties - Tom Reynkens [slides]
- Statistical analysis of weather-related property insurance claims - Christian Rohrbeck [slides]
- Claims frequency modelling using telematics car driving data - Mario Wüthrich [slides]
- Machine learning for actuaries: An introduction - Valerie du Preez, Steven Perkins [slides]
- Truncated regression models for the analysis of operational losses due to fraud: A high performance computing implementation in R - Alberto Glionna [slides]
- Using Random Forest to estimate risk profiles and probability of breakdowns - Lara A. Neira Gonzalez [slides]
- Simulating economic variables using graphical models - Aniketh Pittea [slides]
- RShiny at Qatar Re: A business case study - Marc Rierola [slides]
- PnC reinsurance modeling using Python and TensorFlow - Pauli Rämö [slides]
- 'KSgeneral' : A package for fast, exact, Komogorov-Smirnov goodness of fit testing - Senren Tan [slides]
- Statistical learning for portfolio tail risk measurement - Michael Ludkovski [slides]
- Reverse sensitivity testing: What does it take to break the model? - Silvana M. Pesenti [slides]
- Using R for catastrophe modelling of cyber risks in (re)insurance - Benjamin C. Dean [slides]
- SFCR automated analysis using scraping, text mining and machine learning methods for benchmarking and capital modelling - Aurelien Couloumy [slides]
- Machine learning and fairness for commercial insurance - Oliver Laslett [slides]
- Getting value out of machine learning - Javier Rodriguez Zaurin [slides]
- Announcement Insurance Data Science conference 2019 - Mario Wüthrich