- FIXING DATA: Out-of-sample predictions of missing values with machine learning algorithms can help close data gaps in a wide range of insurance specific dataset
- MAKING DATA ACCESSIBLE: ML-driven data curation algorithms can transform non-intelligible data-streams into accessible and explainable ontologies that underwriters can leverage to take informed decisions
- MAKING DATA USEFUL: ML-curated data allows insurers to move from classic Generalised Linear Models to more accurate, data driven, risk assessment, thus implementing automated, data-led underwriting.
Alicia Montoya – Head Research Commercialization | Swiss ReAlicia joined Swiss Re in 2012, driving innovation, product development, and commercialization of solutions that address some of the world’s biggest risks, from climate change and natural catastrophes to sustainable energy, food security, infrastructure and transportation. She leads Swiss Re’s Quantum Cities™ initiative, using tech to foster sustainable economies and societies.
October 15 @ 15:00
15:00 — 15:20 (20′)
Day 1 | M8 | Machine And Deep Learning Stage
Alicia Montoya | Head Research Commercialization| Swiss Re