Lucia Bevere – Senior Catastrophe Data Analyst, Swiss Re Institute

Lucia Bevere is the author of the annual sigma on natural catastrophes and man-made disasters. She has published eight sigma studies since 2005. In addition, she is responsible for the sigma catastrophe database, the only internationally available commercial catastrophe database to record natural catastrophes and man-made disasters.

She is member of the Working Group on Human and Economic Impact Characterization at the Centre for Research on the Epidemiology of Disasters-CRED of the Université Catholique de Louvain.

Lucia holds a Masters degree in Business Administration from the Università Bocconi – Milan, Italy.

Experience
  • 2000 – 2022 Senior catastrophe data analystSenior catastrophe data analyst, Swiss Re
  • 2012 – 2015 Integrated Research on Disaster Risk (IRDR) programme
  • IRDR Disaster Loss Data (DATA) Project Working Group
  • 1988 – 1997   Explorer Marketing Research

The Disaster Loss Data (DATA) project, under the umbrella of the Integrated Research on Disaster Risk (IRDR) programme, brings together stakeholders from different disciplines and sectors to study issues related to the collection, storage, and dissemination of disaster loss data.

The aim is to establish an overall framework for disaster loss data for all providers, to establish nodes and networks for databases, and to conduct sensitivity testing among databases to ensure some level of comparability.

Education
  • 1998 – 1999 City, University of London / MSc, Information Science
  •  1995   Università Bocconi
Latest reviews by Lucia Bevere
Role for Insurers & Reinsurers in Building Flood Resilience & Close Insurance Protection Gap" class="attachment-csco-thumbnail size-csco-thumbnail wp-post-image" alt="Role for Re/Insurers in Building Flood Resilience & Close Insurance Protection Gap">
Role for Re/Insurers in Building Flood Resilience & Close Insurance Protection Gap
Today risk assessors use a wide set of tools ranging from sophisticated flood hazard maps to fully probabilistic risk models, but more can be done