Related Event

Event Summary

Organization: BMZ, DFID, InsuResilience Global Partnership, and World Bank

Description

Thursday, May 17, 16:30 – 18:00

Opening 
  • Rachel Turner, Director for Economic Development and Europe, DfID
  • Thomas Helfen, Head of Unit, BMZ
Launch DFID–GFDRR Challenge Fund on Disaster Risk Finance

Nicola Ranger, DFID

Pitch sessions: Problems and innovation
Government representatives pitch problems that they face in risk financing and which they hope big data and machine learning can help address:

  • Indonesia – Mr Fatchur Berlianto, State Asset Management, Ministry of Finance
  • Morocco – Mr Abdeljalil El Hafre, Treasury
  • Philippines – Ms Paola Alvarez, Assistant Secretary, Department of Finance
Private sector organizations will pitch their work and potential innovative solutions for risk financing.

  • One Concern – Ray Mueller, VP Government
  • Global Parametrics – Jerry Skees, Founder, Chief Strategy Officer and Director
  • Metabiota – Nita Madhav, Head of Data Science

Overview

Data plays an integral part in disaster risk management through enabling quantitative financial analysis to better inform decision making. Big data and machine learning offer the potential to transform policy design and risk management practices by providing more visual and more engaging risk information.

The application of big data (e.g. satellite, social and news media, mobile and texts, apps, community-based) and machine learning has the potential to revolutionize disaster risk management at every step of the process. Before an event, large datasets help better understand and model risk through large-scale asset and exposure data collection, near real-time hazard mapping, identification of patterns, early-warning and forecast capability and improved risk visualization techniques. During a disaster, the understanding of the severity and extent of a loss event can be processed from a larger variety of data sources (e.g. climate, commodity, market, political risk information or cell phone data for food insecurity), offering insights into impact-level risk transfer solutions. After a disaster, those technologies could also help improve the loss adjustment and claims settlement process to accelerate payouts of indemnity insurance or to refine understanding of parametric payouts.

Overall, the underlying key benefit is more accessible, more engaging and more visual ways of communicating and addressing disaster risks, thereby helping raise awareness, better support decision-making and financing solutions.