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Challenge 1 big data and cash

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#emergencydatascience
Dec 4-5, 2018 | York University

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Challenge 1 big data and cash

  1. 1. TakingAdvantage of Cash Delivery Data ChallengepresentedbyCatholicReliefServices william.martin@crs.org HumanitarianResponseDepartment Toronto|4December2018
  2. 2. Cash and Vouchers in Humanitarian Operations 2
  3. 3. 3 Atypical natural humanitarian disaster: Typhoon Damrey, Vietnam, 2017
  4. 4. 4
  5. 5. 300 project live with mobile data collection on more than 50 million beneficiaries
  6. 6. Cash andAssets Transfer Platform 6
  7. 7. What do users wants? 7 As a person regularly affected by natural disaster, I want to receive as quickly as possible humanitarian assistance in a “one stop shop” manner so that I am able to resume quickly my activities and be better prepared and resilient for the next crisis As a humanitarian coordinator, I want to be assisted by a roboadvisor to help me identifying needs, market and other infrastructures and services capacity in close to real time so that we can appeal for right amount of funding and adjust our intervention and supply of the humanitarian assistance to the ever changing context of the response. As a financial service provider, small vendor, faith-based organization -not in clusters system-, local partner, I want to have access to close to real time context and need analysis, and response scenario to be able to provide what people need the most at my community and individual level directly so that I direct my service where it is needed the most (B2B, B2B, P2P)
  8. 8. Building the new humanitarian ecosystem 8 User Cloud, Blockchain Government Fintech Insurance Companies & investors Lawyers “Old School” humanitarian
  9. 9. What are the possibilities you see for better leveraging emerging data science &AI capabilities? • Sandbox testing • Piloting • Build upon technology and experience existing in finance, insurance, medical and law sectors on roboadvisor. • Standardizing data points (e.g. HXL langage) • Aggregating data points • Strengthening data protection and beneficiary privacy. • Discussing “ownership” and sharing of data. 9
  10. 10. 10 Q&A

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