Initial Project Description: 

Insurance, reinsurance and broker organizations capture and store data on real property, including information on natural disasters, claims, type of usage, construction and other modifications. Today each organization stores and administrates this risk data individually. There is no real way for organizations to exchange this data for the purposes of data enrichment. As a result, the quality of existing data may be poor as the information is often incomplete and outdated.  >> Read More 

Problem Statement:

What are the main barriers/ elements required to build a risk exposure data warehouse (REDW), and how could it add value once in place? 


Duration of Project:

  • 2 Days

Project Participants: 

  • AIG
  • Cowan Group
  • Highline Beta
  • Munich Re
  • RSA
  • SAP
  • The Cooperators
  • TMD

Project Highlights and Milestones: 

The initial goals of the team were to:

  • Identify key elements and barriers to building a REDW.
  • Identify the data that would need to be stored in the REDW.
  • Develop a list of use cases to monetize on the data stored within the REDW.

Over two days, the project team worked to achieve these goals by working through Design Thinking based exercises.  The project team presented their outputs on their final afternoon at the Lab.


The project team identified the following barriers that would need to be overcome to build a REDW.

  • Competition (collaboration)
  • Privacy (regulation)
  • Data sources
  • Data quality
  • Trust

The following top three opportunities for monetization were identified by the project team:

  • A “check in” service for residential policy holders when they go away, to prevent their insurance from becoming void.
  • Make risk data available to customer to purchase, so that customers may make informed decisions (such as which house to buy).
  • One-click insurance – the ability for customers to insure their property immediately, as property data would already be available to insurers.


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