2021-10-29 Meeting Agenda

Date

29 Oct 2021

This is a weekly series for The Regulatory Reporting Data Model Working Group. The RRDMWG is a collaborative group of insurers, regulators and other insurance industry innovators dedicated to the development of data models that will support regulatory reporting through an openIDL node. The data models to be developed will reflect a greater synchronization of data for insurer statistical and financial data and a consistent methodology that insurers and regulators can leverage to modernize the data reporting environment. The models developed will be reported to the Regulatory Reporting Steering Committee for approval for publication as an open-source data model.

openIDL Community is inviting you to a scheduled Zoom meeting.

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https://zoom.us/j/98908804279?pwd=Q1FGcFhUQk5RMEpkaVlFTWtXb09jQT09

Meeting ID: 989 0880 4279
Passcode: 740215

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Meeting ID: 989 0880 4279
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Attendees

• Dina Burgess 
• Daniela Barbosa
• Dale Harris 
• Ruturaj Waghmode
• Brian Hoffman
• Ken Sayers
• Kristian Farner
• Lori Munn
• Megan Ebling
• peter antley
• Robin Westcott
• Satish Kasala
• Stephen Lee
• Susan Chudwick 

Goals

• Define Charter
• Identify key stakeholders 
• Review Automobile Statistical Data Model 
• Review Data Dictionary 

Discussion items

Recording

RRWG_2021-10-29 Meeting.mp4

Action items

•     Review Charter:       

  • Research and assess relevant industry reference regulatory reporting

              data models and data standards

  • Recommend industry reference data models and data standards that may be referred or incorporated into regulatory reporting data models
  • Review, refine and document regulatory reporting data models
  • Recommend data models to openIDL Steering Committees for approval
  • Review requests for, analyze, design and document updates to regulatory reporting data models
  • Data models discussed, created & documented are published as open source
  • Identify Actors and their perspectives/views that are applicable for a given data model
• Susan to share her gap analysis (NAIC vs auto data model)
• Peter to add acceptable values (enumeration lists) and rules