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Date

Attendees

Nathan Southern

Sean Bohan 

Jefferson Braswell 

Peter Antley 

Ash Naik 

Allen Thompson

Mason Wagoner 

Chudwick, Susan R 

Jenny Tornquist

Reggie Scarpa

Joseph Nibert

Brian Hoffman

Kevin Petruzielo

Rambabu

Mike Nurse



Minutes


I. Introductory Comments by Peter Antley

A. Welcome

B. Reading of LF Anti Trust Statement

II. Agenda Items

A. Recap

  1. Test data for MHO loaded up 
  2. Mason working on DP - will have it finished by next friday
  3. Exceptions in farm properties, otherwise DP rounds out residential properties
  4. Plans worked out for this coming year. Ingesting data from all stat plans - great progress here

B. Today's Agenda

  1. Antley presented a video that covers progress from the last year (ran video) - enthusiastic response.
    1. Final version at the meeting on Wed. - will be premiered there'
    2. Questions raised about how we make reporting and non-reporting lists (beyond simply AAIS) clear within the UI; Peter agreed to bring this up in the AWG in the coming week. Noted that if another stat agent came in and assisted with extraction patterns, we would see the name there in lieu of AAIS.
    3. Peter stressed the criticality of exploring how we write data calls, also how do we engage regulators more broadly.
  2. PA referenced new participant on call - Joseph Nibert.

C. Looking ahead - Peter referenced plan/desire to go into commercial general liability as the next line for modeling

  1. JT: it will be different than others - because it works with the policy effective date, not accident or accounting date
  2. JT: key difference is how data is reported to NAIC and others
  3. Also possible that we may do farm properties before CGL, just so we can close out residential.
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.

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