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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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Meeting ID: 989 0880 4279
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Meeting ID: 989 0880 4279
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Attendees

Goals

Meeting Minutes

I. Opening

A. Greetings to attendees

B. Mr. Antley: LF AntiTrust statement.


II. Agenda - Data Modeling and Internal Data Work - Mr. Antley

A. Overview/Recap

  1. Discussion of data modeling and what idl project is doing with data. Concerned that discussions may be becoming overly technical. Wants to dial the tech speak down a bit
  2. Pulled up graphic on Earned Premium - 3 columns: Input / Business Layer /Output
  3. Noted that last week, Mr. Williams led a discussion on car years. 
  4. Also noted that he led the discussion on business layer - wants to revisit and continue this.

B. Business Layer

  1. Re: Input, Stat plan as it is gives us adequate data to do regulatory reporting, and we can ingest most of needed information:
    1. Accounting date
    2. Duration
    3. Coverages and exposures
  2. Re: Output: some of the terms for which people are asking (presented examples here): e..g, Earned premiums, car years, incurred loss, earned/written exposures and premiums, incurred claims/losses, calculated ratios, average expenditures, average premiums, underwriting expenses.
  3. Mr. Antley: the way they solve (@AAIS, in his warehouse) these questions today: they take the input records, process these to be centered around the idea of a policy, and then calculate: earned premium, paid loss, incurred loss, outstanding losses, earned exposures, paid claim counts, outstanding claim counts. They calculate all of this on quarterly basis. Sits and persists in data store on level on which they are making reports, they have these terms, grouped by policy, calculated by quarter. If x person asks "what is my earned premium for the year, for these kinds of coverages," he does a select query that does filters and aggregates and produces year output. Data on a policy and quarterly basis with the premium after it has been earned.
  4. In AWG: Discussion - how do we set up HDS so it is accessible to regulators, sans putting undue burden on rest of system?
  5. Pointed to base layer, from which we answering questions. How do we make it accessible to the persons making queries? Quarterly basis reports right now -→ fairly easy and straightforward
  6. Mr. Antley solicited thoughts/suggestions from group about what the data layer will look like
    1. Mr. Sayers: when looking at data layer, we must ask visibility to whom? Carriers e.g., want to see stat plans eventually with more data. Can we put this in HDS per Mr. Braswell's suggestion? Data layer could be an ephemeral pass-through that is part of the extraction pattern, or a standing entity where ETL transforms stat plan. Key questions: what are we asking the carriers to prove, and do they care about any format other than the stat plans?
    2. Mr. Antley: who are the voters in this RRDMWG? We have carriers, and we have regulators. Another critical question: if we just look at the easiest way to load this, and say, the carriers can just be done with loading the stat records, at this point who is tasked w/turning the stat records into a query that makes sense for the regulators? Without relying on regulators to expend the energy/effort into turning records into something useful?
    3. Mr. Sayers: There is discovery here. We start from the stat plan - may want to make it less codified to make it more workable, but it can be a perfectly viable raw material. We can throw some reports at it however and say how difficult is it to get from the stat plan data to this report?
    4. What are we asking carriers to provide and do they care about formats other than stat plans


Mr. Antley: carriers vs. regulators. For him, critical question: who is tasked with turning the stat records into a query that makes sense for regulators? 


Mr. Sayers: we can start with stat plan as raw material, throw reports at it and ask how difficult is it to get from this stat plan data to report. And ask: Do we need an intermediate format?

Mr. Madison: If something is a raw element not included in current stat plan, must be added.  Business layer is a black box for now. This meeting does input and output. Pointed to limiting focus of this meeting to data modeling alone. (Mr. Braswell agreed).

This meeting is not concerned with business layer: only concerned with how do we calculate earned premium.

Mr. Harris: we want to use existing stat plan as a means of building the plumbing. We want to be able to get from A to Z from an architectural perspective - request comes in, permission approved, extraction occurs, and then at EOD we have a report. Wants to go back to data model we have

Mr. Braswell: what are outputs that need to be clarified. Affirmed Mr. Harris's idea as prescient and valid.

Mr. Antley: having a difficult time transforming data 

Mr. Harris: it works in AAIS why can it not work in idl, etc. Mr. Braswell: this is an architectural question.

Mr. Sayers: extraction pattern has been broken up into multiple levels to get it to work in AAIS. Getting it all to work in one extraction pattern overly complicated. 


Mr. Madison: Most concerned with clarity of the rules: it is possible to over-engineer any model. His challenge: what are we trying to achieve. Separating business rules from shape of model of data. 


Not a single straight move. Mr. Antley: confused about this. Summing exposure, premium, incurred claims/losses. 

Discussion items

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Notes


Action items

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