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Date

Antitrust Policy

Attendees

  • Sean Bohan (openIDL)
  • Peter Antley (AAIS)
  • Jeff Braswell (openIDL) 
  • Nathan Southern (openIDL)
  • Greg Williams (AAIS)
  • Ken Sayers (AAIS)
  • Megan Ebling (AAIS)
  • Rajesh Sanjeevi
  • Satish Kasala (Hartford)
  • Truma Esmond (AAIS)
  • James Madison (Hartford)
  • Allen Thompson (Hanover)
  • Tsvetan G (Senofi)
  • Joan Zerkovich (AAIS)
  • David Reale (Travelers)
  • Dale Harris (Travelers)

Agenda:

  1. Discuss HDS needs, requirements (see notes below)


Time

Item

Who

Notes









Action items

Notes: 

HDS REQUIREMENTS WIP IS HERE

  • What happened last week
  • First Meeting under the name "HDS Task Force"
  • first formal
  • prior had been watercooler discussion around data modeling
  • going forward - what is the HDS
  • start back and not spend time the group has done prior - how do we move HDS forward
  • James
  • work on requirements (ask to send)
  • Useful to look at a couple models, instead of one
  • risky to try to do all in one layer
  • balance
  • useful to have notions of the b-model at highest level, persistence model, loading model
  • business, presentation, persistence, loading
  • b-model
  • largely like list of elements, meaningful chunks
  • presentation - optimized for writing queries
  • some business but not concerned about system performance
  • Persistence - preserving history and truth
  • ultimate definition of truth, not necessarily easy to use
  • Loading - get the data into the system
  • compromise 
  • loaded data into persistence, presentation asks "what is easier to consume rather than truth"
  • tried to build dimensional model that preserves all history is hard
  • Business Model
  • implementation and perf agnostic
  • one step down from data dictionary
  • Ken - excited, loading model is different
  • James - entitles, attributes and relationships understood by business users
  • biz user willing to dive in, but understandable
  • no regard for implementation, tech, or processing req to load it
  • Element - single piece of info
  • entity - set of elements
  • business entity that is not recognizable to business users and tends to occur in conversations - policy, claim, vehicle, and home are typical examples
  • business model has to be careful about not getting crazy about abstract entitles
  • relationship - use of entity names "user has a" "policy is a"
  • model must not repeat the attributes of an entity in more than one place
  • model must make it difficult to over-count the elements and values
  • prevent excessive de-normalization
  • if you take premium, and repeat premium for every claim, could over-sum 
  • reasonable level of denormalization
  • business model should make it difficult
  • sparsity is the measure of empty values to total number of values
  • put homes and autos on the same row
  • totally different attributes for each
  • silly key, but bunch of elements filled out for one, others filled out, bunch of blanks
  • humans love flat and wide
  • put things together that are unrelated get sparsity problem
  • not defining 8 normal forms right now
  • will define in 3 min
  • no entity when populated will have sparsity greater than 10%
  • if occurs, entity reviewed
  • entity that is highly covariant with another entity may be embedded in it
  • Peter
  • when get 10% for #11 - how do you come up
  • James - throwing darts, consensus is what we decide
  • "should be reviewed " - conversation trigger
  • rationalization for normalizing, not just theory
  • can make address its own domain
  • most b people - its policy address (or garaging address)
  • saying - when some entity is highly covariant, doesn't do much sep from it, 
  • denormalization argument
  • #13 - laundry list, worth enumerating entity dictionary
  • seed list
  • Policy, Vehicle, Driver, Coverage, Claim, Claim Event, MORE
  • list of what they are and what they need
  • grouping data dictionary elements
  • intro entities - intro relationships
  • policy has one of more vehicles
  • vehicle has one or more drivers
  • policy has zero or many claims
  • many claim events
  • MORE
  • Kudos from all
  • Ken - great guidepost for coming up with a good model but not necessarily requirements
  • needs to... <examples>
  • Dale
  • is that the requirements for HDS
  • see this as a lower level than HDS
  • how the HDS would be created but not necessarily the requirements 
  • will be helpful in guiding development
  • still need bullet list requirements
  • David
  • this is great - good way to once we know we want to build, loves most
  • should be sanity checks and guideposts
  • most
  • to answer any one question - what is the HDS supposed to do
  • level of sparsity or normalization vs... if I don't have a stated biz req for what HDS is meant to do is touch
  • might not need to, business requirements are more lax
  • not sure what HDS is supposed to do
  • Peter
  • must support state DOI such as auto coverage and auto territory
  • Truman - can't do "all DOI" must define each one
  • Ken - short cut in the meeting
  • Truman - cant skip that - critical to answering each question
  • any two data calls
  • annual, last year, year/half over course of year or a point in time
  • cant go backwards
  • Joan - is it possible that theres types of question, not answer every one, but fall into simple classes
  • annual data call, one set of data 100s of questions answered from that set of data, very static
  • other type - whats the state today - only a few classes of questions or sets that are queried
  • simplify
  • Truman - agree , not each state report, couple diff ones, returning over historical period that exists or a snapshot
  • David - decouple it
  • really important
  • HDS should not be referencing specific use cases
  • should be ref by the DMWG
  • define DM that fits known use cases and predict future use cases
  • implement and expose data elements
  • any other requirements - easy and extensible
  • don't define specific things
  • requirement - HDS must implement data models developed by DMWG
  • Dale - data must conform to DMWG data model standards
  • David - it shall store and expose, make it accessible, make it real
  • gist of it
  • Dale - data should be current through 45 days
  • David - Dales closer 
  • then we need to go one layer deeper
  • these are decision points
  • middle layer missing - perf of HDS
  • bridging gap of what Dale wrote and this
  • Peter - thinks DMWG will need more - very far from technical
  • David - closes to business requirements
  • user stories, non functional requirements, business requirements
  • thing that must be done
  • data that falls out of that - what we need to implement in HDS
  • one layer deeper and above
  • what are the requirements
  • we don't need to know every change, just know and turned into a req
  • req. - data is current as of X Date
  • shall be exposed by HDS
  • discuss them
  • or could say "performance - what is acceptable - do we need instantaneous reads, what level of adhoc query do we need
  • to figure out
  • then decide how to build DM based on that
  • Satish - traceability of the data
  • trace thru HDS and back to source system
  • implementation - could be keys
  • others
  • how easy it would be for the data calls to discover the data in hDS
  • do we have a req where data call or extraction pattern, need to know what is in HDS
  • what attributes do we have
  • what is the level of relationship of those attributes
  • Ken - model we all know
  • Satish - discoverable in realtime?
  • do we have discoverable data requirements? confirming to a model
  • David - a business requirement - what the user experience is for the data callers
  • what the expectations are
  • start from the user experience and user stories and work our way down
  • how will it be used and how will carrier load into it
  • two user stories not terribly well defined today
  • what will that look like, how structure
  • not defined
  • Satish - must provide data current to 45 days prior - hinting at historical data? do we want to explicilty define history we maintain?
  • Dale - 5 years + current year
  • Peter - want to say CGL and NJ have weird reqs - closer to 7
  • David - HDS will store data as mandated by regulatory statutes
  • Truman - does it matter if apply to each co differently?
  • David - not every req needs to be enforced by openIDL, on carrier to und that
  • requirement - HDS must be current and have hold back period of x years, then the carrier can decide how they want to implement
  • carrier can decide how to implement, req "it must be there"
  • Ken - must meet retention requirements
  • Dale - prior + 45 days
  • processing, get thru it, makes sure it is right, dont get feeds every day, some monthly
  • David - hold off period to make sure it is right
  • what we need + req
  • Peter - trailing 24 months right now, 45 days will make all real happy
  • Dale - edit package, open IDL sponsored and maintained edit package the info goes through prior to landing in HDS
  • must maintain min of 5% tolerance at state line level
  • similar to SDMA
  • Peter - can do based on SDMA
  • Joan - part of NAIC req
  • talk about what data needs to be avail for RR - 5% tolerance as well
  • David - edit "before  being in HDS" - when we load HDS could conform to 3 packages and fail 7 based on data call, could conform perfectly but their could be a new data call that doesn't
  • Ken - example - provide VINs, I don't provide vins which would fail that call 
  • David - run against data in the HDS
  • Peter - wont have NAIC data to get to the current reconciliation wont have long after 45 day period
  • Ken - are we conflating 2 reqs - put data in with quality but might not meed reqs of data call
  • 2 diff reqs
  • Satish - is there any req on backwards compatibility
  • DM will change over time
  • are we mandating HDS is backwards compatible with previous vers of the DM
  • Peter - in the camp of extraction patterns written against current iterations of model 
  • extraction model should tie to one model
  • David - prob DMWG will update data model, will happen, all my old data when it updates might 
  • might not have existed on a policy 7 years ago
  • some issues there where - needs to be define
  • Ken - data model needs to change over time
  • Satish - how does HDS need to behave
  • Dale - even though conform to data model, mot every attribute in the data model 
  • minimum required elements provided for everyone, all others at the option of the carrier
  • Ken - ND example of being very sparse and still participating
  • Dale - if doing stat reporting, minimal amount of data required
  • David - almost think those reqs can be handled by the queries, HDS for simplicity only has to adhere to DM going forward
  • if DM changes, anything in the HDS can optionally be updated
  • Dale - even the fields in the dm today, not all are required - just Day 1s
  • David - query tells us if it is needed for a specific use case
  • simple req on HDS - required fields only mandated to be updated when a new DM is released
  • could always go backwards
  • example - middle of 2023, DM updated, we might just re-run all 2023 against the new DM, but unlikely go back to 2019
  • query checked - what data is there
  • HDS shall only conform to DM going forward not backwards compatible
  • Ken - how does new data relate to old data
  • worries about migration of the model
  • informs how we build the model
  • ways to do it
  • extensibility - lead to - less normalized more extensible kind of format
  • sparsity but you could have struct of db not change with new data elements
  • 2 very diff architectures
  • Jeff - more of a graph approach with facts vs schema/tables
  • David - more JSON like
  • document-like
  • easy to start loading new data in year 5
  • query old data from year one
  • ignores if not there
  • whats there passes the check
  • less performant
  • with a performance requirement - would let us know if an acceptable solution
  • Satish - carrier - change to the DM, v 2 - carrier 2 is still on V1, don't / wont migrate - how does the extraction pattern work?
  • David - 2 EPs or 1 that checks for both versions, decouples DB from use case better
  • if I am VA, running same data call for five years, only some carriers have new data, write EP that that hits both
  • Ken - SLA approach - everyone shall conform by X time
  • more consent, fewer dark corners
  • David - carrier concern - whole value prop, set data, load HDS, takes churn off of us
  • updating dMs every year, req fields added every year, looks less attractive, sla requirement
  • very hard, erodes value prop
  • Ken - aspire to migrations for those things, easier to run
  • some of these will be trivial
  • most part - once solved model
  • adding fields not reorganizing
  • David - governance and guidelines "not requesting carriers add more data every couple months"
  • know there will be iterative
  • needs to be sensible, but cant be constantly asking carriers to add more mandatory data
  • Dale - there will be a governance process inside each carrier 
  • new item doesn't happen overnight
  • David - unfunded mandate
  • cant commit to mandated field from openIDL, internal gov processes for data David cannot guarantee success on
  • mandate - these extra fields are mandatory, cant go back to. a line of business "put this in its mandatory" - they will say no
  • even if you make it optional, too much drift/variation of data in there, it will be a mess
  • major concerns here
  • Jeff - standard model doesn't change too much, when they do it is thought out and structured
  • high level reqs, not HDS but inform "how we make it extensible"
  • Peter - if we add a new element shouldn't be backfilling for new model
  • new attributes 
  • Jeff - policy - should you do it or not
  • not just add a field and have a diff iteration of the model every month
  • Peter - auto guy wants "yes/no" for usage based insurance
  • Jeff - anticipation of structure vs availability of the data
  • update history - - policy question
  • more work
  • concept of extraction request - federated and exists within diff carriers
  • not a simple topic
  • David - goes to why concerned about moving forward, if this is mechanism by doing data calls and asking for elements outside of standard - needs to be mechanism
  • right now don't need to work about data call not matching stat reporting requirements
  • needs to be easy and extensible to respond to data calls
  • unless we expect regs to only be choosing data from regulated list of data models
  • Dale - info not in HDS< may fall for carrier to do directly rather than openIDL
  • never going to have all data calls going thru openIDL
  • David - if it was really seamless, regulators look and say "i need this one element" and could easily sqy "we can add that" it would make our lives really easy,
  • used for adhoc data calls
  • if it is hard, can go around openIDL, less attractive
  • hard to predict
  • consider - might be beneficial for long term, 99% of data for data call, easy for carrier to add an element would make it easy for carriers
  • Dale - picked up a lot of things for regulator in Day 2 and Day 3
  • David - covid 19 - no one saw that exact data call coming
  • always bespoke?
  • Dale - might have been able to do it thru statistical data
  • might have needed to get to coverage codes
  • Peter - influenza of 1920 - 100 year disease
  • David - req - we aren't going to cover every possible data call, trying to get the vast majority 
  • Peter - homework - getting regulators back together Friday
  • short call 
  • altogether in the room on Friday
  • talk about queries, sample questions
  • agenda?
  • Dale - working on what he views as business reqs
  • 3 buckets
  • data, data integrity, access and security and comms
  • vetting with his folks at Travelers

Recording: 

openIDL_Arch_HDS_TF_053122.mp4



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