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Alternative Data Sources for Modeling

This presentation explores issues to consider when appending alternative data, including legal and privacy concerns, data applicability and availability, and methods for finding matches.

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Alternative Data Sources for Modeling

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  1. Alternative Data Sources for Modeling Presented by John Wilson CAS Special Interest Seminar – October 5, 2004

  2. Presentation Overview • Issues to consider when appending data • What about legal / privacy concerns • Considerations for data applicability / use • What data is available? • How to find matches?

  3. Legal / Privacy Concerns • Are we accessing FCRA database? • FCRA requires permissible purpose, or • Aggregated, de-personalized research files • If not FCRA data now, will it be? • Use of non-FCRA data for FCRA purpose can taint the database and create new obligations

  4. Data Applicability • Access - if not on-line now, can it be? • Coverage - full & complete, or “spotty”? • Reliability • Can it be pragmatically applied in workflow? • Is it subject to manipulation (“gaming”)? • Affordability (cost vs. benefit)

  5. What property data is available? • Data on the subject property • geography, construction, prior losses • Data on the insured • consumer credit data • prior losses • household profile • What else?

  6. Types of Data • Homeowners - Underwriting Report Data • Consumer Credit data • Loss History (CLUE) • Real Property data • Geographic data • Inspection Results data

  7. Types of Data • Consumer Credit • as a pre-developed score or scores • as a set of pre-aggregated characteristics • in “raw” form which must be aggregated • Prior Coverage Information

  8. Types of Data • Loss History data • as a set of pre-aggregated characteristics • losses at property, and / or • associated with consumer • exclude Cats • examine just property losses, or • examine prior auto losses as well?

  9. Types of Data • Real Property Data • County tax assessment information • Court records • Physical characteristics • Sale price • Other financial transactions • Flood Zone Determination (FEMA / NFIP)

  10. Types of Data • Geographic Data • Latitude / Longitude • Spatial Analysis • Satellite Images • Distance to _________ • Others?

  11. Types of Data • Inspection result data (internally captured) • Const. Style / type / stories / replacement cost • Slab / crawl / basement / daylight / finished • Number of BR, BA, Kitchens, total rooms • HVAC details, presence of pool, fence, etc. • Underwriting hazards? Remediation?

  12. Types of Data • “Demographics” • ages, number in household, education level • home business, est. income, occupation, etc. • “Psychographics” • magazines, TV shows, catalog purchases • survey results extended to all via geography • Coverage / Individual / Reliable / OK?

  13. Types of Data • Internal appends • past premium payment history • time with carrier, other coverages • experience on companion policy • deductibles, protection devices, etc. • Consider potential before ruling it out

  14. What auto data is available? • Data on the vehicle(s) • Data on the insured • consumer credit data • prior losses • household profile • driving practices / places • What else?

  15. Types of Data • Automobile - Underwriting Report Data • Consumer credit • Loss History - both lines! • MVR? - company captured • violations must be normalized • application may need to be state-specific • Prior Coverage Information

  16. Types of Data • Automobile - Underwriting Report Data • Vehicle Data • Home Ownership Verification • Household Composition • Demo / Psychographics • Internal appends

  17. How to find matches • Use consumer ID data to match • Full name • Address • SSN • DOB • DL # • ID must be removed prior to analysis

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