Chapter 14 — Further Reading

Sources grouped by the book's three citation tiers. Tier 1 is verified canonical material you can stand behind; Tier 2 is real industry practice and studies whose exact specifics you should verify before quoting; Tier 3 is the chapter's own constructed teaching material. Where a real study or event is named, treat its direction and existence as solid and its precise figures as something to confirm — this chapter deliberately attaches no fabricated statistic to any real source.

Tier 1 — Verified canonical

  • The personal-auto policy (PAP) as standardized through ISO / Verisk — the bureau coverage form and its parts (liability, medical payments/PIP, uninsured/underinsured motorist, collision, and comprehensive). The reference architecture for everything in §14.1.
  • The Fair Credit Reporting Act (FCRA) — the federal statute governing the use of credit-report information and requiring adverse-action notice when such information adversely affects an applicant. Foundational to §14.3.
  • The Federal Trade Commission's study of credit-based insurance scores in automobile insurance — the well-known public examination finding these scores predictive of insurance loss. Cite the finding; verify the specifics. (§14.3)
  • California Proposition 103 (1988) — the ballot initiative restructuring California insurance regulation: prior approval of rates, an elected commissioner, and the mandated prioritization of driving record, annual miles, and years of driving experience in auto rating. The standing example in §14.5.
  • Michigan's no-fault auto reform (2019, effective 2020) — the legislation introducing choice of PIP medical limits, a medical fee schedule, and related changes to a system formerly built on unlimited lifetime PIP medical benefits. The standing example in §14.5 of the coverage mandate driving price.
  • The McCarran-Ferguson Act (Chapter 4) — the basis for state-by-state regulation of insurance, which is why personal-auto rating rules form a patchwork across states. (§14.5)
  • The National Association of Insurance Commissioners (NAIC) model rating laws and the "not excessive, not inadequate, not unfairly discriminatory" rate standard — the framework every filed auto rate must satisfy. (§14.5)

Tier 2 — Attributed, specifics unverified

  • Industry reporting and rating-agency commentary on personal-auto combined ratios in recent years. It is well established that the line has run unprofitably on underwriting in several recent years; consult current trade press, rating-agency line reviews, and regulatory filings for the year-specific figures rather than relying on any number quoted here. (§14.7, Case Study 1)
  • The early-2020s personal-auto profitability cycle — the documented pandemic-era frequency drop and premium givebacks, the 2021–2022 frequency-and-severity rebound, the 2022–2023 underwriting losses, and the rate-driven correction. The sequence is public; verify any specific magnitude. (Case Study 1)
  • Public usage-based-insurance programs — e.g., Progressive's Snapshot and comparable telematics offerings — as illustrations of the monitored-period and continuous UBI models. Treat product mechanics as illustrative of the category; confirm any current program detail with the carrier. (§14.4)
  • Vehicle-technology repair-cost literature — industry and repair-research material on how advanced driver-assistance systems (ADAS), sensors, and cameras have raised collision repair severity even as some systems lower crash frequency. (§14.2, §14.7)
  • State-by-state surveys of restricted auto rating factors — credit, gender, occupation, education, and territory restrictions vary and change; consult a current regulatory survey (e.g., NAIC or a reputable industry compendium) for the live rules in your state. (§14.5)
  • The Institutes (AINS / CPCU) personal-lines course materials — structured treatment of PAP coverage parts, classification, territory, and personal-auto rating at certification depth. (§14.1, §14.2)

Tier 3 — Illustrative / constructed

  • Harbor Steel & Fabrication, Inc. — the running constructed Underwriting-File project; the owner's personal auto and umbrella appear here only as a teaching aside on account rounding. All facts illustrative.
  • Figure 14.1 — "The clean record that isn't the cheap risk" — a constructed Read-the-Submission block contrasting two clean-record applicants.
  • The chapter's worked rate examples — the multiplicative-relativity premium build (§14.2) and the combined-ratio Python snippet (§14.7) — all constructed teaching figures, not any real carrier's numbers.
  • Case Study 2's framing of Proposition 103 and Michigan no-fault — the statutes are real (Tier 1); the qualitative analysis and any illustrative phrasing of magnitudes are the chapter's own and are kept non-numeric on purpose.

If you read only one thing: read the text of California Proposition 103's auto-rating provisions (the mandated ordering of driving record, annual miles, and years of driving experience). Nothing else so concretely shows the gap between what the data would weight and what the law lets you weight — which is the whole lesson of this chapter's title and of §14.5.