Chapter 34 — Further Reading

Sources are grouped by the book's three citation tiers. Tier 1 is verified and canonical; Tier 2 is real and attributed but with specifics you should confirm against current sources; Tier 3 is the constructed teaching material from this book. The InsurTech sector moves fast and its companies report new numbers every quarter, so treat any specific figure as a moving target and check the primary filing.

Tier 1 — Verified, canonical

  • SEC filings of the publicly listed InsurTech companies (IPO prospectuses on Form S-1 and quarterly/ annual reports on Forms 10-Q and 10-K) — the authoritative public record of these companies' premium growth, loss ratios, combined ratios, and the strategic shifts (repricing, segment exits, reinsurance) discussed in Case Study 1. The primary source for any exact figure.
  • The McCarran-Ferguson Act and the state rate-regulation regimes (Chapter 4) — the reason an API-delivered rate must still match a filed rate, and why the encoded logic of an automated quote is examinable by a state regulator. Real and binding on every InsurTech transaction.
  • The Fair Credit Reporting Act (FCRA) — governs the third-party data that pre-fills an instant quote (Chapters 8 and 31); applies in full no matter how fast or automated the distribution.
  • The NAIC's work on accelerated/algorithmic underwriting, big data, and artificial intelligence — the model bulletins and committee activity through which U.S. insurance regulators are addressing automated and AI-driven underwriting; the regulatory backdrop to the encoded-logic compliance discussion in §34.4 and the fairness issues deferred to Chapter 35.
  • The doctrine of insurable interest (Chapter 4) — the canonical legal requirement that a parametric weather or event product must be designed around so that it is insurance and not a wager (§34.3).

Tier 2 — Real and attributed; verify the specifics

  • Industry and consultancy analyses of the InsurTech sector (the regular InsurTech reports from major reinsurance brokers and consultancies, and the venture-funding trackers) — broadly reliable on the shape of the wave (the funding boom and pullback, the relative durability of MGAs and enablers, the full-stack carriers' loss-ratio struggles), but specific funding totals and rankings change continually and should be checked against the current edition.
  • Trade-press coverage of embedded insurance and API distribution (the insurance and InsurTech trade publications) — useful for the range of real embedded programs (travel, device, freight, software-platform, mobility) and the API-driven distribution stack; individual program terms and results are mostly proprietary, so treat program-specific claims cautiously (as Case Study 2 does with its labeled composite).
  • Reinsurance and capital-markets commentary on parametric insurance — parametric structures are long-established in the catastrophe and reinsurance markets and well documented there; the consumer-scale parametric products are newer and their loss results are not yet a long public record, so quantified claims about retail parametric performance should be treated as preliminary.
  • General industry combined-ratio and loss-experience data (AM Best, S&P Global, NAIC) — the personal- lines loss-ratio pressures that hit the InsurTech carriers (catastrophe-driven property volatility, auto severity inflation) are well attested as patterns; the specific annual figures change yearly.

Tier 3 — Constructed teaching material (this book)

  • The Harbor Steel & Fabrication underwriting file (the Port Hadley plant, Meridian Risk Partners, and the chapter's File checkpoint, including the parametric-wind-supplement option) — constructed teaching example, realistic but not drawn from any real account.
  • The "optional protection plan that selected against itself" composite (Case Study 2) — a clearly-labeled composite built from real industry patterns (program business, class underwriting, adverse selection), not any one named program; it illustrates a mechanism, not a company's results.
  • The illustrative landscape taxonomy and the quote-in-seconds flow diagram (§34.1, §34.4) — schematic, not-to-scale teaching devices.

If you read only one thing: pull up the most recent 10-K or 10-Q of any one listed InsurTech carrier and read the management discussion of its loss ratio and combined ratio against its premium growth. In two pages you will see this chapter's entire argument in a company's own audited words — growth that was easy, an expense ratio that improved, and a loss ratio that decided everything.