Why Two Insurers Quote You Different Prices (The Rating-Factor Math)

The central insight: rating is not ranking

Imagine two carriers, A and B, both rating the same hypothetical driver: 38, clean record, ZIP 78704 (Austin, Texas), 2021 Honda Accord, 100/300/100 limits, $500 deductibles. Carrier A's rating model weights credit history at 35 percent of the variance in the final price. Carrier B weights credit at 12 percent and weights ZIP-level theft frequency at 30 percent. If our driver has excellent credit and lives in a low-theft ZIP, both carriers come back cheap, but for different reasons, and Carrier B is probably cheaper. If our driver has thin credit and lives in a high-theft ZIP, Carrier A is probably cheaper because credit (where the driver ranks worse) is weighted less heavily.

This is why “cheapest car insurance” queries are unanswerable in general. The answer depends on the specific shape of your profile relative to each carrier's rating-factor weights, none of which are public. The four-quote method exists because you have to discover this empirically.

Driving record

The single most predictive factor across most carriers' models. Tickets (especially moving violations), at-fault accidents, claims history, and DUI/DWI convictions all add surcharge. Typical surcharge schedule: a first speeding ticket adds 10 to 25 percent for three years; a first at-fault accident adds 25 to 40 percent for three years; a DUI adds 60 to 100 percent or moves the policy into non-standard markets entirely. Surcharges decay; most fade after three years, some after five. What you can do: drive carefully, keep records of safe-driving courses (most carriers offer 5 to 10 percent for completing a state-approved course every three years).

Annual mileage and primary use

More miles, more risk exposure, higher premium. The categories are typically pleasure (lowest, often under 7,500 miles per year), commute (most policies, 7,500 to 15,000), business (highest, includes use for income generation). The cost-per- mile relationship is roughly 1 to 2 percent of premium per 1,000 miles in the mid-range. What you can do: if you used to commute and now work from home, re-rate your policy to pleasure use; the savings can be 8 to 15 percent.

Location (ZIP, garaging, urban vs rural)

Carriers rate by territory, with ZIP-level granularity in most states. Inputs include population density, theft frequency, accident frequency, density of uninsured drivers, weather exposure, road quality, and garaging type (street vs driveway vs garage). Moving across town can change your rate 20 percent. Moving from suburbia to a dense city centre can change it 40 percent. The standardisation rule applies: give every carrier the same address, otherwise the comparison is meaningless.

Age and gender

Age curves are roughly U-shaped. Premiums peak in the late teens (highest-risk cohort by collision frequency), drop steadily through the twenties, plateau in the thirties through fifties (the trough), and rise modestly from the late sixties as cognitive and reflex factors begin to register. A 19-year-old typically pays 2.5 to 3.5 times what a 40-year-old pays for the same policy. Gender remains a rating factor in most US states but is prohibited in California, Hawaii, Massachusetts, Michigan, Montana, North Carolina, and Pennsylvania. The gender effect is small (under 10 percent in most age brackets) and has been narrowing.

Vehicle

Carriers rate vehicles using the ISO symbol system, which assigns each VIN a numeric score reflecting expected loss cost (theft frequency, repair cost, crash severity). A high-symbol vehicle (high-end European sedans, sports cars, certain truck models with high theft rates) costs meaningfully more to insure than a low-symbol vehicle (entry-level family sedans, minivans). The symbol assignment is updated as new vehicles enter the market and as loss data accumulates. What you can do: when shopping for a vehicle, factor the insurance cost into the total cost of ownership; a $35,000 vehicle that costs $2,400/year to insure has a different economic profile from a $35,000 vehicle that costs $1,400/year.

Credit-based insurance score

In states that permit it (most US states), credit-based insurance scoring is one of the strongest single predictors in carrier rating models. The score uses similar inputs to a FICO score (payment history, balances, length of history, recent inquiries, credit mix) but applies a different formula optimised for insurance loss prediction. The III argues there is a strong actuarial correlation: drivers with better credit-based insurance scores file fewer and smaller claims on average. The magnitude of impact varies by carrier but commonly ranges from 25 to 50 percent difference between excellent-credit and poor-credit profiles, holding everything else constant.

States prohibiting credit-based insurance scoring in personal auto rating: California, Hawaii, and Massachusetts. Several other states (Maryland, Washington, others) restrict its use in specific ways (e.g. cannot be sole reason for denial; cannot be used at renewal). What you can do: improve your credit before shopping; even a small score improvement can translate to material premium reduction in states permitting its use.

Continuous coverage

Most carriers offer a discount (often 5 to 15 percent) for prior continuous coverage. The opposite is also true: most carriers surcharge for any lapse in coverage, even one day, with the surcharge commonly 20 to 40 percent for the first renewal cycle following the lapse. The surcharge decays as the continuous-coverage tenure rebuilds. The lapse-surcharge effect is one of the most expensive aspects of mid-policy switching done badly, which is why the timing guide emphasises never having a one-day gap between policies.

Marital status, homeownership, education, occupation

These are the “soft factors,” less heavily weighted than the heavy hitters above but still part of most carriers' rating models. Married drivers commonly pay slightly less than single drivers (the actuarial argument is that married drivers file fewer claims; cause and correlation are debated). Homeowners often qualify for an automatic homeowner discount if bundling. Higher education attainment and certain occupations (engineer, teacher, military, specific professional categories) have historically attracted small discounts at certain carriers. Several states have pushed back on these factors as proxies for socioeconomic status: Maryland, New York, and Washington have all restricted specific uses, particularly the use of education and occupation in auto rating.

Imagine three carriers rating the same identical risk profile: 38 years old, clean driving record for the last seven years, suburban ZIP, 2021 Toyota Camry, 100/300/100 limits, $500 deductibles, married homeowner, fair credit (around the 65th percentile), 12,000 miles per year, commute use.

Hypothetically, three carriers could weight the rating model as follows:

(These weights are illustrative, not actual carrier model parameters.) For a driver with strong driving history but weak credit, Carrier B's model produces the lowest premium because it weights driving record highly and credit lightly. For a driver with thin driving history but excellent credit, Carrier A's model wins. For a driver in a high-theft territory, Carrier C and Carrier B (weighted equally on territory) produce closer prices than Carrier A. Same risk, three different prices, all defensible from each carrier's own actuarial standpoint.

The conclusion: the cheapest carrier for any specific profile is empirically discoverable but not theoretically predictable. This is why the four-quote method exists, why a single comparison-site result is not a substitute for it, and why shopping every renewal (or every two renewals) is genuinely worth the time.

Connected pages

• How to compare: the four-quote method this rating-factor math justifies.
• Coverage spec builder: the worksheet that locks in the spec, so the only variation across quotes is rating-model variation.
• Lower your rate without switching: how to make your existing carrier re-rate.