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Global insurance premiums grew by 2.7% in inflation-adjusted terms in 2010 to $4.3 trillion, climbing above pre-crisis levels. The return to growth and record premiums generated during the year followed two years of decline in real terms. Life insurance premiums increased by 3.2% in 2010 and non-life premiums by 2.1%. While industrialised countries saw an increase in premiums of around 1.4%, insurance markets in emerging economies saw rapid expansion with 11% growth in premium income. The global insurance industry was sufficiently capitalised to withstand the financial crisis of 2008 and 2009 and most insurance companies restored their capital to pre-crisis levels by the end of 2010. With the continuation of the gradual recovery of the global economy, it is likely the insurance industry will continue to see growth in premium income both in industrialised countries and emerging markets in 2011.
For example, most insurance policies in the English language today have been carefully drafted in plain English; the industry learned the hard way that many courts will not enforce policies against insureds when the judges themselves cannot understand what the policies are saying. Typically, courts construe ambiguities in insurance policies against the insurance company and in favor of coverage under the policy.
At the most basic level, initial ratemaking involves looking at the frequency and severity of insured perils and the expected average payout resulting from these perils. Thereafter an insurance company will collect historical loss data, bring the loss data to present value, and compare these prior losses to the premium collected in order to assess rate adequacy. Loss ratios and expense loads are also used. Rating for different risk characteristics involves at the most basic level comparing the losses with "loss relativities"—a policy with twice as many losses would therefore be charged twice as much. More complex multivariate analyses are sometimes used when multiple characteristics are involved and a univariate analysis could produce confounded results. Other statistical methods may be used in assessing the probability of future losses.
In the United States, economists and consumer advocates generally consider insurance to be worthwhile for low-probability, catastrophic losses, but not for high-probability, small losses. Because of this, consumers are advised to select high deductibles and to not insure losses which would not cause a disruption in their life. However, consumers have shown a tendency to prefer low deductibles and to prefer to insure relatively high-probability, small losses over low-probability, perhaps due to not understanding or ignoring the low-probability risk. This is associated with reduced purchasing of insurance against low-probability losses, and may result in increased inefficiencies from moral hazard.
NerdWallet averaged rates for 40-year-old men and women for 20 ZIP codes in each state and Washington, D.C., from the largest insurers, up to 12 in each state. “Good drivers” had no moving violations on record and credit in the “good” tier as reported to each insurer. For the other two driver profiles, we changed the credit tier to “poor” or added one at-fault accident, keeping everything else the same. Sample drivers had the following coverage limits: