Insurance

Firms and individuals can be sub­ject to risks which, in the aggregate, form a class of homogene­ous cases. For example, out of a thousand firms, no one knows if a given firm will suffer a fire next year or not; but it is fairly well known that ten of them will. In that case, it may be of advantage for each of the firms to "take out insurance". They can pool their risks of loss, or a specialized firm, an "insurance company", can organize the pooling for them. Each firm will pay a certain premium, which will go into a pool to compensate those firms which suf­fer the fires.

And that is the principle of insurance.

Insurance and Probability

Case probability

Case probability means, that we know some of the factors which determine the outcome of a particular event; but there are other determining factors which we don't know. The cases are individual, unique, and nonrepeatable, their result is uncertain. If in roulette a ball falls ten times on red in succession, the probability, that in the next turn will be the result black, is not greater than it was before. Football games cannot be predicted on the results of last games, nor can be presidential elections.

Instances of case probability are uninsurable.

Main article: Probability

Class probability

Class probability means, that we know nothing about an individual outcome, but we know everything about a whole class of events, and are certain about the future. In a lottery, for example, we know how many tickets are in total and how many will be drawn. But that does not say at all, if a particular ticket or tickets will win, and buying more tickets does not increase the chance of winning. An instance of class probability is called risk. It is possible to insure against risk, because the behavior of a class of events (or a reasonable subset of it) is well known.

The field for the application of class probability is the field of the natural sciences, ruled by causality.

Main article: Probability

Risk and Insurance

Risk occurs when an event is a member of a class of a large number of homogeneous events and there is fairly certain knowledge of the fre­quency of occurrence of this class of events. For example, a firm producing bolts knows from long experience that, say, 1 percent of these bolts will be defective. It will not know whether any given bolt will be de­fective, but it will know the proportion of the total number. This knowledge can be converted into a definite cost of the firm’s operations, especially where enough cases occur within a firm. In other situations, a given loss or hazard may be large and infrequent in relation to a firm’s oper­ations (such as the risk of fire), but over a large number of firms it could be considered as a "measurable" or actuarial risk. The firms can pool their risks, or a specialized firm - an insurance company - could organize the pooling for them.

Profit and loss are the results of entrepreneurial uncertainty. Actuarial risk is converted into a cost of business operation and is not responsible for profits or losses except in so far as the actuarial estimates are wrong.

Insurance in the US

The US property- and casualty-insurance regulation system claims to perform two main functions. First, to ensure insurers hold enough capital to remain solvent. All developed countries regulate solvency of their insurance companies in one way or another. The second function is to make insurance "affordable," that means price control. There are differences between states, but in most of the country, insurers need to have their rates authorized if they want to write insurance using them. The simplest way to improve insurer's solvency is to keep the premiums high, and to improve 'affordability' the premiums have to be low. Regulators claim they know how to strike the perfect balance.

The "affordability" function of the regulation resulted from the Sherman Antitrust Act. Historically, it was common practice for insurers to share their claims data for the purpose of insurance-rate making. Having access to good claims data meant that insurance companies could price and manage their business better, and expand and enter new market segments. The Sherman Act became effective for insurance in 1944, when the Supreme Court decided that insurance was interstate commerce and therefore should be regulated by Congress. As a result, the useful practice of data sharing, was outlawed by federal antitrust regulation.

But before the era of cheap computers, insurance could not exist without the data-sharing arrangements. So the McCarran-Ferguson Act was introduced in 1945, allowing the industry to return to the old practices but instructing the states to "protect" customers. And so, government involvement in rate making was mandated, without eliminating the allegedly undesirable claims-data sharing.

As is usually the case with other forms of price control, insurance-pricing regulation creates shortages. For example, since 1977 the Massachusetts Division of Insurance has been setting individual auto insurance rates for the entire state. Every insurer operating in the Commonwealth has had to use the government rates or leave the state. Since then, the number of insurers has fallen from more than 100 to just 19. In 2008 was the situation so dire that the current commissioner actually decided to liberalize the regime slightly to prevent more citizens from driving uninsured.

Insurance in the UK

Until recently, British property and casualty pricing was totally unregulated. Regulators concentrated on the solvency function. The long tradition of freedom of enterprise resulted in the emergence of the unique London market of insurance. For centuries, London was the only place on Earth where it was possible to place big and nonstandard risks. Even today, if one wants to insure a power plant or a system of telecommunication satellites, London is the place to get it done.

The lack of pricing regulation in the United Kingdom resulted in a large number of pricing innovations being developed and tested there. A good example is the so-called GLM statistical approach, a mathematical methodology developed by two British actuarial software companies^{[citation needed]} in the late '90s. Stripped-down versions of this innovation have since been exported to the United States and implemented with a few years' lag. Eventually, even the regulators started using GLM for granting rate approvals.

The same process is happening with actuarial-reserving and capital-modeling techniques and software. Since excessive regulation in the United States cripples innovative actuarial thought, most of the inventions are being developed in the United Kingdom and simply shipped across the Atlantic.

The less-regulated market gives Britons access to better insurance services. For example, a very sophisticated broker market has developed in the United Kingdom, providing policyholders with specialized products and advice. Complex nationwide software platforms created by the broker community allow huge price-comparison websites to provide millions of policyholders with binding quotes from nearly a hundred insurers in a few minutes.

Another example is the ease with which new insurance products can be created. In the US, the state regulators get very involved in the classification rules, underwriting guides, and even wording of the insurance contract. As a result, most private motor policies written in the last 30 years in the US have been written on one of the few standard ISO forms or some modifications of those. In the United Kingdom, where consenting parties are freer to enter an insurance contract of their choice, independent insurance brokers provide dozens of different policy wordings tailored to specific market segments. That means more choice for the customer.

External links

• Wikipedia on insurance