Peter G. Gosselin of the LA Times describes recent changes in catastrophe insurance markets, some of which have shifted risk from insurance companies to the government and individuals. For example, in many states the government has capped the total amount insurance companies must pay to policyholders after natural disasters. In these cases, the government agrees to cover any costs over and above the cap limiting the insurance companies' exposure to risk.
But the big change is the ability of insurance companies to assess risk at the individual level to a greater degree than ever before. This allows them to design policies and rates to match an individual's characteristics. Whether this is good or bad overall is an open question. While it improves the efficiency of insurance markets in a variety of ways, if winners and losers can be predicted accurately in advance insurance markets break down because there is no way to pool risk across individuals. For example, if one out of ten people will face high losses after an earthquake, and you can tell which person it will be in advance, there is no way share the risk across these ten individuals. Instead, one will face very high costs and nine very low costs - same average, but a different distribution (all else equal, e.g. the individual who faces the high rate may take preventative measures to reduce risk lowering overall and average costs).
In addition, with individual pricing there is a worry that the poor will face very high rates and be unable to afford insurance coverage. With the ability to assess risks at the individual level and predetermine winners and losers, each individual will, in essence, enter into a savings program that covers lifetime disaster costs with an individualized monthly premium. But if those who are poor also happen to be high risk, then many will not be able to afford insurance. If so, this shifts risk to the government and to private sector agencies such as non-profits that deliver aid since they will have to step in and help to some degree after a disaster.
I think that insurance companies should be allowed to vary rates according to factors within an individual's control, but factors beyond an individual's control ought to be pooled even if they can be identified a priori. For example, the risks of being born with a costly genetic problem ought to be shared across the population even if a prenatal blood test will reveal it, while the risks from smoking ought to fall on the individual. This may be difficult to define in practice, e.g. if we expect the an unemployed person to take any job that is open or face a cut in their unemployment benefits, is the decision to move and take a job in an area with a high earthquake risk fully within the individual's control? But mostly the lines are clear and I think it's a good guiding principle:
Insurers learn to pinpoint risks -- and avoid them, by Peter G. Gosselin, LA Times: Hemant Shah is in the business of creating catastrophes. The computers at Shah's Silicon Valley company, Risk Management Solutions Inc., contain mathematical models of every U.S. disaster from the 1812 earthquake ... in St. Louis to the 9/11 assault ... in New York, as well as 100,000 synthesized "extreme events."
RMS runs its disasters through your community — and sometimes right through your home — to see how you'd fare in a hurricane, hailstorm, earthquake, epidemic or terrorist attack. The firm sells its knowledge to insurance companies to help them decide whom to cover and how much to charge.
Since Hurricane Katrina last year, those decisions have been running pretty much in one direction. Based in part on RMS' predictions, companies ... have gotten out of some lines of coverage altogether ... and ... have spent the year dropping or paring back policies... And this may only be the beginning.
"Between hurricanes along the East and Gulf coasts and earthquakes along the West Coast, it is an open question whether the private insurance industry will continue to insure the coastline at all," said University of Pennsylvania economist Howard Kunreuther, one of the country's foremost authorities on disaster.
RMS is at the vanguard of a technological revolution that's reshaping the nation's ... property casualty insurance industry. The industry ... is embracing a new generation of powerful computer techniques to learn everything it possibly can about you — or at least people very much like you — your health, habits, houses and cars. It is using this new trove of data to replace traditional uniform coverage at uniform rates with an increasingly wide array of policies at widely varying prices.
Industry executives say the aim is to create a finely tuned system in which companies can better manage the risks they bear while consumers can more carefully pick the protection they need and pay just the right amount for it.
As insurers become more adept at the techniques, "American consumers can be more assured that their companies will be there when they need them to pay their claims," said Robert P. Hartwig, chief economist of the industry-funded Insurance Information Institute in New York. ...
But some regulators, economists and consumer advocates contend that the industry's growing use of sophisticated computer-aided methods is producing side effects that could undermine the very nature of insurance.
Traditionally, insurance companies group people facing similar dangers into pools. Company actuaries determine how often events such as illnesses or accidents have befallen pool members in the past and how costly those occurrences have been. Insurers set their rates based on the frequency and loss histories...
A key characteristic of this approach is that there's an incentive for insurers to assemble pools as big as possible. The bigger the pools, ... the more accurate their frequency and loss numbers.
But the question has always hung in the air: What if insurers could ... predict who's more likely to be hit with setbacks in the future? What if they could charge such customers steeply higher rates, or avoid them altogether? Wouldn't that boost profits, making shareholders and executives happy, and ensure that insurers had plenty of cash on hand to pay the smaller claims of the safer customers?
That is the promise of catastrophe models like RMS'. And it's the promise of new "data-mining" methods that let companies use a person's income, education or ZIP code to predict future claims. That in turn encourages insurers to raise rates or refuse coverage for the very people who need it most — low- and moderate-income families, for example, or those who've suffered such setbacks as unemployment.
As the industry expands its ability to "slice and dice" customers and applicants, Texas Insurance Commissioner Mike Geeslin, among others, worries that "the risk-transfer mechanism at the heart of insurance could break down." If that happens, Geeslin warned, "insurance will stop functioning as insurance."
Rushing into harm's way?
By providing companies with so much information about individual properties and policyholders, new techniques ... are riveting insurers' attention on how choices made by individuals are raising the cost of disasters, while dampening industry interest in the kind of broad risk-reduction measures that were once a hallmark of American insurance.
The industry now contends that one of the chief reasons Katrina and other recent disasters caused so much damage — and produced such huge insurance claims — is that Americans are rushing into harm's way by moving to hurricane-prone coasts and earthquake zones like California. And one of the chief reasons, according to this argument, is that they're being subsidized by homeowners insurance premiums that have been held artificially low by state regulators.
The argument has attracted a wide following in the last year both inside the industry and out. ... The solution, according to industry leaders and many policymakers, is to let insurers charge higher rates in danger zones to discourage people from moving there, and to make those who live there pay for the additional risks they run.
The problem is that some key statistics don't seem to support the argument. Though government statistics do show various sorts of growth in the nation's danger zones, they don't show it occurring at an appreciably faster pace than for the country as a whole. ... What this suggests is that rising disaster damage and costs are more a function of demographics than insurance rates.
"You simply cannot make the case from the numbers that America's coastal counties have grown at a disproportionately faster rate than the country as a whole over the last 25 years," said Judith T. Kildow, who runs the largely government-funded National Ocean Economics Program at Cal State Monterey. If anything, Kildow said, "the numbers show that growth is now greater inland." ...
Of course, the latest round of rate hikes and coverage cutbacks is not RMS' handiwork alone... Indeed, many of the recent changes are extensions of ones begun after the nation's last major run-in with natural disasters, including the 1989 Loma Prieta earthquake in the Bay Area, the 1991 Oakland firestorm, 1992's Hurricane Andrew in Florida and the Northridge earthquake in 1994.
Those disasters destroyed tens of thousands of homes and uprooted hundreds of thousands of people. They also scrambled the finances of many insurance companies... The industry responded by seeking state help and changing the terms of homeowners policies.
After lengthy political battles with state regulators, insurers were effectively relieved of responsibility for covering the wind and quake dangers that had just cost them so dearly. Those jobs were shifted to a set of state-created companies and agencies.
In California, the insurers were no longer required to sell earthquake insurance as part of their homeowners policies. Henceforth, most homeowners would get that coverage from the California Earthquake Authority. ... CEA's creation effectively capped the amount that the industry could lose to quakes at a comparatively modest few billion dollars.
In Florida, the state set up a fund to provide insurers with low-cost insurance of their own to help cover wind damage claims. In addition, Florida officials established what eventually became Citizens Property Insurance Corp. as a home insurer of last resort...
The industry's other response was to begin changing the language in homeowners policies. Industry executives maintain that the changes have been solely intended to clarify what companies cover. ... But regulators say many of the changes have shrunk the protection that policyholders get.
"Insurers are taking on a helluva lot less risk than they used to," complained California Insurance Commissioner John Garamendi.
The story of a single change illustrates the gulf that has opened between what insurers say they are selling and what most homeowners think they are buying.
When the late-1980s-to-early-'90s disasters hit, the gold standard for homeowners was the "guaranteed replacement cost" policy. ...[R]egulators interpreted "guaranteed replacement cost" to mean that insurers had to replace a destroyed home essentially no matter what the ... expense... And most policyholders — both before and since the '80s and '90s disasters — have assumed that this is the kind of coverage they purchased. ...
After the 1991 disaster, companies began dropping guaranteed replacement cost policies in favor of similar-sounding but substantially more limited "extended replacement cost" ones. Under the latter policy, an insurer is obligated to pay only up to the dollar amount ... plus, typically, an additional 20%. By now, industry executives say, the former type of policy has all but disappeared.
The problem is that few policyholders understood what was at stake in the word change. Encouraged in part by industry advertising, they continued to believe that their insurance would replace their houses if they were destroyed. ...
[P]olicyholders had better prepare themselves; more changes are on the way.
Give RMS a street address almost anywhere in the country, and it can pull up what's at the location, and tell you when it was built and out of what. Then it can run hundreds, sometimes thousands, of simulated disasters across the structure. ...
At the same time, so-called data-mining companies use years of insurance company data to generate a computerized library of correlations between claims and such personal attributes as income, education, ZIP code and credit score. That library can then be used to predict whether that person will file a claim in the future. ...
RMS' techniques and those of the data-miners share three crucial similarities: They're only possible because of recent advances in computing power. ... And they have set off a mad scramble among insurers to slice their once-broad pools of policyholders into finer risk categories.
Northbrook, Ill.-based Allstate now sorts its home and auto policyholders into 384 categories, up from the three that it used until a few years ago. At Bloomington, Ill.-based State Farm, the nation's largest auto and home insurer, the number of categories the company uses has increased 100-fold. At Cleveland-area-based auto insurer Progressive, the number runs into the millions.
Insurance executives say that the rush to refine is producing positive results. It gives companies more detailed information about the risks they bear; allows them to offer lower rates to, for example, homeowners who live in safe places; and lets firms individualize policies to fit each policyholder's needs. ...
But the ever-finer slicing appears to be having other effects as well, ones that worry a variety of regulators and insurance theorists.
States like California and Maryland have banned insurers from using credit scores, ZIP codes and other factors in deciding whether to cover someone, arguing that they unfairly discriminate against the poor and minorities. Washington state officials complain that the proliferation of categories and risk factors has so confused policyholders that the state now requires a company to provide customers written explanations whenever it gives them anything but its best rate.
"If I have a lot of house fires, [insurance companies] should charge me more," said Washington state Insurance Commissioner Mike Kreidler. "But when insurers reach and grab information like credit or occupation or education, people say, 'Wait a minute. I thought we were talking about insuring my home or auto. What does occupation or education have to do with it?' " ...
Perhaps most broadly, the new techniques appear to be dismantling much of what insurance traditionally has been about. Until now, insurance of almost every type has performed two key functions.
The first is pooling. Anyone buying an insurance policy is, in effect, kicking into a pot that covers the cost of future bad events befalling a few of their number. The second is providing cross-subsidies. Some buyers are more likely to get nailed by bad events because, for example, their genetic makeup leaves them prone to disease or their houses are not built to the latest code, and others are less likely.
But for the most part, insurers have not known which policyholders fall into which category, so they have charged generally uniform rates, which means that those in the "more likely" category get a subsidy by being able to pay the same as those in the "less likely"...
However, as disaster models such as RMS' and data-mining provide companies with increasingly detailed knowledge about individual policyholders, there are fewer and fewer pockets of such ignorance and therefore less and less room for cross-subsidies.
"Insurers are squeezing subsidies out of the system across the board, and they're going to carry it absolutely as far as they can," said Columbia University economist Bruce Greenwald.
On its face, the trend might seem a positive one. Among other things, it means that policyholders with good genes and safe houses can enjoy lower rates. But at least in some cases, Greenwald and others argue, the end of cross-subsidies spells trouble.
In the case of healthcare insurance, it would mean that a substantial fraction of the nation could no longer afford coverage. In the case of homeowners insurance, it ultimately might mean that large swaths of the nation's coasts become unaffordable for all but the wealthiest Americans who can bear unsubsidized rates.
And this may not be where the dismantling ends. Some analysts say that the same kind of modeling and data-mining that's helping companies squeeze out cross-subsidies could end up squeezing out much of the pooling in insurance as well.
As insurers use the new techniques to get ever-more-refined estimates of what individual policyholders are likely to cost in the future, they may be tempted to charge people closer and closer to full freight for treating an illness or rebuilding a fire-damaged home. Then even those who benefited from the end of cross-subsidies could see their rates go up as they effectively are asked to pay their own way, rather than share the cost by pooling with others.
Industry executives argue that competition among insurers will prevent such an eventuality. "I don't think you're ever going to get to the extreme of no pooling," said Greg Heidrich, senior vice president of policy with the Property Casualty Insurers Assn. of America, one of the industry's largest trade groups. But regulators are not as confident.
"When you begin to tailor or refine policies," said Alessandro A. Iuppa, president of the National Assn. of Insurance Commissioners, which represents the nation's 50 state insurance departments, "you could end up with people basically covering their own losses."
But that, of course, would not be insurance. ...