Researching insurance screenings
February 9, 2010
This figure is my own representation of an exchange ― reconstructed from interviews with people working in insurance companies― between a possible user and an insurance seller who works for one of the health insurance firms in Chile. Probably this encounter happens after the salesperson, interested in increasing her client portfolio, contacts a possible user who has accepted to have an introductory meeting. When they meet, the seller asks certain socio-demographic information (sex, age, family number, income) from which it is possible to suggest the array of insurance policies available for the prospective user, and the premiums and type of coverage in each case. If the potential user is still interested; she will be asked to fill a ‘medical declaration’ which, for the most part, focuses on her previous medical history. The meeting finishes here. At the next meeting, the salesperson plays a different role; now her work is informing the outcomes of the medical declaration. There are three main options: accepted without restrictions; accepted but with a restricted policy; or not accepted. Restrictions and rejections are connected to the user’s medical history, or what is called ‘pre-existences’, that is, past medical events that suggest potential future medical expenses which insurers are legally allowed to not cover. This is not so different to many other commercial interactions we face every day, that are generally seen only interesting for the experts directly involved in these industries. However, I think, this opens at least three different research agendas of social studies of finance.
First, like other risk screening processes studied by Deville and Poon, this is an exchange that apart of human beings, involves many other type of actors, such as forms, objects, affects, and so on. In this case, when the seller gathered socio-demographical information and proposed certain policies, she was referring to an already assembled network. Here the main actor is the actuarial department. This department is in charge of developing new information systems by matching the available statistical information and potential costs of medical provisions. In order to do that, they produce a virtual object, namely, a population’s potential health situation and their potential costs. These are virtual because they are not material (a tendency in statistical software) yet they are regarded as objects because from the moment they are produced they are assumed as real, and cause a real impact upon the next stages of the network. The medical declaration is evaluated by a different section known as ‘medical comptrollers’. By using previous epidemiological information, they can predict the future risk of new users, determining the existence of relevant pre-existences. Here two virtual objects are produced: the past medical history of a potential user and her possible future health. What is produced in both cases is not just virtual but multiple. The medical history developed by medical comptrollers is not the same as the medical history presented by the seller or to the way in which past medical events are conceived by the prospective user. At the same time, medical history will change depending on the kind of formulas used to merge medical statistics, on the form that registers this information, or in the event of changes taking place in the statistical information at hand.
Second, this exchange is embedded in wider processes. As discussed in a previous post, a long chain of events, including economists as main actors, had been relevant in shaping the form of this exchange. At the same time, as the director of one of the first private health insurance companies in Chile explained to me, from the beginning of the system in the early eighties, the statistical information that is available (and its ability to predict future events) has dramatically increased, changing the landscape of this industry. In fact, this is not just a matter of available technologies, but actuaries themselves have been a very scarce resource. This is not a professional degree offered at Chilean universities; therefore, insurance firms mostly hire experts from Argentina, where this profession is one of the specialisations in schools of business and economics. And finally, like car insurance, these are compulsory insurance policies which are much more regulated than other type of policies. In this sense, the clear division between actuarial department and medical comptroller has to do with that that this system’s regulation allows considering only two factors in their pricing tables: age and sex (of course: the formula used to connect these two variables with the potential health cost is owned by each firms). Then, instead of being included in the premium, medical history has been connected to potential exclusions.
Finally, this exchange also opens new social connections to be followed. As scholars inspired by the late Foucault have shown insurance is a technology of risk, and as such, what it does is pooling or connecting people under a common fund. This is made in different layers. First, in their risk screenings, new users are included in statistical populations that allow estimating their potential health expenses. Second, in case the insurance policy is bought, users are connected with other usersof the same type of policy. Most probably, they don’t know you, but your monthly withdrawn can help to pay their hospital in case they have an accident or they can help you if you are the one sick. In this sense, insurance is really important in producing what Durkheim called “organic solidarity”, or the modern situation that tie us to those that we don’t know. However private insurance does not work in the same logic than national welfare regimes. Pooling is not about building a national population, but about producing more delimited funds. We are not connected to all the costumers of our chosen insurer, but with those that are in our same group (for instance: men, young, etc.). We are actually connected to others, but we cannot join our “colleagues” because we cannot really who they are, or even the categories that tie us together. In this sense, this third potential stream of research, is not just about how this insurance exchange is embedded in wider political events or entangled in heterogeneous networks, but about following how it is central in assembling new collectives and social categories.