Tag Archives: Risques

Is there discrimination against the poor?

(With Laurence Barry, we wrote a short article on discrimination against the poor, in French)

In 2013, Martin Hirsch (former director of Emmaüs and Assistance publique – Hôpitaux de Paris) stated “it’s getting expensive to be poor”. This reality was confirmed by a recent study, in France, by the Banque Postale*, which showed that on average, a poor household has to pay 1,500 euros more each year to access the same goods and services as a better-off household, introducing a “double poverty penalty**”. Unfortunately, insurance is not left out: the use of credit scores in many countries reinforces what could be a form of discrimination against the poor. In the United States, where the practice is more common than elsewhere, a commission of inquiry recently tried to explain the link between credit score and claims frequency: is it because, as some insurers argue, people with lower scores are also less careful than others? Or is it because, having less financial means than others, they more naturally ask to be compensated for the losses incurred? And, in this second case, are we not also making them pay twice for their condition?

From excellence to wealth as a virtue

On what criteria do we admire people? For the Greeks, excellence, or arête (ἀρετή), was a major virtue. This excellence went beyond moral excellence: in the Greco-Roman world, the term evoked a form of nobility, recognizable by the beauty, strength, courage, or intelligence of the person. Now this excellence had little to do with wealth: thus Herodotus is astonished that the winners of the Olympian games were content with an olive wreath and a “glorious renown,” peri-bones (περὶ ἀρετῆς). In the Greek ethical vision, especially among the Stoics, a “good life” does not depend on material wealth – a precept pushed to its height by Diogenes who, seeing a child drinking from his hands at the fountain, throws away the bowl he had for all crockery, telling himself that it is again useless wealth.

Greek society is nevertheless a deeply hierarchical society, even if it is organized around values other than material wealth. We can then ask ourselves at what point in Western history wealth became the measure of all things. One thinks then of Max Weber’s theory: the ethics of Protestantism pushes for work and earthly success as a revelation of a divine election to come: the rich of this world would be the chosen of the next. In the same way Adam Smith, taking a critical look at the birth of capitalism in the society of his time, titles a chapter of The Theory of Moral Sentiments (1759) “Of the corruption of our moral feelings occasioned by that disposition to admire the rich and great, and to despise or neglect the poor and lowly.”

Today, the cult of wealth seems to have never been so strong and material success is almost elevated to the rank of virtue. On the other hand, poverty becomes a stigma that is hard to get rid of; but history shows us that this is not natural.

From “good” to “bad” poor

Indeed, the poor have not always been “bad”. As Fulconis & Kikuchi (2017) remind us, the Church has largely contributed to disseminating the image of the “good poor”, as it appears in the Gospels: “happy are you poor, the kingdom of God is yours”; or “God could have made all men rich, but he wanted there to be poor people in this world, so that the rich would have an opportunity to redeem their sins”. Beyond this, the poor is seen as an image of Christ, Jesus having said “whatever you do to the least of these, you will do to me”. Helping the poor, doing a work of mercy, is a means of salvation.

For Saint Thomas Aquinas, charity is thus essential to correct social inequalities by redistributing wealth through almsgiving***. In the Middle Ages, merchants were seen as useful, even virtuous, since they allowed wealth to circulate within the community. Priests played the role of social assistants, helping the sick, the elderly and the disabled. The hospices and xenodochia of the Middle Ages (ξενοδοχεῖον, that “place for strangers,” ξένος) are the symbol of this care of the poor. And quite often, poverty is not limited to material capital, but also social and cultural, to use a more contemporary terminology.

Towards the end of the Middle Ages, the figure of the “bad poor”, the parasitic and dangerous vagabond, appeared. In line with Weber, Todeschini (2021) insists on the increasing value attached to work and social “usefulness”. Brant (1494), the first, begins to denounce these welfare recipients, “some become beggars at an age when, young and strong, and in full health, one could work: why bother”. For Fulconis & Kikichi (2017), this mistrust is reinforced with the great pandemic of the Black Death. Colombi (2020) returns to this turning point, at the end of the Middle Ages, when in the cities, the bourgeois closed their districts with chains, to avoid that “poor and foreigners” settle there. The hygienic theories of the end of the 19th century added the final touch: if fevers and diseases were caused by insalubrity and poor living conditions, then by keeping the poor out, they were protected from disease.

Poor… by choice?

In the words of Mollat (2006) “the poor are those who, permanently or temporarily, find themselves in a situation of weakness, dependence, humiliation, characterized by the deprivation of means, variable according to the times and the societies, of power and social consideration”. Recently, Cortina (2022) proposed the term “aporophobia”, or “pauvrophobia”, to describe a whole set of prejudices that exist towards the poor. The unemployed are said to be welfare recipients and lazy, says Lamy; it is also the famous “where there is a will there is a way”, (which can be found in contemporary expressions such as “those who don’t want to do anything, those who don’t want to work” or “I’ll cross the street and find you a job”). And as is often the case, these prejudices, which stigmatize a group, “the poor”, lead to fear or hatred, generating an important cleavage, and finally a form of discrimination. Cortina’s (2022) “pauvrophobia” is a discrimination against social precariousness, which would be almost more important than “usual” forms of discrimination, such as racism or xenophobia. Cortina ironically notes that rich foreigners are often not rejected.

But these prejudices also turn into accusations. Szalavitz (2017) thus abruptly asks the question, “Why do we think poor people are poor because of their own bad choices?”. The “actor-observer” bias provides one element of an answer: we often think that it is circumstances, which constrain our own choices, but that it is the behavior of others that changes theirs. In other words, others are poor because they made bad choices, but if I am poor, it is because of an unfair system. This bias is also valid for the rich: winners often tend to believe that they got where they are by their own hard work, and that they therefore deserve what they have.

Social science studies show, however, that the poor are rarely poor by choice, and increasing inequality and geographic segregation do not help. The lack of empathy then leads to more polarization, more rejection and, in a vicious circle, even less empathy.

Links between wealth and risk(s)

To discriminate is to distinguish (exclude or prefer) a person because of his/her “personal characteristics”. Can we then speak of discrimination against the poor? Is poverty (like gender or skin color) a personal characteristic? In Quebec, “social condition” (which explicitly includes poverty) is one of the protected variables and therefore prohibited discrimination. This is not the case in France. As Barry & Charpentier (2021) remind us, when actuaries calculate a premium, discrimination directly linked to risk, and provided that the variable is not protected, is generally seen as legitimate. However, it is well known that wealth or social status has a lot to do with risk, whatever it may be. At the global level, Denis Hatzfeld reminds us that “earthquakes are much more deadly in poor countries than in developed countries, which have gradually learned to protect themselves from them. Similarly, Le Hir (2010) states that “A schoolboy is 400 times more likely to die in an earthquake in Kathmandu than in Tokyo”.

This is true for most risks. In France, we find in the deaths due to road accidents 3% of executives and 15% of workers, while they represent nearly 20% of the working population each, according to ONISR (2022). Blanpain (2018) points out that the gap in life expectancy at birth is 13 years between the most affluent and the most modest men. Recently, Allain (2022) noted that the most modest French people, at comparable age and sex, had almost three times more diabetes, twice as much liver or pancreatic disease, 1.6 times more chronic respiratory disease, etc. than the average. Cambois, Laborde and Robine (2008) similarly noted that the number of years of disability for blue-collar workers is also much higher, over a shorter life span on average.

The use of credit scores in insurance

In North America, companies such as Experian, Equifax and TransUnion keep records of the borrowing and repayment activities of all individuals with bank accounts. FICO (Fair Isaac Corporation) offers a formula to convert these records into a score, the credit score. This score is a function of debt and available credit, income and its variations, and history of incidents, bankruptcies or simple delinquencies. It is often seen as an assessment of a person’s creditworthiness, or the likelihood that he or she will repay debts. It is by nature closely related to income (Crowe 2022), making the credit score a robust proxy for wealth. Fourcade and Healy (2013) show that, as a good credit score has become a necessary condition for obtaining credit and maintaining purchasing power, this system has come to create an impenetrable wall between advantaged and disadvantaged classes. In a sense, a bad credit score becomes a self-fulfilling prophecy: people with a bad score (and therefore considered high risk by banks) become dependent on short-term alternatives. This increases the costs of future financing, thus the probability of default (François 2021) but also the probability of not finding a job (this score can be requested by employers****). “Using credit scores to punish the poor exacerbates existing socioeconomic inequalities,” Wang (2018) thus aptly asserts.

As an example, Table 1 compares a few parameters based on people’s credit scores, including the rate obtained for a $150,000 loan over a 30-year horizon, and the average insurance premium charged for car insurance (for a 30-year-old driver, driving 20,000km per year, in the city).

Table 1: Actual price of a $150,000 loan and the amount of a car insurance premium (for comparable coverage and risk profile), based on credit score (ranging from 300 to 850). Source: InCharge Debt Solutions.

Kiviat (2019) has extensively studied the use of credit scores in the pricing of auto insurance in the United States. The US regulator has indeed looked at the proven link between bad credit score and auto risk. What explanation can be given for this correlation? Wouldn’t the score be an indicator of poverty and not a proxy for the driver’s prudence as insurers claim? For if social condition is not a protected variable as it is in Canada, it is still largely associated with skin color, which is a prohibited variable. Discriminating on the basis of credit score could therefore amount to prohibited racial discrimination. By examining the debates around these issues, Kiviat highlights the ethical complexity of using facially neutral variables. And if, as noted above, poor living conditions increase risk in general, it is worth asking whether insurance is not helping to apply the double whammy that Martin Hirsch spoke of to the poor.


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Caplovitz, D. (1963). Poor pay more; consumer practices of low-income families. Free Press.
Colombi, D., (2020). Où va l’argent des pauvres. Payot.
Cortina, A. (2022). Aporophobia: Why We Reject the Poor Instead of Helping Them. Princeton University Press.
Crowe, A. (2022). The Relationship Between Income and Credit Score. Credit Sesame Personal Finance and Credit Survey,
Fourcade, M. & Healy, K. (2013). Classification situations: Life-chances in the neoliberal era, Accounting, Organizations and Society, 38 (8): 559–572
François, P. (2021). Catégorisation, individualisation. Retour sur les scores de crédit. Chaire PARI, WP #24.
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Lamy, T. (2022) Assistés, paresseux… pour 50% des Français, les chômeurs sont responsables de leur situation. Capital, décembre 2022
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Le Hir, P. (2010). Catastrophes et pauvreté, la double peine. Le Monde, 22 janvier,
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* Study entitled “Study of the double poverty penalty in France“, published at the end of 2022 by Action Tank Entreprise & Pauvreté, Boston Consulting Group and the Banque Postale

** This phenomenon, widely studied in the 1960s, see Caplovitz (1963), is known in economics as the “boot theory” (popularized by Pratchett’s novel (1993)), “take boots, for example. A really good pair of leather boots costs fifty dollars. But an affordable pair of boots, which were sort of OK for a season or two and then leaked like hell when the cardboard gave out, cost about ten dollars (…). But the thing was that good boots lasted for years and years.”

*** The notion of redistribution can be contrasted with the “Matthew effect” as defined by Merton (1950). Inspired by a passage from the Gospel according to St. Matthew (which he reverses), he states that “to him who has shall be given, and he shall have plenty; but to him who has not, even that which he has shall be taken away.”

**** This rating practice is actually not new and dates back to the late 19th century: Josh Lauer (2017) shows that as early as 1870, so well before big data or even credit cards, US banks employed assessors to make financial strength reports on people. For Lauer, it is a gigantic surveillance system that was set up at the beginning of the 20th century, leading to the algorithmic credit scores as we know them today (see also François (2021)).

Climate risk, some slow long-term trend?

In most of the scenarios that talk about climate change, we are told about projections for 2050 or even 2100, time scales that are so far away that we have the illusion that the major risks will only be for “future generations“. And these scenarios evoke the possibility of a rise of 1, 2 or 4°C in several decades, a figure that should seem derisory when we are used to seeing temperatures vary by 10 or 20°C within the same day, by 15, 20 or even 30°C between winter and summer. In this context, how can we finally think seriously about climate risk?  Continue reading Climate risk, some slow long-term trend?

Le risque climatique, une tendance lente de long terme ?

Il s’agit ici de la version préliminaire de l’article depuis paru dans Risques, à l’automne 2022.

Dans la plupart des scénarios qui évoquent les changements climatiques, on nous parle de projections avec pour horizon 2050, voire 2100, des échelles de temps tellement lointaines qu’on a l’illusion que les risques majeurs seront seulement pour les « générations futures ». Et ces scénarios évoquent des possibilités de hausse de 1,2 ou 4°C d’ici plusieurs décennies, chiffre qui devrait sembler dérisoires quand on est habitué à voir des températures varier de 10 ou 20°C au sein d’une même journée, de 15, 20 voire 30°C entre l’hiver et l’été. Dans ce contexte, comment penser enfin sérieusement le risque climatique ?  Continue reading Le risque climatique, une tendance lente de long terme ?

On consequences of Goodhart’s law

This post was initially written in French, in the Winter 2021.

As Marilyn Strathern stated, Goodhart’s Law says that “when a measure becomes a goal, it ceases to be a good measure.” There are many economic applications, but this law also helps to understand the dangers of algorithmic decisions, or to explain the difficulty of using the data available since the beginning of the SARS-CoV-2 COVID-19 pandemic.

Continue reading On consequences of Goodhart’s law

The scientific approach in times of crisis

This post was initially written in French, and published in April 2020.

In a conference given on February 13, 2020[i], entitled Against the Method, Didier Raoult stated “I have never done randomized trials […] to do that on infectious diseases, it makes no sense“. This view was repeated in a more detailed article, where Didier Raoult defended (what he called) “the morality [and] the humanism” of the Hippocratic oath against “the method” (and “mathematics”). As he reminds us, doing control groups is “telling the patient that we are going to give him at random either the drug we know works or the drug we do not know works” (Raoult (2020a, 2020b)). While this method of randomized experiments is now hailed in all disciplines – as the Nobel Prize in Economics awarded in 2019 to Esther Duflo, Michael Kremer and Abhijit Banerjee reminds us – how can a researcher take such a position today?
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What responsibility for the algorithms?

This post was initially written in French with Rodolphe Bigot (lecturer at the University of Picardie Jules Verne), in the Winter 2020, and follows a previous post entitled Rethinking responsibility and causality.

Historically, algorithms were content to provide decision support, leaving a human being to make the decision, but experiments are underway, with autonomous systems, making decisions, whether it be car driving systems, or predictive justice algorithms, as shown by Huss et al. (2018). This autonomy, which basically means the “ability to act freely” also refers to the idea of “governing oneself by one’s own laws“. But what is the responsibility of the decision maker in the case of a prediction that leads to harm?
Continue reading What responsibility for the algorithms?

Rethinking responsibility and causality

This post was intially written in French with Rodolphe Bigot (lecturer at the University of Picardie Jules Verne) in the Fall 2019.

In 150 years, the concept of responsibility has evolved a lot, without ever disappearing. And today, we find it in a variety of contexts, from ecological or industrial disasters – we will evoke a “precautionary principle” that has blurred the very notion of causality – to “intelligent machines” – which leave the role of helper to finally make decisions in our place.
Continue reading Rethinking responsibility and causality

Insurance and discrimination, what role for actuaries?

This post was initially published in French in September 2021.

The essential role of an actuary in charge of pricing is the segmentation of the portfolio (or “insurance classification” in English), corresponding to a discrimination activity (mathematically speaking) in the sense that the actuary will look for the most “discriminating” variables, to explain another one (in relation with the loss experience). But in the legal sense, discrimination is forbidden by law, which places the actuary in an often delicate and complex position.
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The myth of interpretability and explicability of models

This article was initially written in French and published in November 2021.

Rubinstein (2012) claimed that “in economic theory, like Harry Potter, the Emperor’s New Clothes, or King Solomon’s Tales, we play in imaginary worlds. Economic theory invents tales and calls them models. An economic model is also somewhere between fantasy and reality (…) The word ‘model’ sounds more scientific than the word ‘fable’ or ‘tale’, but I think we are talking about the same thing“. Today, very often, learning models will build a model, based on learning data, and the actuary’s job will be to make sense of it, to find the story – the fable – that it is possible to tell. Continue reading The myth of interpretability and explicability of models

Reconciling collective risks and individual decisions

This article was co-authored with Laurence Barry, and initially written in French during the 2020 Summer.

The early days of the SARS-CoV-2 (or COVID-19) pandemic have seen a proliferation of calls for “individual responsibility”, starting with strong calls (and even an obligation in some countries, including France) to stay home as much as possible in the early spring of 2020, before it became mandatory to wear a mask in public (often closed) places during the summer. To paraphrase Coluche « dire qu’il suffirait que les gens restent chez eux pour qu’on puisse sortir… ». This call for each person’s responsibility is made in the name of all and for the good of all, symbolizing this very particular solidarity that the pandemic reminds us of: the risk that I choose to run does not only concern my person but also constitutes a risk for those around me. To formulate it in probabilistic terms, McKendrick (1926) stated that “the probability of occurrence increases with the number of existing cases“. This conception of individual responsibility, which is quite intuitive a priori, actually runs counter to the classical conception of economics: the rational (and responsible) individual makes choices that concern him, and that concern only him. The collective good is deduced by summing up individual utilities, independent of each other. But here is the problem: with the epidemic, an interdependence of utilities is created, so that the well-being of so-and-so, who chooses not to wear a mask, can harm the health and therefore the utility of many other people. How then can we think in economic terms of this “individual responsibility” in the context of the epidemic?

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The taboo of the exponential

For Carl Sagan, “if you understand exponentials, the key to many of the secrets of the universe is in your hand”. But not everyone seems ready to unlock the secrets of the universe. Thus, in mid-November 2021, more than 18 months after the beginning of the SARS-COVID 19 pandemic, the Minister of Health stated “the circulation of the virus has accelerated for a few weeks now, with an increase of 30% to 40% per week. We are not yet in a so-called exponential phase” (quoted in Ouest France (2021)). Since an increase at a constant rate is precisely the definition of “exponential growth”, one may wonder about this statement, which reveals either a lack of numeracy on the part of our leaders, or an element of language, with the word “exponential” becoming a taboo word that should not be mentioned?

(this is the English tranlation of a post published in January 2022)

Continue reading The taboo of the exponential

Modeling contagion

Two years after the beginning of the COVID-19 pandemic, due to the SARS-CoV-2 virus, we have all become (pseudo)-experts in contagion models. But beyond diseases, these models based on networks of interactions between people are also commonly used to describe the spread of a computer virus, of social norms, of an idea or a rumor in a society, or of an economic crisis, as Kucharski (2020) reminds us.

(this is the English tranlation of a post published in April 2022)

Continue reading Modeling contagion

Are there acceptable deaths? or how to end a pandemic

Zylberman (2021) noted that “this pandemic began with the first case, but it will not end with the last case (…) one cannot date the end of a pandemic and the beginning of an endemic. Yet, in mid-April, the French president slipped in an interview (Garnier (2022)) that “society [is] on its way out of COVID” implying that the SARS-CoV-2 pandemic was over. At the same time, the virus was still killing more than 100 people a day, according to official statistics. While it is legitimate to question what exactly is a “COVID death“, it may seem surprising that 100 deaths per day (for more than three consecutive months) were met with such indifference, and that such a level was interpreted as the end of the pandemic.

(this is the English translation of a blog post published a few days ago)
Continue reading Are there acceptable deaths? or how to end a pandemic

Y-a-t-il des morts acceptables ? ou comment finir une pandémie

Zylberman (2021) notait « cette pandémie a commencé avec le premier cas, mais elle ne se terminera pas avec le dernier cas (…) on ne peut pas dater la fin d’une pandémie et le début d’une endémie ». Pourtant, mi-avril, le président français a glissé dans une entrevue (Garnier (2022)) que « la société [est] en sortie de COVID » laissant entendre que la pandémie de SARS-CoV-2 était terminée. À la même époque, le virus tuait encore plus d’une centaine de personnes par jour, selon les statistiques officielles. S’il est légitime de s’interroger sur ce qu’est précisément un « mort de la COVID », il peut sembler étonnant que 100 morts par jour (pendant plus de 3 mois consécutifs) aient suscité autant d’indifférence, et qu’un tel niveau soit interprété comme la fin de la pandémie.
Continue reading Y-a-t-il des morts acceptables ? ou comment finir une pandémie

Modéliser la contagion

Deux ans après le début de la pandémie COVID-19, due au virus SARS-CoV-2, nous voilà tous devenus (pseudo)-experts en modèles de contagion. Mais au delà des maladies, ces modèles basés sur des réseaux d’interactions entre personnes sont aussi couramment utilisés pour décrire la propagation d’un virus informatique, de normes sociales, d’une idée ou d’une rumeur dans une société, ou d’une crise économique, comme le rappelle Kucharski (2020).

Continue reading Modéliser la contagion