Tag Archives: interview

Insuring an uninsurable world – the pricing actuary’s Mission Impossible?

In InsuranceERM, David Walker published, yesterday  Insuring an uninsurable world – the pricing actuary’s Mission Impossible?

“Actuarially, it is entirely possible – and often documented – that the technical premium reflecting pure risk without political intervention, mutualisation or capping varies by a factor of 30 or more, depending on exposure to flood or forest fire risk,” says Arthur Charpentier, author of a 2024 book Insurance, Biases, Discrimination and Fairness and professor of mathematics at the Université du Québec à Montréal. This level of variation is exhibited in real life, too. Annual premiums for high-risk properties in Canadian provinces of Ontario and Alberta can exceed C$3,000 ($2,185), “compared to under C$100 elsewhere”.

In Canada, premiums are very moderate, as flood insurance is often excluded from basic policies, and “overland flood” coverage remains limited and capped (“Overland flooding … is typically not covered by a standard policy. Optional residential overland flood coverage is now offered by many insurers for the majority of homes across the country and is based on riskhttps://www.ibc.ca/stay-protected/severe-weather-safety/flood-and-water). However, technical premiums, calculated by modelers (JBA, Fathom, Swiss Re), vary by a factor of ×20 to ×50, depending on proximity to a watercourse, elevation, soil type, and flood frequency. Some properties in Ontario and Alberta have an expected annual cost of more than $3,000/year, compared to <$100 elsewhere. The report “Adapting to Rising Flood Risk” (Federal Task Force, 2022) states “Total residential flood risk in Canada… $2.9 billion per year. 89.3% is concentrated in the top 10% highest risk homes” (https://www.publicsafety.gc.ca/cnt/rsrcs/pblctns/dptng-rsng-fld-rsk-2022/index-en.aspx). This means that the most exposed minority accounts for almost all of the expected annual loss, reflecting a high degree of risk heterogeneity—the basis for justifying highly differentiated technical premiums. The same report states, “In high-risk areas, flood insurance is cost-prohibitive for Canadians, if available at all, and especially so for low-income households. In some areas, risk-based insurance premiums could reach $10,000-15,000 or more for flood endorsements alone, on top of other home insurance costs.” The actual actuarial cost is rarely passed on to the buyer, but private insurers take it into account by sometimes refusing to offer coverage or by excluding certain areas. In fact, actuarially, it is entirely possible—and often documented—that the technical premium (the one that reflects pure risk, without political intervention, mutualization, or capping) varies by a factor of ×30 or more depending on exposure to flood (or forest fire) risk. This is true in Canada, Europe, and Australia, even though this technical reality is often invisible to the insured due to political adjustment or solidarity mechanisms. For example, in France, the observed premium is uniform: 12% of the MRH contract via the CatNat scheme, regardless of the risk. But analyses show that the “real” actuarial premium could vary by a factor of 20 to 30 between a house in a non-flood zone and one in a red zone of the PPRI. Some municipalities have a loss ratio 30 times higher than the national average, but this difference is completely smoothed out. This is not the case in Germany, where flood insurance (Elementarschaden) is optional and therefore not widely mutualized. There, the commercial premium often reflects the risk more accurately, with differences of ×15 to ×30 for the most exposed areas. Three factors are often cited as reasons for this: Spatial risk heterogeneity (one neighborhood may be partially located in an area at risk of a hundred-year flood, while another, in the same zip code, is completely safe); Increase in property values (as real estate values increase (e.g., $1 million homes in coastal areas), the higher the potential capital cost, even for a low-frequency event); Changing climate and frequency (the risk is no longer stable: in Germany, Canada, and France, areas that were previously “marginal” are becoming high-risk due to climate change).

Les données actuarielles des assureurs, un trésor pour la connaissance client ?

Dans le supplément des Échos, publication d’une entrevue datant du printemps dernier.

Quels sont les typologies de données utilisées par les assureurs ?

Les actuaires, ces spécialistes des données et des statistiques chez les assureurs, utilisent les données clients internes, à savoir celles que les assurés leur fournissent, notamment au moment de la souscription de contrat, sur leur véhicule, leur lieu d’habitation, etc. Ils peuvent aussi “piocher” ailleurs, dans la cote argus par exemple, pour estimer le montant maximal d’un sinistre ; dans l’historique des inondations ; les données de cambriolage ; les données INSEE ou encore la météo. À partir de toutes ces données, les actuaires vont créer des modèles afin de prédire des scores d’accidents, de fraudes, de résiliation…

À quoi sert l’analyse des données actuarielles?

Ces données permettent surtout de segmenter le portefeuille, de trouver les bonnes variables tarifaires, pour créer des classes tarifaires en assurance auto ou habitation par exemple. Elles peuvent aussi être utilisées pour trouver le juste prix pour couvrir de nouveaux risques. Elles permettent enfin de répondre aux nouvelles demandes des assurés. Avant, avec l’assurance auto par exemple, lorsque votre voiture tombait en panne, on vous remboursait les frais et ça suffisait. Maintenant, les clients veulent être hébergés, disposer d’une voiture de remplacement… C’est à l’actuaire d’évaluer le coût de ces nouveaux services pour les inclure dans les différentes primes proposées par l’assureur.

« Il y a d’un côté l’approche marketing, qui va chercher à individualiser pour proposer des offres personnalisées ; de l’autre celle de l’actuaire, qui va chercher à trouver des catégories pertinentes, en mutualisant. »

a suivre…