Personalized Insurance Premiums Cheaper Thanks to AI? Here’s Why It’s a Slippery Slope

This article was initially written in French.

Insurance is based on a principle of solidarity that is undermined by the algorithms tasked with creating our profiles. As algorithms become more precise, the bill becomes more personalized. Various “at risk” profiles may thus find themselves excluded from insurance schemes, as the costs are so high. Personalization has an obvious legitimacy. But it must be reconciled with equitable access to insurance.

It must first be understood that insurance is marked by a fundamental paradox. On the one hand, its very principles assume a collective mechanism in which everyone contributes according to their capacity and benefits from solidarity in the event of a loss. On the other hand, technological advances, ever-larger datasets, and increasingly precise actuarial methods push toward ever greater individualization of premiums.

It is nothing less than reconciling actuarial refinement with the values of redistribution and solidarity on which the profession of insurer was founded.

To this tension is added an increasingly demanding legal framework, which prohibits any form of discrimination based on sensitive data, sometimes correlated with risk factors that are nevertheless relevant.

Pricing segmentation

Insurance companies have long used classification as the pillar of their economic model: age, sex, profession, geographic area, claims history…

In 1662, English statistician John Graunt published the Bills of Mortality, a first statistical analysis of London’s death registers. In 1693, English astronomer Edmund Halley developed the first quantified mortality table, allowing calculation of life expectancy at each age. These works laid the foundations for differentiated pricing by age and sex, which long remained the two main criteria of segmentation in life-death insurance.

At the same time, after the Great Fire of London in 1666, the first fire insurance contracts appeared: companies collected data on the type of construction materials and urban density. In the 18th–19th centuries, premiums were segmented according to the proximity of neighboring buildings and the presence of fire services, giving rise to the first “high-risk zones” and “low-risk zones.”

With the rise of the automobile in the 1910s–1920s, American insurers began systematically recording the number of claims, and the age and sex of drivers. As early as the 1920s, several pricing “classes” were distinguished: young drivers, women drivers, experienced drivers, making it possible to set variable premiums depending on the profile.

Today, actuaries have sophisticated algorithms, machine learning tools, and a flood of data: onboard telematics, connected objects, geolocation, driving or lifestyle behavior… For the insurer, refining segmentation makes it possible to charge each policyholder “their true risk level,” reducing the cross-subsidization effect from good risks to bad ones, while improving overall profitability.

But overly fine pricing reduces pooling; it can make insurance very expensive, even inaccessible for certain high-risk segments. Hence today, actuaries seek a subtle balance, aiming to capture the right information to differentiate profiles, while preserving the viability of the insured community.

Policyholders and the illusion of winning personalization

In Europe, the legislative proposal FIDA (Financial Data Access Framework) would open regulated access for insurers to individuals’ financial data. Its purpose is to refine understanding of spending and repayment behaviors. In this context, the promise of ultra-personalized pricing arouses both hopes of lower premiums and fears of excessive profiling and significant exclusions.

Faced with this new influx of data, many clients perceive personalization as a win-win approach: if I manage my budget better, I will benefit from a discount; if my saving and repayment habits are judged virtuous, my health premium will decrease; if my financial profile improves, my home insurance will become lighter.

This “pay-as-you-live” or “pay-how-you-drive” logic appeals: individuals believe themselves masters of their insurance cost through their lifestyle choices.

Yet several points deserve to be highlighted.

The principle of pooling is not neutralized: those who cannot adopt the most virtuous behaviors remain dependent on the solidarity of others. Indeed, even if higher-risk individuals pay more individually, those who are less at risk nevertheless continue to bear part of the costs thanks to the principle of pooling.

The asymmetry of information is reinforced, as the insurer knows statistics better than the client. The offer of personalization is often based on correlations, sometimes tenuous, whose scope the client does not understand.

Very fine personalization can force the most at-risk to over-insure, or on the contrary to give up insurance, weakening the pool.

Thus, even strengthened by access to financial data, “personalization” is not necessarily synonymous with “empowerment” for the consumer.

The legal framework: when the fight against discrimination is required

The development of big data in insurance raises important ethical and legal questions: how far can sensitive variables be exploited to predict risk?

In France and in the European Union, legislation explicitly prohibits discrimination based on protected criteria: ethnic origin, gender, sexual orientation, disability, religious beliefs, etc. The Solvency II Directive (EU) requires insurers to use “transparent” and non-discriminatory risk models.

Unlike the European Union—which bans differentiated pricing based on protected criteria (gender, origin, disability)—the Quebec model offers a more permissive framework. While the Charter of Human Rights and Freedoms of Quebec also prohibits discrimination, it provides exemptions specific to insurers: they can, when a factor is statistically relevant, base pricing on age, sex, or marital status.

This usage, authorized solely on the basis of a correlation, raises questions.

Ethics and social responsibility of insurers

Beyond mere legal compliance, insurers are increasingly judged on their ethical practices and social responsibility by consumer associations and the media, which relay incidents of algorithmic discrimination and exert reputational pressure.

In recent years, insurers must therefore ask themselves collectively how to guarantee equitable access to their products for vulnerable populations, without sacrificing the financial viability of their portfolios. Some innovative models propose “solidarity” formulas or capped premiums to avoid exclusion.

Insurers are being required to show more and more transparency. They must clearly explain pricing criteria, make calculation keys accessible to avoid a feeling of arbitrariness. Finally, they must integrate data protection and privacy from the design stage of offers (“privacy by design”), in order to preserve trust.

Insurers that manage to reconcile personalization, fairness and inclusion will become reference players for clients concerned with ethics.

Reconciling solidarity and data: a crucial challenge

The challenge, as we see, is considerable.

It is nothing less than reconciling actuarial precision with the values of redistribution and solidarity that founded the insurance profession.

It is in resolving this tension that the future of insurance will be decided: neither pure price discrimination nor simple illusory personalization, but rather a balance allowing each to contribute according to their risk and to benefit in fair measure from the pooling of life’s uncertainties.

In the end, who will bear the cost of insurance?

This article was written with Laurence Barry, co-holder of the PARI Chair (Research Program for the Understanding of Risks and Uncertainties), initially in French.

Storms that repeat, premiums that soar, insurers pulling out: in the era of climate change, one question arises: who will ultimately foot the bill?

From the workers’ mutuals of the 19th century, created to cushion the blows of industrial development, to the shareholder logics of today’s multinationals, insurance has always reflected the great risks of its era.

Now, under the pressure of climatic events with unprecedented frequency and severity, the sector faces a new equation: how to remain solvent and socially legitimate when claims (amounts paid out by an insurance company for losses) grow faster than premiums (collected)? Between soaring rates, exclusions of coverage, and the threat of entire territories becoming uninsurable, how must insurance solidarity reinvent itself?

Each for all, and all for each

Since 1990, insured losses linked to natural disasters have grown by 5% to 7% per year – 137 billion U.S. dollars in 2024, and a trend toward 145 billion in 2025. Lucian Coman/Shutterstock

Before becoming a financial industry worth billions of euros, insurance began as a simple common pot: members contributed, the victims drew from it, and the surplus (if any) returned to the policyholders. From solidarity and mutual aid organizations created under the Hanse (the Hanseatic League, network of merchant cities in Northern Europe between the 13th and 17th centuries) to medieval guilds, associations of people practicing the same trade or activity, the logic was already that of a risk-pooling, a zero-sum sharing of risk. Each pays for all, and all for each.

In the guilds of the Middle Ages, in Europe, each master craftsman paid an annual fee that financed the rebuilding of a workshop destroyed by fire or support for the widow in case of death. For economic historian Patrick Wallis (eprints.lse.ac.uk), this was the first structured relief fund. The Danish charters of 1256, which imposed compulsory “fire aid” (brandstød) after a loss, provide a perfect example, as shown by social policy researcher Bernard Harris.

The principle runs through the centuries. In the 19th century, mutual aid societies introduced rebates when claims were milder than expected. Even today, nearly one in two policyholders in fire, accident, and miscellaneous risks (P&C) belongs to a mutual where he or she is a statutory co-owner.

The financial equation remains fragile: when the climate transforms chance into near-certainty, the premium is no longer a simple “cake-sharing” but an ever-larger advance on future expenses. The Swiss Re group has calculated (swissre.com) that, since 1990, insured losses linked to natural disasters have grown by 5% to 7% per year – 137 billion U.S. dollars in 2024, with a trend toward 145 billion U.S. dollars in 2025 (respectively 118 billion and 125 billion euros).

The mutualist model (erudit.org), founded on the relative rarity of claims and geographic diversification, is forced to reinvent its solidarity if frequency doubles and severity explodes… at the risk of tipping toward segmentation as fine as that of shareholder-driven insurers.

Solidarity pricing and shareholder optimization

Starting in the 1990s, financialization injected a new imperative: the premium must cover claims, finance marketing, remunerate equity, and occasionally serve as an adjustment variable for quarterly targets. Pricing optimization, popularized under the term price optimization, dissects thousands of behavioral variables (number of clicks before signing, banking inertia, connection times) in order to estimate the individual reservation price, that is the minimum price a seller is willing to accept, or a buyer is willing to pay, in a transaction.

In other words, it is no longer only a matter of estimating the actuarially most “fair” premium (the actuary being the expert in risk management), in the sense given by Kenneth Arrow in 1963 (aeaweb.org), but also the highest premium the policyholder is willing to pay. The fair premium being the expected average cost of claims, the amount the insurer expects to pay next year for similar risks.

The Institute of Australian Actuaries denounces, in its report The Price of Loyalty actuaries.asn.au), a systematic penalization of loyal clients, likened to a tax on trust. In the United Kingdom, the Financial Conduct Authority (FCA, ca.org.uk) struck hard. Since January 1, 2022, renewal pricing must be identical to that for a new client at equal risk; the authority estimates the savings for households at £4.2 billion over ten years.

This regulatory battle goes well beyond price. By relegating the logic of pooling to the background, behavioral optimization strengthens indirect socio-economic indicators—such as age, the digital divide, or residential stability—which end up weighing more than pure technical risk in determining the premium.

Now the insurer has access to private data lakes (raw data), where the policyholder is unaware of what makes their premium more expensive. By nature, contracts remain resistant to any simplified comparison. One shows a €2,000 deductible, another a lower compensation ceiling or exclusions hidden in tiny clauses, so that it takes an almost legal review to really align the offers, as a European Commission report pointed out (commission.europa.eu).

One file out of two refused

The rise of extreme events brutally illustrates these drifts. In Australia, three climatic phenomena in the first half of 2025, including Cyclone Alfred, generated 1.8 billion Australian dollars (AUD), or 1 billion euros, in compensation claims. The Insurance Council warns that home insurance premiums will see double-digit increases, and some contracts could reach 30,000 AUD per year (or €16,600 per year) in the most exposed areas (abc.net.au).

In the United States, California is seeing cancellations and refusals of coverage. A report cited by the Los Angeles Times shows that three major insurers declined nearly one file out of two in 2023 (latimes.com). A class action accuses 25 insurance companies of collusion with the aim of pushing victims toward the FAIR Plan, a pool of last-resort insurers with reduced coverage (cbsnews.com).


Toward systemic “uninsurability”

The phenomenon is not marginal. Insurers are reducing their exposure. U.S. insurers State Farm and Allstate stopped issuing new policies in California as early as 2023 (reuters.com). In Florida, because it intervenes when no private insurer accepts to cover a home at a reasonable price, the public last-resort insurer Citizens saw its portfolio grow to about 1.4 million policies at the peak of the crisis, then fall back below one million at the end of 2024 thanks to transfers (takeouts) to private players—a real improvement, but one that still reveals a fragile market (insurancejournal.com).

At the global level, Swiss Re counts 181 billion U.S. dollars of 2024 losses left to victims or states, or 57% of the total (swissre.com).  Faced with these growing protection gaps, insurers are reducing their exposure. This contraction of supply rebounds onto real estate finance: economist Bill Green reminds, in a letter to the Financial Times, that the slightest insurance default leads, in a few weeks, to the cancellation of mortgages supposed to secure the American middle class (ft.com).

When insurers withdraw or when the premium becomes unaffordable, property values collapse, and with them, the stability of an entire segment of the local banking system.

Refounding the social contract of risk

Nevertheless, avenues are emerging. The Center for American Progress proposes the creation of resilience funds co-financed by premiums and by the federal state, in order to finance levees, reinforced roofs, and relocations in very high-risk areas (americanprogress.org).

In Europe, France maintains a CatNat scheme based on a uniform mandatory surcharge – 20% in 2025 – for a risk reinsured by the Caisse centrale de réassurance (CCR). This mechanism guarantees unlimited compensation while pooling disasters across the entire national territory. Combined with incentive pricing (deductibles adjusted according to prevention measures), these mechanisms can preserve insurability without exploding individual premiums.

What remains is to address the upstream side: limiting exposure by freezing building permits in unbuildable areas, conditioning bank financing on climate compatibility, and sustaining, at the national level, a progressive climate prevention surtax that would finance structural adaptations while smoothing rate shocks (ecologie.gouv.fr, strategie-plan.gouv.fr)

At this price, insurance would once again become a common good: neither a pure financial product nor a simple common pot, but an essential infrastructure where society, and no longer only the insurer, consciously chooses the share of the climate bill it accepts to bear.