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Recent headlines in Australia have brought attention to insurance pricing practices. A 14% annual increase in premiums, highlighted by the Australian Council of Trade Unions (ACTU) , as the sharpest rise in the Consumer Price Index, has prompted public concern about the affordability of insurance during a period of economic pressure.
In parallel, the private health insurance sector has come under scrutiny for practices such as “ product phoenixing ”, where policies are closed and relaunched under new names, often with higher premiums.
These examples have intensified wider concerns about fairness and transparency in insurance pricing. This includes growing attention to strategies such as the loyalty penalty and price optimisation, where premiums may vary not only by risk but also by customer behaviour, such as the likelihood of switching providers.
In the context of insurance, an industry built on risk pooling and financial protection, behaviour-based pricing practices raise important questions about their impact on consumer outcomes, particularly on trust, transparency and fairness.
Ongoing debate continues over whether and to what extent, these pricing practices align with the traditional expectations and responsibilities of insurers. In this column, we take a closer look at this evolving issue.
In economics, charging different prices for identical products is known as price discrimination, which is a neutral term. When applied to insurance, this concept requires a specific clarification: “identical products” is less straightforward since insured risks differ.
For instance, two auto insurance policies that offer the same coverage and benefits may be priced differently due to differences in expected losses, based on factors like the driver's history, vehicle type, or location. This approach, known as “risk-based pricing”, is a standard and widely accepted practice in insurance, consistent with the principle of actuarial fairness.
However, insurers may also offer different prices for customers with identical risk profiles. This could be based on behavioural factors, such as the likelihood of switching providers or renewing a policy. This form of pricing, often referred to as “non-risk-based price discrimination” or “price optimisation”, reflects differences not in risk, but in consumer behaviour or perceived willingness to pay.
Price discrimination is typically classified into three degrees:
In the insurance market, similar patterns of price discrimination exist. In some jurisdictions, insurers commonly offer discounted rates to attract new customers, while long-standing policyholders may face higher premiums despite having the same risk profile. Research has documented that these loyalty penalties are often driven by price optimisation techniques.
Price discrimination is a widely accepted strategy in many markets, where it can enhance efficiency by aligning prices with consumers’ willingness to pay. In industries like software or airlines, this can expand access and match pricing to demand.
However, insurance operates under a distinct set of conditions that make the implications of price discrimination more complex, see, for example, Thomas (2012). Below, I summarise several features that differentiate the insurance market from other industries and shape the economic and ethical considerations surrounding pricing practices.
Regulatory responses to price discrimination in insurance vary across jurisdictions.
In the United States, concerns about fairness in personal insurance date back to the 19th century, when industry associations sought to limit practices that allowed wealthier or more influential clients to secure lower premiums not justified by their level of risk. At the time, the focus was on preventing what was termed “unfairly discriminatory rates”, instances where pricing diverged from actuarial principles.
More recently, several U.S. states have taken steps to restrict behaviour-based pricing practices.
Since 2015, approximately 20 states have introduced bans on the use of price optimisation and demand modelling in personal insurance lines. These measures reflect growing regulatory attention to the potential for such practices to disadvantage consumers. Anecdotal reports from industry professionals suggest that price optimisation is increasingly viewed with caution in some North American markets.
In 2022, the UK Financial Conduct Authority banned “price walking” — where renewing customers are charged more than new ones for equivalent coverage — citing concerns that the practice harmed consumers through a lack of pricing transparency, penalised loyalty and undermined trust and fairness in the insurance market.
However, the FCA did not prohibit all forms of optimisation, acknowledging that some uses — such as improving price efficiency or stimulating competition — may benefit consumers under appropriate safeguards.
In the European Union, the European Insurance and Occupational Pensions Authority (EIOPA) issued a recommendation in March 2023 advocating for a similar ban on price walking in insurance renewals when not justified by changes in risk.
In Australia, regulatory action has been more limited to date. However, rising consumer concern, public commentary from groups such as the Australian Council of Trade Unions (ACTU), and an ongoing federal investigation into health insurance pricing indicate increased scrutiny of pricing fairness in the insurance sector.
The use of price optimisation in insurance, where premiums are influenced not only by risk but also by non-risk-based consumer behaviour, has raised concerns about transparency, fairness, and consumer trust. However, some industry observers caution that the issue is complex. Even in the absence of formal price optimisation, subjectivity can enter pricing decisions.
For example, risk-based pricing and expense loadings often involve judgment calls that may implicitly reflect underwriters’ views on customer behaviour, retention likelihood, or risk tolerance. Insurers have long used simpler pricing strategies — such as targeting younger customers through discounts or digital channels — to improve competitiveness, strategies that might inadvertently fall within the scope of strict price optimisation bans. These nuances highlight the importance of ongoing discussion and critical examination of the principles that should underpin fair and responsible insurance pricing.
Miller and Moulder (2024) highlight several practical limitations of price optimisation in insurance, including model uncertainty, misestimation of customer elasticity, and declining performance over time due to shifts in the customer base. Additionally, as shown in Huang and Shimao (2025), the extent and impact of price optimisation are influenced by market competitiveness, with regulatory effects becoming less pronounced in more competitive environments.
As the industry continues to evolve, regular evaluation of pricing practices is necessary to ensure alignment with principles of transparency, consumer protection, and the broader social function of insurance. Defining appropriate boundaries for the use of behaviour-based pricing is likely to require coordinated action by both regulators and industry stakeholders.
Thomas, G. R. (2012). Non-risk price discrimination in insurance: market outcomes and public policy. The Geneva Papers on Risk and Insurance-Issues and Practice, 37, 27-46. Available at https://www.jstor.org/stable/41953166
Huang, F., & Shimao, H. (2025). Welfare Implications of Fair and Accountable Insurance Pricing. UNSW Business School Research Paper Forthcoming. Available at SSRN: https://ssrn.com/abstract=4225159
Miller, H., & Moulder, T. (2024). Optimal illusion – A look at the practical limitations of price optimisation. Paper presented at the Actuaries Institute 2024 All-Actuaries Summit, Sydney, Australia. Available at: https://actuaries.logicaldoc.cloud/download-ticket?ticketId=5b86fb11-f32b-4826-bdf7-c0774d66a961