hile the mathematical foundations of risk are universal, regional regulatory philosophy and market maturity have dramatic impacts on actuarial pricing across the globe. A session at the CAS’ recent Ratemaking, Product, and Modeling seminar explored how these global differences manifest in unique actuarial skillsets, as explained by Akur8 senior actuarial data scientist Kamela Taleb and Akur8 head of product Mattia Casotto.

Taleb opened the session by addressing the confusion that can arise when insurance professionals transition between international markets. Global variations of key industry terms, for instance, often reflect distinct underlying approaches to pricing, such as:

• Technical Premium = Premium
• Pure Premium = Loss Cost
• Tariff = Rating Plan

To illustrate these discrepancies, Taleb shared an experiment involving a 30-year-old driver with a clean driving record seeking an auto insurance quote in Canada, Japan, the U.K., and the U.S. Despite having a consistent profile, the subject received a wide range of quotes, driven by local market constraints and differing views of risk. Taleb categorized these differences into three archetypes:

• Heavily Regulated Markets: Defined by consumer protection rules, in which every pricing decision requires extensive justification.
• Information-Friendly Markets: Defined by competitive positioning and rapid iteration.
• Emerging Markets: Defined by data challenges and opportunities to build modern systems without the burden of legacy infrastructure.

In heavily regulated markets like the U.S. (admitted lines), Canada, and Japan, carriers face prohibited factors such as credit, gender, and age, as well as political pressure that can create gaps between pricing indications and actual charged rates. Conversely, in innovation-friendly markets like the U.K. and Australia, competition forces a high degree of sophistication. In these regions, carriers’ selection is risk adverse if they fail to update their models quickly enough. For markets such as Indonesia and Brazil, the limited data available shows that the presence of legacy systems can slow the adoption of more sophisticated underwriting and pricing techniques.

Casotto shifted the focus toward the tools and timelines behind the actuarial process. In the United States, organizations such as the Insurance Services Office (ISO) and the National Council on Compensation Insurance (NCCI) provide “prepackaged” industry rates based on the shared loss costs, allowing carriers to set prices more quickly. However, membership in these organizations is not commonly disclosed to the public.

Several international parallels to this system exist, including the German Insurance Association (GDV) and the General Insurance Rating Organization of Japan (GIROJ). In Japan, companies typically must remain within a 12.5% standard deviation from the GIROJ’s rates, creating structural constraints in which an entire portfolio must comply with a specific “lookup table.”

Such constraints influence the “speed to market” for rate changes in unique ways. In innovation-friendly markets like the U.K., filings are not necessary, which helps drive a rate change cycle of between two and four weeks. That same cycle may require six to nine months in regulated markets like the U.S., which operates under filing and approval regulations such as California’s prior approval pricing process. These environments generate unique actuarial value pressures. Whereas regulated markets reward actuaries for ensuring their decisions are explainable to regulators, competitive markets reward actuaries for understanding customer behavior, competitor repricing, and using tools like price aggregators. In emerging markets, insufficient data access means actuaries are rewarded for simplifying structures for legacy-free environments.

Taleb contextualized these values in relation to price optimization, identifying three forms:

1. Unconstrained: the key driver is the rate indication.
2. Constrained: limiting individual impacts to a specific range, sometimes to retention expectations.
3. Ratebook: applying rate adjustments across entire segments of the portfolio.

Taleb also analyzed the optimization practice “price walking,” wherein insurers gradually charge loyal customers higher premiums than they would quote to new customers with the same risk profiles. One U.K. study found cases where preexisting customers were paying 40% over the technical price while new customers were being offered a 20% discount.

In response, the U.K.’s Financial Conduct Authority implemented rules that require renewal prices to be equivalent to new business rates, meaning only new information such as claims history or risky driving behaviors can justify differences. The change forced a structural shift in the industry, as once-separate “New Business” and “Renewal” teams now work toward unified strategic decisions for the entire portfolio. Bans on loyalty-based price walking also rippled across Europe, with bans already in effect in Ireland, and France and Italy currently conducting research into the practice.

A similar regulatory evolution has unfolded for pricing optimization in the U.S., Casotto added. States in the U.S. began limiting certain optimization techniques as early as March 2014, leading to the NAIC’s adoption of the Casualty Actuarial and Statistical Task Force’s 2015 white paper on price optimization. However, for advanced modeling techniques, regulation in the U.S. is adapting to the new technologies. More than 20 U.S. states adopted the NAIC’s Model AI Bulletin within 15 months of its issuance in December 2023 and currently 88% of auto insurers use or plan to use AI and machine learning. Additionally, CAS recently modified its Exam 8 syllabus to include advanced predictive modeling, AI, and machine learning concepts.

Casotto and Taleb expressed the belief that global pricing processes will eventually converge, highlighting movement within the European and U.S. markets towards a middle ground on the ratemaking process. Their predictions include:

• Transparency over Complexity: Building increasingly complex models is not viable in the long term. Instead, the focus will shift toward transparent and efficient ratemaking practices.
• Data-Driven Fairness: True fairness will eventually be data-driven, with market players proactively removing historical biases rather than regulation alone.
• Standardization of Constraints: The use of “constrained optimization” will remain standard practice to ensure portfolio stability and customer retention.

They emphasized that technology and regulation together will lead to a more synchronized global pricing standard. Whether operating in a heavily regulated archetype or an innovation-driven one, actuaries must remain agile. Navigating the intersection of analytics, technology, and regulatory philosophy is essential for actuaries to continue making insurance and financial products more affordable, available, and sustainable.