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	<title>Definition:Unfairly discriminatory rate - Revision history</title>
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	<updated>2026-04-29T20:54:23Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
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		<id>https://www.insurerbrain.com/w/index.php?title=Definition:Unfairly_discriminatory_rate&amp;diff=12063&amp;oldid=prev</id>
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		<summary type="html">&lt;p&gt;Bot: Creating new article from JSON&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;⚖️ &amp;#039;&amp;#039;&amp;#039;Unfairly discriminatory rate&amp;#039;&amp;#039;&amp;#039; is a pricing classification used by state [[Definition:Insurance regulator | insurance regulators]] to describe a [[Definition:Premium | premium]] rate that treats similarly situated [[Definition:Policyholder | policyholders]] differently without actuarial justification, or that relies on factors prohibited by law. The concept sits at the intersection of [[Definition:Rate regulation | rate regulation]] and consumer protection—distinguishing legitimate [[Definition:Risk classification | risk-based differentiation]] (which is the foundation of [[Definition:Underwriting | underwriting]]) from distinctions that violate statutory standards of fairness. A rate can be adequate and not excessive yet still be deemed unfairly discriminatory if it charges different prices to people who present substantially the same expected [[Definition:Loss | loss]].&lt;br /&gt;
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🔍 State insurance codes generally require that rates not be inadequate, excessive, or unfairly discriminatory—a tripartite standard that [[Definition:Insurance carrier | carriers]] must satisfy during [[Definition:Rate filing | rate filings]]. Regulators evaluate whether the rating variables an insurer uses—such as credit score, territory, age, or gender—bear a reasonable relationship to expected losses and expenses. If a variable produces price differences that cannot be supported by [[Definition:Actuarial analysis | actuarial analysis]] or that correlate with protected classes in ways the state prohibits, the rate may be rejected or the insurer ordered to revise it. The growing use of [[Definition:Predictive model | predictive models]] and [[Definition:Artificial intelligence (AI) | AI]] in pricing has intensified regulatory scrutiny, because complex algorithms can embed proxy discrimination—where ostensibly neutral variables effectively replicate the effect of prohibited factors like race or ethnicity.&lt;br /&gt;
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🛡️ For insurers, the stakes of getting this wrong are significant. Deploying a rate deemed unfairly discriminatory can trigger regulatory enforcement actions, mandatory refunds, [[Definition:Market conduct examination | market conduct examinations]], and reputational damage. Beyond compliance, the concept shapes strategic decisions about which data sources to incorporate into [[Definition:Rating algorithm | rating algorithms]] and how transparent an insurer&amp;#039;s pricing methodology needs to be. [[Definition:Insurtech | Insurtech]] companies that build novel pricing models around alternative data—telematics, social media behavior, IoT sensor readings—must navigate these fairness requirements carefully, often conducting bias audits and disparate impact analyses before filing rates. As regulators develop more sophisticated tools for reviewing algorithmic pricing, the definition of what constitutes unfair discrimination continues to evolve alongside the technology.&lt;br /&gt;
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&amp;#039;&amp;#039;&amp;#039;Related concepts:&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
{{Div col|colwidth=20em}}&lt;br /&gt;
* [[Definition:Rate regulation]]&lt;br /&gt;
* [[Definition:Risk classification]]&lt;br /&gt;
* [[Definition:Rate filing]]&lt;br /&gt;
* [[Definition:Predictive model]]&lt;br /&gt;
* [[Definition:Market conduct examination]]&lt;br /&gt;
* [[Definition:Actuarial analysis]]&lt;br /&gt;
{{Div col end}}&lt;/div&gt;</summary>
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