Disparate Treatment
Intentional discrimination in which similarly situated consumers are treated differently because of a protected characteristic.
Disparate treatment is intentional discrimination. It occurs when an insurer treats similarly situated consumers differently specifically because of a protected characteristic such as race, gender, or national origin. An example would be a rule that explicitly charges higher premiums to applicants of one race.
This is different from disparate impact, which does not require intent. A model can produce disparate impact even if no one intended to discriminate, when a neutral variable acts as a proxy for a protected class. Most AI fairness testing in insurance focuses on disparate impact because the discrimination is embedded in patterns rather than stated rules.
Disparate treatment claims are still relevant for AI governance, because a model that uses or appears to use a protected characteristic directly can trigger both legal and reputational risk. See our glossary entries on disparate impact and unfair discrimination.