What is Bias?
Bias in AI systems occurs when models produce systematically skewed outputs that unfairly favour or disadvantage certain groups or perspectives. In financial services, bias can manifest in various ways, such as inconsistent treatment of client demographics, skewed risk assessments or unbalanced recommendations. Bias can arise from training data, model design or deployment context. Firms must test for bias, implement mitigation strategies and monitor AI systems to ensure fair treatment and regulatory compliance, particularly in relation to Consumer Duty and equality obligations.
Bias in financial services
In financial services, biased outcomes can mean customers with similar needs are treated differently, which conflicts with the requirement to treat customers fairly and to deliver good outcomes under Consumer Duty. Firms therefore test AI systems for bias before deployment and continue to monitor outcomes across customer groups once they are live.