In today's data-driven world, analytical models are instrumental in decision-making processes across industries—from healthcare and finance to retail and governance. While these models can bring precision and efficiency, they are not immune to bias. If left unchecked, ethical biases in analytical models can reinforce discrimination, reduce trust, and lead to flawed decisions. Hence, ethical bias checks are not just best practices—they are essential components of responsible analytics.