As more P&C insurers adopt predictive models in their rating plans, many rely on tools like lift charts and Gini coefficients to demonstrate performance. While these metrics are useful, they only scratch the surface. A strong model in isolation isn’t enough—it needs to align with business objectives, regulatory expectations, and pricing fairness. Lift charts, for […]

In today’s regulatory environment, a strong model isn’t enough. Insurers are increasingly expected to demonstrate not only that their rating plans are predictive, but that they are understandable, intuitive, and fair. Transparency has become a core expectation—not just a courtesy, but a requirement. This shift is partly driven by growing scrutiny from state regulators, who […]

For both insurers and regulators, the concept of rate adequacy sits at the heart of responsible insurance pricing. But while it's often mentioned in filings and regulatory discussions, it’s not always well understood outside the actuarial sphere. Put simply, rate adequacy means that premiums are sufficient—neither too high nor too low—to cover expected losses and […]

In a field where models, methods, and credentials can start to look the same, what truly sets an actuarial consulting firm apart is how it approaches the work—and the people behind it. At Taylor & Mulder, we don’t see ourselves as just number-crunchers or model builders. We see ourselves as long-term partners in helping our […]

For small and mid-sized insurers, predictive modeling can feel out of reach—especially when larger firms treat it as a one-size-fits-all product. At Taylor & Mulder, we believe effective actuarial support isn’t about dropping in a model and walking away. It’s about building a lasting partnership grounded in regulatory insight, strategic alignment, and clear communication. “There’s […]

As a consulting firm specializing in rate filing reviews for state insurance departments and regulators, we at Taylor & Mulder recognize the challenges P&C insurers face when transitioning from traditional rating models to generalized linear models (GLMs). While GLMs offer improved predictive accuracy and a more refined risk assessment, they also introduce concerns regarding rate […]