Adapt to Market Changes Faster: Smarter Pricing for MGAs with AI

Insurance pricing models gradually drift away from reality as market conditions evolve. This session explores practical approaches to monitoring model performance, updating models efficiently, and deploying changes seamlessly into production.

Over the past years, machine learning and AI tools have become increasingly embedded in actuarial workflows. This shift is helping pricing teams detect model drift more quickly, automate many routine manual tasks and is breaking down traditional bottlenecks in the overall pricing process.

The result is pricing teams that can respond more rapidly to changing market conditions, while focusing more of their time on understanding the portfolio and undertaking that require true actuarial judgment.

• Describe how pricing model drift occurs as market conditions evolve and why it presents a challenge for insurers and MGAs.
• Outline practical methods used to monitor pricing model performance and identify signs of model deterioration over time.
• Explain how machine learning and AI tools are being applied within actuarial workflows to improve drift detection and reduce manual operational tasks.
• Summarise how combining AI capabilities with actuarial judgment enables pricing teams to respond more effectively to changing market conditions.