I utilize a combination of statistical analysis, actuarial science, and machine learning techniques to develop pricing models. This includes regression analysis, loss ratio analysis, and predictive modeling to assess risk and determine appropriate premiums. I also incorporate market trends and competitor analysis to ensure the pricing is competitive yet profitable.

I stay updated with the latest regulatory changes and guidelines by regularly consulting legal and compliance teams. I incorporate these requirements into the pricing models and conduct periodic audits to ensure adherence. Additionally, I maintain detailed documentation to demonstrate compliance during regulatory reviews.

In a previous role, I noticed a significant shift in market conditions due to increased competition. I conducted a thorough analysis of our pricing structure and identified areas where adjustments were needed. By re-evaluating risk factors and competitor pricing, I implemented changes that maintained profitability while staying competitive.

Balancing profitability and customer retention involves a deep understanding of customer behavior and risk assessment. I use data analytics to identify customer segments that are more price-sensitive and adjust pricing strategies accordingly. Offering value-added services and loyalty programs also helps in retaining customers without compromising profitability.

I am proficient in using tools like Excel, R, Python, and SAS for data analysis and modeling. Additionally, I have experience with actuarial software such as Emblem and Radar for pricing and risk assessment. These tools enable me to perform complex calculations and simulations efficiently, ensuring accurate and reliable pricing models.