As regulatory changes take place in the Philippine health insurance industry, this study focused on addressing the existing pricing concerns by introducing the loss model driven Frequency-Severity Method which is widely used in other insurance markets around the world. The study aimed to demonstrate the application of risk management and loss modeling on the estimation of health insurance product prices and the advantages and disadvantages of the Frequency-Severity Method over the traditional Loss-Cost approach in which only claims severity is estimated. The results of the study showed that by classifying data according to its similar characteristics, the risk of wrongly specifying a best-fit probability distribution is minimized, percentiles can be determined through Maximum Likelihood Estimation hence avoiding the use of the central limit theorem and the resulting segmented pricing equation is more effective in expressing in numbers the primary pricing drivers. Claims data were right-skewed heavy-tailed and best-fitted into the Weibull distribution as determined by Anderson Darling and p-value estimates. The modeled premiums were approximately twenty-percent higher than the empirical premiums, however, showed a fifty-percent increase in underwriting profit on the onset. The twenty-percent gap was also addressed through the adjustment of the frequency component, and by this adjustment proved the versatility of the pricing model
