Ms. Franchezca Denise Espiritu and Ms. Catreena Anne Teng from University of Santo Tomas, College of Science, Department of Mathematics and Physics presented their thesis: "Analysis of the Factors Affecting Car Insurance Claims in the Philippines" to PIRA joint meeting of PR, Publicity & Marketing, Education and Motor Committees.
SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
Summary of Findings
From the sample space of 787 actual claims data of private and commercial vehicles, the sixth and last model using stepwise backward elimination regression showed that the policy type, accident place, driver’s weight, gender and age as well as the third and eighth restriction from the driver’s license are significant factors to gross amount of claims with 95% confidence interval. The factors that was not found to be significant were premium amount, years of driving experience, the driver’s height as well as their condition to wearing eyeglasses and the fourth driving restriction from the driver’s license. For the separate regression performed on motorcycles having a sample space of 16 actual claims data, only the driver’s weight and age are found to be significant.
Analysis on the actual claims data limited to the experience of a local insurance company which caters to the entire Philippines shows that policy type, accident place, driver’s weight, gender and age as well as the third and eighth restriction from the driver’s license are significant factors to gross amount of claims of both private and commercial vehicles. The driver’s weight and age were also found to be significant factors to the gross amount of claims of motorcycles. The results were limited to the information of the driver’s at the event of the accident and none for the assured thus failing to present a decent model for the occurrence of claims. However, results from the regressions shows consistency with other related studies specifically age being a significant factor costing the insurance company Php 400 less for every additional year in age for private and commercial vehicles and Php 219 less for every additional year in age for motorcycles on average.
Given the results of this study, the researchers were not able to properly model the frequency of claims due to the lack of data. Having the same information of the driver’s for the policyholders would be ideal in order to create a better model and to further come up with a suggested premium pricing. The researchers recommend that the gathering of data from new policies, narrowed specifically on the significant factors found, particularly their gender, their age, their weight, their policy type, their restrictions from driving a particular kind of vehicle found in their driver’s license and knowing whether or not they reside within Metro Manila would be helpful in arriving with the correct model.