Comparison of BDCL and Bootstrapping Bornhuetter Ferguson Methods in Claim Reserve Estimation (Case Study at Actuarial Consulting Firm X)

Risk is an inherent uncertainty in human life. In the insurance industry, this requires companies to prepare claim reserves to cover potential future losses. Claim reserve estimation is generally carried out using a deterministic approach, but this method does not explicitly account for uncertainty. Therefore, this study applies development methods such as the semi-stochastic Bornhuetter-Double Chain Ladder (BDCL) method and the stochastic Bootstrapping Bornhuetter Ferguson method. The Bornhuetter Ferguson method is widely used due to its reliability, but the combination with bootstrapping techniques remains limited in the literature. Therefore, this study aims to compare the Bootstrapping Bornhuetter Ferguson method with the more commonly used BDCL method. The BDCL method allows separate calculation of IBNR and RBNS claim reserves, while Bootstrapping Bornhuetter Ferguson integrates bootstrapping techniques to improve reserve estimation accuracy. This study also adds reserve accuracy calculations using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The data used consists of motor vehicle claim data with a quarterly observation period from 2017 to 2021. The results show that the MAPE value of the BDCL method is 12.62%, while the Bootstrapping Bornhuetter Ferguson method produces a MAPE of 8.10%. This indicates that the Bootstrapping Bornhuetter Ferguson method outperforms the BDCL method in calculating claim reserve estimates