This study considers the risk management of insurance policies in line with the implementation of the new International Financial Reporting Standards 17.It applies the paid-incurred chain method to model the future un...This study considers the risk management of insurance policies in line with the implementation of the new International Financial Reporting Standards 17.It applies the paid-incurred chain method to model the future unpaid losses by combining the information channels of both the incurred claims and paid losses.We propose the recovery of the empirical distribution of the outstanding claims liabilities associated with a group of contracts via moment-based density approximation.We determine the risk measures and adjustments that are compliant with the new standard using the Monte–Carlo simulation method and approximated distributions.The historical data on the aggregate Ontario automobile insurance claims over a 15-year period are analyzed to examine the appropriateness and accuracy of our approach.展开更多
基金supported by the Basic Research Plan of Yunnan Province,China(No.2019FA020)the Yunling Scholars of Yunnan Province,China(No.KKRC201952012)the Leading Talents of Industrial Technology in Ten Thousand Talents Plan of Yunnan Province,China,and the Scientist Studio of Yunnan Province,China.
基金This study was funded by the MITACS Accelerate Grant-Award Number IT12339the Foreign Young Talents Program of the Ministry of Science and Technology of China(QN20200017001)the China Postdoctoral Science Foundation(2020M672913).
文摘This study considers the risk management of insurance policies in line with the implementation of the new International Financial Reporting Standards 17.It applies the paid-incurred chain method to model the future unpaid losses by combining the information channels of both the incurred claims and paid losses.We propose the recovery of the empirical distribution of the outstanding claims liabilities associated with a group of contracts via moment-based density approximation.We determine the risk measures and adjustments that are compliant with the new standard using the Monte–Carlo simulation method and approximated distributions.The historical data on the aggregate Ontario automobile insurance claims over a 15-year period are analyzed to examine the appropriateness and accuracy of our approach.
