國際會計準則理事會( IAIS )將於2022年實施IFRS 17,台灣主管機關也就接軌IFRS17為產業設定各階段導入時程。在此新制下,要求各國從原先的固定折現因子改變為需要隨著市場資料即時變動之折現因子,保單貸款的會計科目也將從目前帳列資產,變成負債的減項,且要求保險公司將保單貸款將包括在保險合同的計量中。對於壽險公司,其最大的負債為其所發行之保單,因此在資產與負債的管理上,保單貸款行為就需要被列入特別考慮。 本研究將保單貸款的行為藉由真實保單貸款資料模型化,並預測未來保單貸款情形。將模型帶入生死合險試算各期保單現金流,最後再使用Smith-Wilson 模型與台灣公債、公司債資料建構適當的折現率曲線,計算此保單之準備金。 從結果中可以得知,無論使用ARIMA模型、Nelson Siegel 與 Nelson Siegel Svensson模型預測未來貸還款現金流,對於準備金的影響皆不大,其可能原因在於市場利率持續走低,使保戶進行保單貸款意願低,保單貸款僅佔保費的極小部分。
The International Accounting Standards Board (IAIS) will implement IFRS 17 in 2022, and the Taiwan authorities have also set up a phase-in schedule for the industry in line with IFRS 17. Under the new system, countries will be required to change from a fixed discount factor to a discount factor that changes in real time with market data. For life insurance companies, their largest liability is the policies they issue, so policy lending behavior needs to be given special consideration in the management of assets and liabilities. In this study, I modeled policy loan behavior using real policy loan data and predict future policy loan scenarios. The model is applied to the endowment insurance to calculate the cash flow of each policy period, and using Smith-Wilson model to construct an appropriate discount rate curve with the data of Taiwan bonds and corporate bonds to calculate the reserves of the insurance policy. From the results, it can be seen that the ARIMA, Nelson Siegel and Nelson Siegel Svensson models do not have a significant impact on the reserve, probably due to the low interest rates in the market and the low willingness of policyholders to take out policy loans, which account for a very small portion of the premiums.