本研究以保險事業發展中心之資料分析各種不同因子如年度、性別、保額、有無體檢、保費繳別、保單年度及利差、利率等對脫退率之影響，並將其中較具顯著影響的因子納入脫退率模型之建立，期望能藉此模型準確估計台灣壽險公司生死合險、終身壽險以及定期壽險之脫退率，進而幫助壽險公司之財務規劃。 自本研究之分析發現其中最具影響力之因子為保單生效後之保單年度，因此以此為主軸建立脫退率模型，接著，亦考量利差以及利率所呈現的趨勢於其中分別建立保單年度利差模型以及保單年度利率模型，此外，更完整考量本研究中脫退率相關因素，以羅吉斯迴歸方法建立模型。最後將此四種模型應用於壽險公司準備金之提存，以生死合險為例模擬公司現金流量，發現準備金之分配如同 Tsai et al.(2002)受利率風險影響甚鉅，而加入本研究所建立之四種脫退率模型模擬後，反而減少了公司未來所須面臨的利率風險，其中又以保單年度模型影響最大，而第四種脫退率模型不同於Tsai et al.根據台灣壽險經驗加入所有具影響之因素，其模擬結果介於保單年度模型以及保單年度利率模型間，可發現考量因素之不同對脫退率影響甚鉅，繼而影響準備金之提存。 / In this article, we focus on the causes and the features of lapse rate including year, sex, size, underwriting method, premium payment mode, policy year, interest rate and interest rate difference by collecting and analyzing the empirical data of endowment, whole life insurance and term life insurance in Taiwan from Taiwan Insurance Institute. Then we take factors that have effect with lapse rate into account to establish model, and we hope to accurately estimate the lapse rate of endowment, whole life insurance and term life insurance in Taiwan by these models, and assist the life insurance companies’ financial decision making. After analyzing, we find the most effective factor of this study is the policy year, which means the year after issuing, so we take this one as our primary consideration of our lapse rate model. Then we add the interest rate difference and interest rate in the further two models. Beside this, we further consider the important factors in the part of analysis and put it in the fourth model by using Logistic Regression Model. Finally, we apply these four models to the policy reserve of life insurance company by taking endowment policy as an example simulating the cash flow. We find that the results was same as Tsai et al. (2002) that distribution of policy reserve is strongly affected by interest rate risk, but can decrease interest rate risk the company have to face in the future by adding our lapse rate models, especially the policy year model, and the fourth lapse rate model which count into most factors was not the same as Tsai et al. producing result between policy year model and the policy- interest rate model. From the results of all the lapse rate model. We can know that considering different factors in the model will bring such distinct contribution amount of reserve for life insurance company.

一般而言，壽險公司會在保險契約生效前就支付保單相關之費用，例如核保與承保之成本，並且公司會預期未來保險期間內可以填補上述費用；但若保戶於保險期間內早期解約或是解約情形嚴重，將使壽險公司難達到損益兩平之目標而招受損失，影響公司預期盈收，進而增加公司資金調度上之困難。因此，對於長期穩健經營之壽險公司而言，瞭解各保險解約率變動情形對於公司之財務規劃相當重要，以期降低危害公司之風險。 本文期望藉由台灣保險事業發展中心之實證資料蒐集與相關分析，探討影響台灣壽險業生死合險及不還本終身壽險解約之因素以及其解約率之特性，進而建立與利差及保單年度相關之解約率模型，以期能準確地估計台灣壽險公司生死合險解約率與不還本終身壽險解約率。除此之外，本研究將所建構之解約率模型應用於公司未來現金流量分析，以蒙地卡羅法模擬各險種保單準備金之分配，瞭解各種解約率假設對於公司未來現金流量之影響，進而瞭解解約率參數假設對於準備金風險之評估扮演重要角色。 / In general, the life insurance companies would pay the expenses with respect to the insurance policies before the validity of insurance contracts such as underwriting and insuring costs. If the policyholders are early-surrendered or over-surrendered during the policy period, then it will make the insurance companies hard to achieve their break-even goal and result in affecting the companies’ surplus as well as management of their capital. Thus, for the long-term and stable life insurance companies, it is extremely important to understand the changes of lapse rate in order to reduce the financial risk damage before making any financial decisions. In this article, we expect to focus on the causes and the features of lapse rate changes by collecting and analyzing the empirical data of endowment and whole life insurance in Taiwan from Taiwan Insurance Institute. Based on our analysis, we could build the lapse rate model concerning the relation between the lapse rate and interest rate difference or policy year for estimating the endowment lapse rate and whole life insurance lapse rate accurately. Moreover, we apply the lapse rate model to company’s cash flow analysis. We employ the Monte Carlo simulation to simulate the policy reserve distribution, and we find out that the lapse rate assumption plays an important role in the policy reserve evaluation.