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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/49309

Title: 基於人口結構之壽險評價模型
Population Based Valuation of Taiwan Life Insurances
Authors: Yi-Wen, Wu
Contributors: NTOU:Department of Computer Science and Engineering
Keywords: 雲端財務系統;保險;固定收益模型;生命表;死亡機率;人口結構
Financial Cloud;Insurance;Fixed income model;Life table;Mortality rate;Population structure
Date: 2015
Issue Date: 2018-08-22T06:56:30Z
Abstract: 政府統計數據顯示,在台灣平均每位國民持有約2.3的人壽保單,而投資人壽保險的保費支出占GDP國內生產毛額(亦即保險滲透度)高達 17.23%,居世界第一位。然而,大多數民眾投資人壽保險時往往不清楚其商品價值導致財富的套牢 。本研究基於雲端財務系統架構下建置固定收益模型 ( Fixed Income Model ) 來評價終身險之保單價值,並且探討在利用國民生命表的死亡機率下各式終身險保單是否會隨著風險的高低而產生改變,與被保人生存時的各階段投資中,於人口結構模型加權計算下探討處於有利的人口比例變化。 將性別與年齡作為區分比較,研究結果發現在不探討死亡機率下,投資結果受到保費影響較低,年齡越輕者投保價值越高,但在加入死亡機率的影響後,其保單價值高低產生變化。在人口結構的套用下,投保年齡越輕在大多數時間處於加權平均下投資價值較低的族群,因為受到滿期金的影響因素下,年齡越長者在領回速度較快而成為投資年期中的有利人群,當多數人到達滿期年齡後有利人口比例受年齡族群影響才開始顯著。
Taiwan government statistic data indicates that each person holds 2.3 life insurance policies on average and the money spent on life insurances measures up to 17.23% of the GDP, ranking first in the world. However, most people make investments in life insurances using a buy-and-forget strategy, not knowing how much this insurance is worth to them. This study proposes a new model using mortality rates from life tables and the distribution of population structure to price annuity style life insurances. Based on the Financial Cloud architecture, we design a flexible valuation system which is capable of taking account of the factors above to derive a price for insurance policies. Our experiment results show that the value of insurance policies differ significantly when considering mortality rates. Without the influence of mortality rates, young policy holders often get better returns. But taking the mortality rates into consideration, depending on the contract, the price may differ either greater or smaller than the model without mortality rate. This price difference can be a good indicator for deciding an investment on annuity style life insurances. The influence of population structure is visible whenever a cohort, usually starting from the eldest, reaches the expiry of the insurance policy. As more proportion of the populations reach expiry, the average value of the policy will grow higher and higher, leaving behind the younger cohort investors policy value under average. Policies must be carefully designed and take current population structure into consideration in order not to put all burden on the younger generations.
URI: http://ethesys.lib.ntou.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=G0010357036.id
Appears in Collections:[資訊工程學系] 博碩士論文

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