本文利用國內某商業銀行實際購買房貸壽險的消費者為研究樣本，透過銀行實際資料分析影響貸款客戶購買房貸壽險的決定因素有哪些？
以SAS(Statistics Analysis System)建構回歸模型進行分析，研究結果顯示：依消費者的借款金額、年齡、職業及教育程度的不同，可能是影響消費者購買房貸壽險金額高低的原因。
更進一步分析，除貸款金額與房貸壽險投保金額為正相關及年齡與房貸壽險投保金額為負相關外，職業及教育程度均因族群的不同而與房貸壽險投保金額分別有不同的相關聯性。當消費者的教育程度為國中以下教育程度時，其購買房貸壽險的比率最低，與房貸壽險投保金額則是呈現負相關；而教育程度為專科者，與房貸壽險投保金額兩者間亦為負相關；至於大學教育程度的消費者與房貸壽險投保金額兩者是呈現正相關的，其餘教育程度者結果則不顯著。而除職業為服務業的消費者與房貸壽險投保金額為正相關外，其餘職業為商、公教人員及其他行業者與房貸壽險投保金額均為負相關。
此研究結果，有助於金融機構及壽險公司瞭解潛在消費者的特性，將可以作為未來在保險商品設計與行銷策略擬定之參考。

The samples in the article are from the real buying Mortgage Life Insurance consumers of a domestic commercial bank. Analyze the determinants of the effect that Loan customers who buying Mortgage Life Insurance through the real data collected in the bank?
Construct the regression model by SAS, the result shows that：Depends on the differences of the amount of the consumer Loan amount,age, job occupation, and the level of education are the factors affect the consumers to buying Mortgage Life Insurance.
Further analysis, In addition to Loan amount is significant positive correlations to Mortgage life insurance rates, and years of Loan is negative correlations to Mortgage life insurance rates, Job occupation and education level are related to Mortgage life insurance rates separately by different population. When the education level of the consumers are under junior high, it has the lowest rate to buying Mortgage Life Insurance, and shows the negative correlation in Mortgage life insurance rates. Associate degree of the education level and Mortgage life insurance rates shows negative correlation. As for the consumers graduating from college and Mortgage life insurance rates shows positive correlation, results of the other levels are insignificant.
At last but not the least, in addition to the consumers whose job occupation is services sector shows positive correlation to Mortgage life insurance rates, others who are business, civil and teaching staff, or something else, are all show negative correlation to Mortgage life insurance rates.
The result of the study can help the financial institutes and life insurance companies realize the features of potential consumers. It can used in developing the strategy to design and promote insurant products in the future.

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