Prepayment Risk of Personal Housing Mortgage Loans Research: The Case of Xi'an, a Commercial Bank

Xiaoning Cheng, Qing Zhu
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Abstract

In recent years, Chinese real estate finance is booming, and balance of personal housing mortgage loans is rising yearly. However, its features become significant, which touch upon long-time, low-rate and huge increase in prepayment percentage, leading to a largely increased proportion of bank's interest loss, service cost and management cost. Therefore, it makes new requirements for commercial banks to manage and control prepayment risk. Based on the research data of Xi'an A bank's personal housing mortgage loan client samples, this paper will use binary logistic choice model, from three dimensions of borrower features, loan features and regional features, to finish the investigation, which refers to the significant factors that affects prepayment risk of personal housing mortgage loans. The research shows that the significant factors of affecting prepayment include the real housing price index, loan term, benchmark interest rate, and borrower's monthly income. But other factors are not significant, such as the borrowers' gender, age, monthly payment, loan amount and the expected housing price index.
个人住房抵押贷款提前还款风险研究——以西安商业银行为例
近年来,中国房地产金融蓬勃发展,个人住房抵押贷款余额逐年上升。但其特点显著,即时间长、利率低、提前还款率增幅大,导致银行利息损失、服务成本和管理成本所占比例大幅增加。因此,对商业银行提前还款风险的管理和控制提出了新的要求。本文将基于西安A银行个人住房抵押贷款客户样本的研究数据,运用二元logistic选择模型,从借款人特征、贷款特征和区域特征三个维度,来完成对影响个人住房抵押贷款提前还款风险的显著因素的调查。研究表明,影响提前还款的显著因素包括实际房价指数、贷款期限、基准利率和借款人月收入。但其他因素不显著,如借款人的性别,年龄,月供,贷款金额和预期房价指数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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