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

• Published in: 2014 Seventh International Joint Conference on Computational Sciences and Optimization pp. 450 - 454
• Main Authors: Xiaoning Cheng, Qing Zhu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-07-2014
• Subjects: Benchmark testing; Binary Logistic Choice Model; Economic indicators; Educational institutions; Indexes; Loans and mortgages; Logistics; Personal Housing Mortgage Loans; Prepayment Risk
• DOI: 10.1109/CSO.2014.92

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.