This study contributes to addressing the problem of an aging population by providing important information that determines feasible monthly payments for the clients of Chinese reverse mortgage products and by promoting the implementation of reverse mortgages in China. The variables used in this study include mean values obtained from time series data, of the rate of increase of housing prices, and the probability value, interest rate, and mortality rate obtained through the geometric Brownian motion (GBM). For mortality rates, China Life Insurance female mortality rates (2000-2003) were used. This study aims to apply the main variables that affect reverse mortgage products in a monthly payment model based on Chinese financial market conditions, and determine loan values. In this study, Shanghai’s reverse mortgage monthly payments, by age levels, were calculated through the loan-to-value (LTV) and payment (PMT) methods to evaluate the value of the reverse mortgages. Based on the optimal combination of the three factors of payment amount, loan interest rates, and the level of acceptance of prices, efforts must be made to extract the best value for the elderly. Only in this way can the interests of both lenders and borrowers be protected, by increasing the market share and economies of scale of the reverse mortgage industry and effectively improving the living standards of the elderly.

• Ping Wang(Department of Industrial & Information Systems, Graduate School of Public Policy and Information Technology, Seoul National University of Science and Technology) Corresponding author
• Ji-Pyo Kim(Professor, Graduate School of Public Policy and Information Technology Seoul National University of Science and Technology)