Risk profiles of Reverse Mortgage: empirical evidence from Italy

Among the many challenges facing the world economies, population aging is no doubt one of the most important. According to World Bank Data, the old-age dependency ratio in the world increased from 11% in 2000 to 15% in 2022, and it is expected to increase to 32% by 2050. Both increasing life expectancy (+5.9%) and declining fertility rate (-0.32%) in the last twenty years contributed to World’s rapid population aging. In addition, the inadequacy of pension systems to guarantee acceptable living standards and the large share in the European and North American population of so-called home rich-cash poor individuals are further motivations for the elderly to need to need more funding. The Reverse Mortgage (RM) is a feasible solution for financial needs associated with longevity and it interacts directly with the elderly policyholder. A RM contract allows (usually elderly) homeowners to receive a loan (a lump sum or a periodical cash flow) that will be repaid through the selling of her home following her death or her moving out of the home for any reason. Such a contract typically includes a no negative equity guarantee: if the loan balance exceeds the proceeds from the property’s sale, the amount owed to the lender (e.g., the bank) is reduced to a (ante) fixed quantity. The lender is required to assess the level of risk in the RM contract by considering the lifetime of the holder, the value of the asset (the home), and the interest rate of the loan, which are all stochastic variables. Therefore, the RM contract is driven by three distinct risks: longevity risk, house price risk, and financial risk. Recently, the authors have used a closed formula to mathematically decompose the volatility of the gain/loss for a lender in a RM contract through the above risks, and provided indexes for each component to assess their importance. This paper intends to evaluate the effects of the risk quantification proposed on selected geographic regions of Italy in the period ranging from 2006 to 2023. A Quantitative Risk Analysis (QRA) was performed on data from databases regarding Demography, Health, Economics and Finance. The QRA contemplated the use of 35 both parametric methods and non-parametric approaches for the purpose of prediction. The work contributes to: 1) bridge the gap between theoretical approaches during the early design phase of the financial instrument RM and empirical approaches during its actual applications; 2) give the lender a tool to assess and manage the RM contracts in Italy that are based on geographic areas: 3) improve the understanding and diffusion of RM contracts; 4) provide a list of possible scenarios for policymakers and regulators to take positive or negative actions.