Stochastic evaluation of mortgage default losses resulting from flood damages and different mortgage arrangements for post-Katrina Louisiana houses

Purpose - – The purpose of this paper is to investigate the total number of mortgage default occurrence possibilities and monetary damage amounts to the sampled properties due to the excessive flooding caused by natural disasters. Mortgage default loss assessments due to natural catastrophic events are of great interest to lenders, insurance firms, forensic engineering professionals, inspecting agencies and the federal and state government planning officials and risk-mitigating teams. Design/methodology/approach - – In this study, a stochastic methodology is used to address the risk of mortgage default losses and the homeowners’ investment returns, given: damage severity levels of hurricane floods and the mortgage types and arrangements on selected properties. Nine different houses, with various mortgage arrangements, located in different flood damage zones were investigated three years after Hurricane Katrina. To quantify the flood damage risk values which are compared with exceeding damage probabilities, the Poisson’s distribution is used through performing random variable analysis walks for each property during each house’s mortgage life cycle. Findings - – Henceforth, through introduction and constructing the “Zonal Damage Matrix” for the investigated houses, the total number of mortgage default occurrence possibilities and monetary damage amounts to the properties are calculated for each exceeding flood. Thereafter, the homeowners’ net equity values and the investment returns are estimated for risk identification and evaluation purposes. Originality/value - – For each of the sampled houses, the probability of mortgage defaults and the homeowners’ net equity values are estimated using Poisson’s distribution based on 60,000 randomly generated numbers to construct ten different hazard-related default scenarios for each property over the 30-year mortgage life cycle. The investment returns are therefore estimated for risk identification and evaluation purposes.