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Reverse mortgage: a neural network approach for pricing and risk assessment
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Orientador(es)
Resumo(s)
Population aging and low precautionary savings rates has put European public social systems
under strain. As a result, home-ownership among seniors as viable mean of income stream
enhancement and welfare for seniors has been boldly encouraged by governments. Thus, equity
release instruments for pensioners have been proposed by the market. These products are mostly
encompassed in North America where the elderly are less reluctant to express their desire to
transform housing into wealth. Still, southern European countries present large home-ownership
rates and an aging low income population that may well unlock future demand.
Whilst housing is a highly illiquid asset and emotional attachment as well as inconvenience of
moving barriers may occur, in recent literature relatively new approaches to monetize homes
have undergone major developments.
Particularly, this study will be mainly concerned with the risk and profitability analysis of
reverse mortgage schemes through actuarial and deep learning techniques in the attempt to
conceive a framework that fully encompasses the valuation needs of companies willing to
commercialize home equity based products.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Retirement Reverse mortgage Pricing Risk assessment Long short term memory neural networks