Reverse mortgages through artificial intelligence: new opportunities for the actuaries

Emilia Lorenzo (), Gabriella Piscopo (), Marilena Sibillo and Roberto Tizzano ()
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Emilia Lorenzo: University of Naples Federico II
Gabriella Piscopo: University of Naples Federico II
Roberto Tizzano: University of Naples Federico II

Decisions in Economics and Finance, 2021, vol. 44, issue 1, No 3, 23-35

Abstract: Abstract In its basic structure, the reverse mortgage (RM) is a contract where a home owner borrows a part or the totality of the future liquidation value of his home at the time of his death. The risks that are borne by the lender are linked to the volatility of the real estate market, that is the house price risk, the financial market risk, that is the interest rate risk, and the uncertainty of the borrower’s lifetime, that is the longevity risk. The quantification of the future liquidation value and its valuation at the issue time is fundamental in the construction of the RM contract either in the perspective of the lender or in the one of the borrower. In the paper, we explore the use of neural networks to project the real estate market data; this approach allows to obtain a predictive analysis of the pricing process and indeed provides a dynamic pricing algorithm.

Keywords: Artificial intelligence; Neural network; Pension product; Real estate; Reverse mortgage (search for similar items in EconPapers)
JEL-codes: C6 G1 G5 J1 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10203-020-00274-y

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