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.

在其基本结构中，反向抵押贷款 (RM) 是一种合同，房主在其去世时借入其房屋未来清算价值的一部分或全部。贷款人所承担的风险与房地产市场的波动有关，即房价风险，金融市场风险，即利率风险，以及借款人生命周期的不确定性，即长寿。风险。无论是从贷方还是从借方的角度来看，未来清算价值的量化及其在发行时的估值对于构建 RM 合同至关重要。在论文中，我们探索了使用神经网络来投影房地产市场数据；这种方法允许获得定价过程的预测分析，并且确实提供了动态定价算法。