The present study performed a bibliometric analysis using 119 articles in the field of reverse mortgages from the Web of Sciences (WoS) database from 1978 to May 2022. To provide a comprehensive result, this study employs VOS Viewer software to construct the networks of co-citations of authors and sources of articles. The results show that the growth trend was recognized from the beginning year 2011 and it gained significant attention from researchers before and during the predicament period of the Global financial crisis 2007-8. It can be seen that the positive trend of interest in this field of study remained in the following years, particularly in the years 2020 and 2021. Using the co-citation analysis, the authors focus on fundamental issues in reverse mortgages such as knowledge (literacy) and demands of reverse mortgage products for elderly homeowners, risks associated with reverse mortgages such as default on their property taxes and insurance, potential growth of reverse mortgages as a financial tool, and fair valuations of reverse mortgages. The Journal of the American Real Estate and Urban Economics Association and Insurance Mathematics and Economics are found to be the most-cited journals in the field of study of reverse mortgages.

The objective of this study is to examine the readiness of Malaysian millennials and Gen-Zs for fintech adoption in accounting. This study developed the conceptual framework based on the Unified Theory of Acceptance and Use of Technology (UTAUT)’s four key fundamental constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC). The research utilized a quantitative method using an online survey to gather data from 108 respondents across Malaysia. The findings indicate that PE and FC are found to be key predictors of users’ fintech adoption intention (AI). It was also discovered that EE and SI have no significance on users’ fintech adoption intention (AI). Also, AI has a significant impact on users’ loyalty to keep using Fintech services. It is observed that PE is the strongest predictor of fintech adoption intention followed by FC, and AI does have a positive influence on consumers’ fintech loyalty due to the positive correlation between them. The result also demonstrates that adoption intention has a direct effect on users’ fintech loyalty. To encourage consumers to further continue using fintech services in the future, it is necessary to build a consumer loyalty base. The presence of one may attract new users to adopt the fintech services hence forming loyalty. Overall, this study may help gauge a portion of Malaysian millennials and Gen-Z’s awareness, adaptability, and acceptance of fintech in accounting.