- Original authors / creators
- Maryam Sholevar
- Original publication
- Journal of Financial Services Marketing · · 2026-08-07
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- CC BY 4.0
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- Evidence limits
- Adjacent research, not a directly sampled family-office study. Applicability to a family office requires separate assessment. Although financial literacy had been discussed since the 1970s, the 2008 global financial crisis brought it to the forefront as a central academic topic and policy concern, exposing widespread gaps in the public’s understanding of financial systems (Goyal and Kumar 2021). The 2008 crisis was closely linked to subprime mortgage losses and securitisation, as well as wider failures in regulation, supervision, institutional risk management, and credit ratings. One possible theory is that poor financial decisions stem from shortsightedness arising from a lack of understanding of financial products. Post-crisis policy discourse increasingly emphasised financial education and individual capability, sometimes alongside critiques that this emphasis may underplay structural causes. In fact, it has become common to highlight the lack of financial literacy among consumers during crises, from the 2008 crash to the COVID-19 pandemic (Knowles and Schifferes 2020; Gerth et al. 2021; Bechlioulis and Karamanis 2023; Setiawan et al. 2024). As a result, financial literacy became more prominent in post-2008 policy and research agendas and was frequently referenced by major financial institutions and federal bodies in the United States. Prominent studies, such as those by Lusardi and Mitchell (2011), established a foundation for subsequent research by linking financial literacy to wealth accumulation, retirement planning, and overall financial well-being. Cude (2021) explained that Lusardi and Mitchell did not provide a simple definition of financial literacy in their pioneering works. This lack of definitional clarity has prompted critiques, including concerns over the universal applicability of their framework and the appropriateness of their assessment methods. Studies such as those by Klapper et al. (2015) highlight the limited global applicability of standardised measures of financial literacy, noting significant disparities across financial systems, product access, and educational priorities. Atkinson and Messy (2012) argue that the focus on interest rates and investment products overlooks basic financial practices prevalent in developing and underbanked regions. In most countries, individuals’ primary concern is access to basic financial services rather than credit. Even in the United States, 4.5% of individuals are still unbanked (Federal Deposit Insurance Corporation, 2022). In many cases, people use complex financial loans (including unregulated markets) whose overall interest rates can be devastating, and a rudimentary understanding of interest rates might even exacerbate the illusion of affordability. Therefore, there is a vital need to move away from the established oversimplification of financial literacy. Stella et al. (2020) utilised principal component analysis and proposed a new questionnaire to measure financial literacy across three main dimensions: attitude, skills, and knowledge. This reflects the broader need to treat financial literacy not as a single narrow score, but as a construct whose meaning depends on the financial, institutional, and social context in which it is measured. Data scope: Although the original data collected for this study are tailored to the research objectives, they are limited to a specific geographic and demographic context. Generalisability to other populations and regions remains a challenge and requires further validation. Cross-study comparisons: The framework’s applicability is constrained by the lack of independent analyses using different datasets. Comparative studies are necessary to test the framework’s reliability and robustness across diverse contexts. Complexity of dimensions: Some dimensions, particularly financial literacy, are highly complex and overlap with other dimensions. Future research should refine these constructs to capture their multifaceted nature better. Data collection: Since this research aimed to collect data from a diverse and understudied population, sub-Saharan Africa was chosen to provide a more heterogeneous picture of financial behaviour. This came with its own challenges as questionnaire literacy and the diversity of regional languages made interviewer-assisted administration essential, and the dialogue between participants and interviewers could introduce inevitable bias despite the safeguards adopted. Sample size and multidimensionality: A critical point to stress is that the data (e.g., correlations or KMO tests) are statistically acceptable, but they do not necessarily reflect strong, decisive relationships. There are two key implications. First, the multidimensional nature of financial behaviour makes it difficult to draw definitive conclusions. This is indeed the same point the present paper aims to address: the drawbacks of oversimplifying multifaceted financial behaviour. Second, to inspect multidimensional features, large datasets are typically required. Unfortunately, it is often not feasible to conduct such large surveys within individual research projects. This is why many researchers rely on secondary data from large, general surveys, which often lose their multidimensional nature due to their generality and lack of targeted focus on interconnected dimensions.
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