Linking Financial Literacy and Behavioural Finance to Saving and Debt Behaviours: A Literature Review of Global and Developing Economy Contexts

Abstract

This paper aims to analyse the contributions of studies that link financial literacy (FL) and behavioural finance (BF) in relation to saving and debt behaviours, considering both global and developing economy perspectives. This study employs a semi-systematic literature review (S-SLR) to examine 109 articles sourced from Scopus and Web of Science, published between 2011 and 2024. The evidence shows mixed results regarding the influence of FL and behavioural factors on saving and debt behaviours, with saving receiving greater attention. Most research is quantitative and concentrated in developed economies, although some developing Asian economies are also represented. The in-depth analysis of developing economies indicates that, while FL training and intervention-based approaches are relatively well established, studies integrating FL and BF remain scarce, limiting a comprehensive understanding of financing decisions. Future research should therefore prioritise the developing contexts, adopt more diverse methodologies, and incorporate psychological variables. This S-SLR offers an integrated perspective on FL and BF in relation to saving and debt behaviours as components of financing decisions, contrasting with existing literature reviews, which typically treat these fields separately, focus on investment decisions, and provide limited in-depth analysis of developing economy contexts, while also generating insights to support future research on this interconnection.

1. Introduction

Over several years, research on financial literacy (FL) and behavioural finance (BF) developed largely independently and was often viewed as mutually exclusive rather than complementary (Fernandes et al., 2014; Rasool & Ullah, 2020). Nevertheless, both areas were used as explanatory variables in studies of financial decision-making. Over the past decade and a half, research has gradually shifted to examine the interaction between FL and BF and their combined influence on financial decision-making (e.g., Adil et al., 2022; Ashfaq et al., 2023; Baker et al., 2019; Pham & Le, 2023). This study, therefore, analyses the contributions of the literature linking these two domains, particularly regarding saving and debt behaviours. In this context, “behaviours” encompasses intentions, attitudes, and decision-making, consistent with the conceptual approaches adopted in the studies included in this semi-systematic literature review (S-SLR) (e.g., Kusairi et al., 2019; Thomas et al., 2023; van Deventer, 2020).

Much of the literature linking FL and BF—both empirical (e.g., Abideen et al., 2023; Adil et al., 2022; Sapiri & Awaluddin, 2023; Suresh, 2024) and literature reviews (e.g., Badola et al., 2023; Dhingra et al., 2023; Gorzon et al., 2024)—has largely focused on investment decisions, particularly within stock market contexts. Consequently, fewer studies examine individuals’ decisions regarding savings and debt, that is, financing decisions that sustain the ordinary course of life. These decisions concern how individuals obtain resources to meet present needs and future financial goals (Atrill, 2020; Hou et al., 2022), and are particularly relevant in developing economies where household financial vulnerability is more pronounced.

Despite the aforementioned limited studies linking FL and BF to saving and debt behaviours, this research stream has gradually expanded over the past fifteen years (e.g., Ananda et al., 2024; Balasubramnian & Sargent, 2020; Choi, 2015; Friedline & West, 2016; Lučić et al., 2023). In light of this development, conducting an S-SLR appears relevant for synthesising existing evidence and supporting further research. Accordingly, this study aims to: (1) identify the main approaches and contributions of research interconnecting FL and BF in relation to saving and debt behaviours; (2) examine the methodological approaches and methods employed in these studies; (3) identify and characterise the geographical distribution of the research; and (4) highlight and suggest directions for future research.

To address the stated objectives, the following research questions were formulated:

Research question 1: What are the main approaches and contributions of studies linking FL and BF in relation to saving and debt behaviours?

Research question 2: What methodological approaches and research methods are employed in studies linking FL and BF concerning saving and debt behaviours?

Research question 3: What is the geographical incidence of studies examining the relationship between FL and BF in the context of saving and debt behaviours?

Research question 4: What suggestions for future research can be drawn from studies on this topic?

Although the geographical incidence is specifically addressed in the third research question, the analysis of each question distinguishes between all reviewed articles and those conducted in developing economies, reflecting one of the study’s central focuses.

This study offers a novel and timely contribution by providing the first S-SLR that specifically examines how financial literacy and behavioural finance jointly shape saving and debt behaviours, domains that have received far less scholarly attention than investment decisions. By synthesising fifteen years of dispersed evidence, with a particular focus on developing economies, the review clarifies conceptual linkages, maps methodological tendencies, and reveals significant geographical and thematic gaps in existing research. This integrated perspective not only advances understanding of financing decisions in everyday life but also establishes a foundation for future empirical and theoretical work, especially in contexts marked by heightened financial vulnerability.

The findings provide a nuanced understanding of how FL and BF influence saving and debt behaviours, with saving behaviour being the most frequently analysed. Around 90% of studies adopt quantitative approaches based on questionnaires and causal or correlational testing. Research is concentrated mainly in developed countries, especially the USA, the UK, Spain, and Poland, while only a few countries represent Asia and Africa, and Oceania remains underexplored. The in-depth analysis of developing economies shows that FL training and intervention-based methods are relatively well established in response to structural financial vulnerability. However, studies integrating FL and BF remain limited, constraining a more comprehensive understanding of financing decision-making. The overall conclusion relates to the fact that future research should focus more on developing economies (Ananda et al., 2024; Bapat, 2020), adopt intervention, experimental, and longitudinal designs (Harahap et al., 2022; Lučić et al., 2023), and incorporate psychological and motivational variables that remain insufficiently explored (Steinert et al., 2020; Wann et al., 2023).

The remainder of the paper is organised as follows. Section 2 describes the procedures for conducting the S-SLR, including the article selection process and data analysis methods. Section 3 presents and discusses the findings in relation to the research questions and proposes directions for future research. Section 4 concludes by summarising the main findings and outlining the study’s contributions and limitations.

2. Materials and Methods

According to Snyder (2019), SLR has become increasingly prominent in economics and business research, and recent studies examining FL and BF have also employed this method (e.g., Arjun & Subramanian, 2024; Badola et al., 2023; Silva et al., 2023). This study adopts the S-SLR, a version of SLR particularly suitable for topics characterised by multiple conceptualizations and the integration of different disciplines or research areas (Snyder, 2019), which aligns with the conceptual framework presented in Figure 1. This author also emphasises that the S-SLR focuses on mapping dominant themes and identifying research gaps through predominantly narrative and qualitative analysis, unlike the predominantly quantitative orientation associated with purely SLR, bibliometric, or meta-analysis reviews. Conducting an S-SLR requires careful planning and systematic procedures, from formulating research questions to selecting, coding, analysing, and extracting results from relevant documents (Snyder, 2019). This study follows these procedures, detailed in the following sections and subsections.

2.1. Guiding Conceptual Framework

Analysing saving and debt behaviours requires considering both rational factors, such as FL, and behavioural tendencies, including the biases highlighted in BF (Choi, 2015; Shen, 2014). This paper builds on the growing literature linking FL and BF, with a particular focus on decision-making related to savings and debt. Research examining the interaction between FL and BF in relation to financial behaviours (e.g., Białowolski et al., 2021; Friedline & West, 2016; Lučić et al., 2023) indicates that this interaction is fundamentally shaped by concepts such as financial capability, sociodemographic factors, and the various psychological dimensions applicable to finance. In addition, the OECD (2022) framework on FL, financial inclusion, and financial well-being, and theories of consumer behaviour, support measuring FL while also offering elements that help explain financing behaviours as decisions aimed at meeting everyday and medium-to-long-term financial needs. This theoretical basis is illustrated in Figure 1, which presents the guiding framework adopted for conducting this S-SLR.

Research on rational and behavioural determinants of financial decision-making suggests that, although financial behaviours constitute an integral component of the elements reflected within FL and BF (that is, actions shaped by external learning processes and intrinsic psychological factors), they are ultimately embedded in individuals’ financial choices (intentions, attitudes, and decisions), broadly regarded as financial behaviours, as noted above. In light of this, the conceptual framework presented in Figure 1 positions financial behaviour as both an input and an output. As an input, it represents one of the three core components of FL and BF—together with knowledge and attitudes (Espinoza-Delgado & Silber, 2024; OECD, 2022; Son & Park, 2019), and biases and emotions (Hayes, 2020; Kapoor & Prosad, 2017; Raaij, 2014; Statman, 2019), respectively—and includes practices such as budgeting, purchase management, saving for emergencies and retirement, and debt management, which collectively influence individuals’ financial decision-making. As an output, financial behaviour reflects how individuals’ FL and BF mechanisms shape their intentions, attitudes, and decisions about saving and debt.

2.2. Document Selection

As an S-SLR, which allows flexible adoption of SLR procedures, this study employed the PRISMA 2020 model (Page et al., 2021) for the document search process in accordance with the requirements of the S-SLR approach. The document search, conducted on 6 January 2025, used the Scopus and Web of Science databases, which are both comprehensive platforms that index globally recognised research. Before the main document search for this S-SLR, we reviewed the existing literature reviews linking FL, BF, and financial behaviours or decisions. This step revealed the absence of any SLR addressing the topic defined by the conceptual framework in Figure 1.

The main document search used keywords derived from the conceptual framework (see Figure 1). Most terms were represented by abbreviations marked with an asterisk (*; see Figure 2) to capture variations in terminology across the literature. To maximise coverage, the search focused on BF and incorporated concepts reflecting the three key areas identified earlier: biases, emotions, and financial behaviour (e.g., Hayes, 2020; Kapoor & Prosad, 2017; Raaij, 2014; Statman, 2019). Equivalent expressions, such as behavioural characteristics and behavioural traits, were also included, alongside the singular use of biases, as some studies examine specific biases in relation to FL (e.g., Ananda et al., 2024; Balasubramnian & Sargent, 2020; Foltice et al., 2018).

The research was limited to: (1) articles and review papers; (2) publications in English, Spanish, and Portuguese; and (3) studies in economics and business (see Figure 2). The first criterion ensures scientific credibility, as these documents are peer-reviewed (Massaro et al., 2016). The second criterion reflects the authors’ language proficiency, noting that a few publications were also available in Russian and Ukrainian. The third criterion is justified by the large body of research in these fields and their alignment with the authors’ research interests.

The sample articles were selected by reviewing abstracts and, where necessary, full texts. The main inclusion criterion was strong alignment with the topic of this S-SLR. Selected studies needed to address FL or financial education and BF—including financial behaviour, emotions, and biases (Hayes, 2020; Kapoor & Prosad, 2017; Raaij, 2014; Statman, 2019)—in relation to saving and/or debt behaviour. Figure 3 summarises the process from document identification to sample selection.

As shown in Figure 3, this S-SLR comprises 109 articles, including two (Choi, 2015; Shen, 2014) identified through earlier reviews. Their inclusion does not reduce the novelty of this study. Neither article employed the systematic review approach, as both lack the methodological rigour associated with it (Massaro et al., 2016; Snyder, 2019). Moreover, they analyse FL and behavioural biases separately rather than within the interactive framework adopted in this S-SLR (see Figure 1). Nevertheless, they were included for their related content, which helped establish the basis for our differentiation, and for their useful suggestions for future research, particularly those provided by Shen (2014).

2.3. Coding and Grouping for Analysis

The coding of the selected articles was organised into three categories (labelled A, B, and C), which guided the analysis and the examination of the research questions:

• Thematic approach—This category includes the predefined approaches outlined in the conceptual framework, together with additional themes identified through the comprehensive analysis of each article. While the framework focused on savings and debt, some studies also addressed related topics such as investment behaviour, daily financial management, and insurance;
• Methodological approach and method—This category covers the methodological designs and data collection methods used in the studies, either individually or in hybrid forms;
• Geographical incidence—This category identifies the locations in which the empirical studies were conducted, organised by continents and countries.

To analyse the findings on global and developing economies separately, we use the World Bank (2024) classification based on countries’ 2023 per capita income. This system distinguishes developed economies (high-income) from developing economies (low-income, lower-middle-income, and upper-middle-income). Countries that changed classification during the analysis period (2011–2024), namely Romania and Russia, were assigned to the category in which they remained the longest. Studies covering multiple countries were classified as developed if at least one country was in the high-income group. We excluded 4 literature reviews that lacked a specifically defined geographical incidence. As a result, the global analysis is based on 109 articles, while the analysis of developing economies is based on 40 articles.

3. Results and Discussion

This section outlines and analyses the findings in line with the research questions. As shown in Figure 3, this S-SLR comprises 109 articles selected from an initial pool of 502 retrieved from Scopus and Web of Science. Figure 4 presents the annual distribution of articles within the sample over the twelve years covered by this S-SLR.

Figure 4 indicates that research linking FL and BF to saving and debt behaviour dates back approximately fifteen years. This supports our objective of highlighting these studies, including their methodological approaches and geographical contexts, in line with Walstad and Wagner’s (2023) recommendation to conduct literature reviews in this area. Consistent with the objectives of this S-SLR—to examine the interconnections between FL and BF in relation to saving and debt behaviour—the findings are presented in

Table 1. Quantitative summary of the findings of the first three questions.

Characteristics of the Studies of the Sample Regarding the First Three Research Questions	Total Articles	%	Developing Economies	%
A. Thematic approach	109		40
A1. Financial literacy and behavioural finance on saving behaviour	42	38.53%	17	42.50%
A2. Financial literacy and behavioural finance on debt behaviour	32	29.36%	9	22.50%
A3. Financial literacy and behavioural finance on both saving and debt behaviours	15	13.76%	8	20.00%
A4. Financial literacy and behavioural finance on daily financial management (expense budgeting and purchasing management), with one or both approaches on saving and debt behaviours	16	14.68%	4	10.00%
A5. Financial literacy and behavioural finance on insurance decisions, with one or both approaches on saving and debt behaviours	2	1.83%	0	0.00%
A6. Financial literacy and financial behaviours (money management, debt, and savings) on financial well-being, with one or both approaches on saving and debt behaviours	2	1.83%	2	5.00%
B. Methodological approach and method	109		40
B1. Quantitative approach, through hypothesis testing based on questionnaires (single application) and cross-sectional experiments, as well as the simulation of practical decision scenarios	82	75.23%	31	77.50%
B2. Quantitative approach, through hypothesis testing based on pre- and post-application of questionnaires on longitudinal experiments and interventions (through financial literacy and/or behavioural finance training)	16	14.68%	7	17.50%
B3. Qualitative approach, based on interview content analysis	4	3.67%	1	2.50%
B4. Hybrid (involving interviews and their respective qualitative analysis, as well as questionnaire and hypothesis testing)	1	0.92%	1	2.50%
B5. Literature review	6	5.50%	0	0.00%
C. Geographical incidence by continents (and countries)	109		40
C1. Europe (Spain—6; UK—5; Poland—5; Sweden—3; Italy—1; Romania—1; France—1; Germany—1; Netherlands—1; Slovakia—1; Various countries—2)	27	24.77%	1	2.50%
C2. America (USA—30; Brazil—2; Peru—2; Canada—1)	35	32.11%	4	10.00%
C3. Asia (Indonesia—6; India—5; Malaysia—3; Thailand—3; Vietnam—2; Turkey—1; Japan—1; Taiwan—1; Laos—1; Philippines—1; Israel—1; Various countries—1)	26	23.85%	23	57.50%
C4. Africa (South Africa—5; Ethiopia—2; Rwanda—1; Uganda—1; Tunisia—1; Ghana—1; Zimbabwe—1)	12	11.01%	12	30.00%
C5. Oceania (Australia—5)	5	4.59%	0	0.00%
Not applicable—Literature reviews	4	3.67%	0	0.00%

Source: Author’s own work.

, based on the coding scheme outlined in Section 2.3.

It should be noted that one of the aims of research linking FL and BF to saving and debt is to support the rational allocation of resources and reduce disparities in financial capability across developed and developing economies. Accordingly, the results are presented and discussed from both global and developing-economy perspectives to enable systematic comparison between contexts.

Table 1 summarises the quantitative findings for the first three research questions—covering thematic, methodological, and geographical approaches—based on the 109 articles analysed. Following Table 1, these results are further interpreted descriptively, illustrated through Figures, and complemented with proposals for future research. They are also discussed within the scope of the concepts and consumer behaviour theories broadly presented in Figure 1 and further detailed according to the actual use of these theories in the studies included in the sample (Figure 5). It should be noted that Figure 5 reflects the frequency with which theories were employed rather than the exact number of studies, as some studies relied on multiple theories to support their frameworks and analyses.

The classification presented in Table 1 serves not merely as a descriptive catalogue of the literature but as an analytical framework that reveals how different strands of research converge and diverge in explaining saving and debt behaviours. By organising the studies according to their thematic focus, methodological orientation, and contextual setting, the Table highlights the structural patterns that underpin the field. This structure allows us to identify clusters of research that share common assumptions or theoretical foundations, as well as areas where conceptual fragmentation persists. In this sense, Table 1 functions as a scaffold for synthesis, enabling a more integrated interpretation of how financial literacy and behavioural finance jointly shape financial decision-making across diverse populations.

Although most studies did not explicitly rely on consumer behaviour theories, some adopted such perspectives, particularly the theory of planned behaviour and the theory of bounded rationality, which together accounted for 12 applications in the sample.

Building on this framework, the subsequent analysis moves beyond the categories themselves to examine the theoretical implications of the patterns identified. For example, the concentration of studies employing rational-choice-based measures of FL alongside behavioural constructs such as overconfidence, present bias, or self-control suggests an implicit recognition of the complementary nature of these perspectives. At the same time, the uneven geographical distribution of studies—heavily weighted toward high-income economies—raises questions about the generalisability of existing theories and highlights the need for context-sensitive models that account for structural constraints and cultural influences. These insights, derived from the organisation of Table 1, contribute to a deeper theoretical understanding of how FL and BF interact in shaping saving and debt behaviours.

The methodological diversity captured in Table 1 also reinforces the appropriateness of the S-SLR approach adopted in this review. The studies span a wide range of designs, including conceptual analyses, cross-sectional surveys, experiments, qualitative investigations, and mixed-methods research. This heterogeneity makes it methodologically inappropriate to apply a PRISMA-based SLR or meta-analysis, both of which require a level of standardisation and comparability that the current evidence base does not provide. Instead, the S-SLR approach allows us to integrate insights across these varied methodologies, identify thematic linkages, and synthesise conceptual contributions that would be obscured by a purely quantitative or protocol-driven review. Thus, the structure of Table 1 not only organises the literature but also illustrates why a narrative, integrative synthesis is the most suitable method for advancing understanding in this field.

3.1. Thematic Approaches and Contributions

The first section of Table 1 addresses the first research question. It shows that studies linking FL and BF mainly focus on saving behaviour (38.53%), followed by debt behaviour (29.36%) and combined saving and debt behaviours (13.76%). The remaining studies (18.35%) combine these themes with additional topics identified under coding category A (see Section 2.3), namely investment behaviour, daily financial management, and insurance. This pattern reflects the tendency of individuals to prioritise income preservation through saving and resort to debt when resources become insufficient. A similar distribution appears in developing economies, where saving behaviour also predominates (42.50%), followed by debt (22.5%), combined saving and debt behaviours (20.00%), and additional thematic approaches (15.00%). The following paragraphs discuss the main contributions of these thematic approaches.

3.1.1. The Role and Limitations of FL in Shaping Effective Saving and Debt Behaviours

Several studies from both global and developing economy contexts argue that FL is essential for sound saving and debt decisions (e.g., Gibson et al., 2022; Klapper & Lusardi, 2020; Widjaja et al., 2020; Zeka & Veri, 2022). Evidence also suggests that financial knowledge developed through schooling and family influence promotes persistent positive financial behaviours and broader economic well-being (Amagir et al., 2022; Batty et al., 2015; Fan & Chatterjee, 2018). Consistent with the influence of family and broader social groups on individuals’ behaviours, the family financial socialisation theory and social cognitive theory help explain these findings and support the view that embedding a culture of sound financial management practices across different life stages and within community settings strengthens the basis for lasting sound financial decision-making. Continuity theory further reinforces this position by suggesting that future behaviours are strongly influenced by experiences acquired during early life stages.

Financial knowledge alone does not ensure rational financial behaviour, effective financial management, or greater use of financial instruments (Bapat, 2020; Polishchuk et al., 2023; Uy et al., 2024). Friedline and West (2016) argue that interventions should move beyond financial education and inclusion toward the development of financial capability, encompassing knowledge, skills, and attitudes (Białowolski et al., 2021; Lučić et al., 2023). This also requires awareness of psychological factors, such as biases that influence saving and debt decisions (Ananda et al., 2024; Castro-González et al., 2020; Gonzalez, 2023; Salas-Velasco, 2024; Steinert et al., 2018). Consistent with the theoretical framework in Figure 1, psychological dimensions of finance and psychodynamic consumer theories suggest that analysing financial behaviour solely through rationality overlooks the “normal” nature of individuals, whose decisions are often influenced by instinctive and emotional factors.

Agunsoye and James (2024) suggest that reducing socioeconomic inequalities may be more effective than financial education alone for improving well-being and financial decision-making. Evidence from Kaiser and Menkhoff (2022) and Potocki (2019) further suggests that FL without a sufficiently robust economic foundation may merely camouflage financial decision-making challenges in the short term. These findings indicate that policymakers should move beyond sporadic FL interventions and instead foster social and economic environments where sound financial practices become part of everyday life from childhood. In line with social cognitive theory, individuals socialised within such environments are more likely to develop positive saving and debt behaviours than those exposed only occasionally to corrective financial training after financial difficulties emerge.

A focused examination of developing economies shows that, while Asian research has for a relatively long time incorporated the interaction between FL and BF in analysing saving and debt decisions, studies in African economies have mainly emphasised FL training programmes as solutions for effective household financial management (e.g., Abebe et al., 2018; Kaiser & Menkhoff, 2022; Owusu et al., 2025; Sayinzoga et al., 2016). These programmes were commonly implemented through intervention and longitudinal approaches (e.g., Kaiser & Menkhoff, 2022; Steinert et al., 2018) and generally produced positive outcomes. However, they also delayed the incorporation of BF factors, as FL alone was often considered sufficient for sound financial behaviour. Consistent with the theory of bounded rationality, Sommer et al. (2023) and Carpena et al. (2019) argue that integrating FL and BF helps bridge the gap between financial knowledge and behavioural transformation required for sound financial decision-making.

3.1.2. The Impact of Behavioural Biases on Saving and Debt Behaviours

Behavioural biases are commonly associated with unsound financial decisions, although some biases, such as overconfidence, may positively affect financial behaviour and well-being (Lind et al., 2020). Evidence also suggests that risk perception, risk tolerance, and herding bias among individuals with high FL support retirement saving decisions (Nguyen et al., 2022; Harahap et al., 2022). In debt management, heuristics may function as efficient decision-making aids, especially for individuals with low confidence in digital financial tools (Shefrin & Nicols, 2014; Gärtner et al., 2023).

The relationship between FL and saving behaviour is strongly influenced by risk aversion, which may act directly or as a moderating factor (Ananda et al., 2024; Sekita et al., 2022). Wagner and Walstad (2023) argue that higher risk aversion leads many women to adopt more cautious saving and debt decisions, thereby limiting their engagement in wealth-accumulation behaviours. Consistent with the framework in Figure 1, personality traits and perceived control—the latter being a key element of the theory of planned behaviour—help explain the balance between personal instincts, behavioural anchoring (Corneille et al., 2021; Foltice et al., 2018), individuals’ fear or tolerance of financial risk (Wang, 2023), and the ability to adopt saving and debt behaviours grounded in rationality, with a reasonable expectation of future financial well-being.

Regarding debt behaviour, Wang (2023) finds that higher risk tolerance increases the use of payday loans and other alternative financial services. From the emotional perspective of gains and losses implicit in prospect theory, such behaviour may reflect the extent to which individuals perceive and assume financial outcomes when making debt decisions. Although Wang’s (2023) findings reinforce the importance of FL in limiting excessive debt and default behaviour (Chotewattanakul et al., 2019; Thomas et al., 2023), the psychological dimension of finance (Statman, 2019) suggests that these outcomes may also represent normal financial experiences capable of generating lessons for future sound decision-making.

As noted above, although more prominently in Asia, research in developing economies has increasingly examined the interaction between FL and BF, especially behavioural biases such as risk tolerance, self-control, and financial (over)confidence (e.g., Hadianto et al., 2023; Harahap et al., 2022; Nguyen et al., 2022; Pardo-Piñashca, 2024). These behavioural dimensions significantly influence saving and debt behaviours by either reinforcing or weakening the effects of FL. While self-control is generally linked to better saving behaviour, overconfidence and high risk tolerance may encourage excessive borrowing and poor financing choices. These findings support integrating behavioural biases into FL initiatives, particularly in developing economies where structural constraints may further amplify their effects on financing decision-making.

3.1.3. Exogenous Factors Influencing Sound Saving and Debt Behaviours

Sinnewe and Nicholson (2023) show that contextual conditions and exposure to financial difficulties influence young people’s financial habits more strongly than subjective FL or financial confidence (Avdeenko et al., 2019; Białowolski et al., 2021). They also find that healthy relationships encourage a future-oriented outlook and greater engagement with financial matters.

Combined with family emotional support, financial skills, and confidence, the factors above strengthen individuals’ capacity for sound saving and debt behaviours (Steinert et al., 2020; Tomar et al., 2021), contributing to future well-being and reducing future regret from insufficient savings (Börsch-Supan et al., 2023). In this regard, image theory, contrasting with the foundations of economic rationality, together with family financial socialisation theory and social cognitive theory, supports the view that financial well-being is not built exclusively through financial discipline, but also through personal, family, and social values that shape saving and debt behaviours aligned with future financial well-being.

Materialism has emerged as a prominent factor in studies conducted in developing economies (e.g., Azma et al., 2019; Flores & Vieira, 2014; Thomas et al., 2023), where lower social development is linked to conspicuous consumption and identity- and emotion-driven behaviour (Hadianto et al., 2023). These tendencies may lead credit users to overlook rational and behavioural considerations, thereby increasing financial vulnerability (Bacha & Azouzi, 2019; Hadianto et al., 2023), though they may also be understood through a social identity theory perspective on belonging. Strengthening social support, emotional well-being, and future-oriented outlooks may therefore promote healthier saving and debt behaviours among individuals in developing economies.

BF has emerged to challenge the view that sound financial decisions rely on rigid models or complex calculations, emphasising the role of human behaviour instead. Statman (2019) argues that individuals should be regarded as normal rather than strictly rational or irrational, with decisions shaped by everyday social contexts; even when suboptimal, such decisions are not inherently abnormal but reflect the complexity and unpredictability of human life.

3.2. Methodological Approaches and Data Collection Methods

To address the second research question, the studies were grouped according to the methodologies employed. Four main categories were identified: (1) quantitative approaches using questionnaires for data collection; (2) qualitative approaches based on interviews; (3) a hybrid approach combining quantitative and qualitative methods; and (4) literature reviews. Figure 6 presents the distribution of these methods within the sample.

The quantitative approach, based on questionnaire data, was employed in 89.91% of the studies in the sample and in 95% of those conducted in developing economies, confirming the prevalence of positivist research in economics and business (Armstrong et al., 2022). Only four articles (3.67%) adopted a qualitative approach based on interviews, and only one study (Steinert et al., 2020) combined both methodological approaches.

Among the studies employing quantitative approaches with questionnaires as the data collection method, a further distinction was made between: (1) those conducting cross-sectional experiments and simulations of decision-making scenarios; and (2) those undertaking longitudinal experiments and interventions, typically involving training provided to respondents to assess its effects. In addition, although limited in number, qualitative and hybrid approaches are recommended, as they enable a deeper examination of individuals’ financial behaviour (Cwynar, 2022). Figure 7 and Figure 8 present an integrated overview of studies using these three approaches, which are considered more engaging and have a relatively greater impact (Agunsoye & James, 2024; Lučić et al., 2023).

The distinction within questionnaire-based quantitative studies is relevant, as intervention, experimental, and longitudinal approaches (code B2 = 14.68% of all articles and 17.50% of articles in developing economies) indicate greater researcher engagement and practical relevance. This responds to calls in the literature for more participatory and longitudinal studies involving closer interaction between researchers and participants (e.g., Castro-González et al., 2020; Cwynar, 2022; Shen, 2014; Wann et al., 2023).

From a continental comparative perspective, evidence in Figure 7 indicates that most studies were conducted in African countries (six in total), suggesting a high level of engagement among researchers and participants in contexts where the scarcity of effective financial decision-making tools is more pronounced (Abebe et al., 2018; Steinert et al., 2018). Figure 8 further shows that these approaches have gained prominence over the years, with evidence that even simple financial training interventions, such as reminder messages, can improve saving and debt behaviours (Sayinzoga et al., 2016; Abebe et al., 2018; Kaiser & Menkhoff, 2022).

An additional analysis examines the originality of questionnaire-based data. A subset of studies relied on data from surveys previously conducted by public institutions and market research organisations. Accordingly, studies using questionnaires as the data source were disaggregated to distinguish between those based on primary data and those drawing on secondary databases provided by such entities. Figure 9 presents the number of studies within this classification and their distribution across countries.

The USA accounts for most studies using non-original questionnaires, reflecting the existence of well-established database infrastructures that facilitate scientific research. However, it may also discourage the adoption of interventionist approaches, which are considered particularly relevant for promoting changes in financial behaviour due to the engagement they foster between researchers and target groups (Abebe et al., 2018; Cwynar, 2022). Therefore, an overreliance on secondary data may constrain context-specific insights, highlighting the need to complement such data with primary, intervention-based research designs, as predominantly observed in studies conducted in developing economies.

3.3. Geographical Incidence

To address the third research question, we identified the countries that comprised the empirical field of the studies in the sample and grouped them by continent. It is important to note that this classification refers to the location of the empirical application rather than the authors’ country of origin. Table 1 presents this information under code C (geographical incidence by continents and countries), while Figure 10 provides a visual representation.

The American continent, represented in the sample by studies conducted in the USA, Canada, Brazil, and Peru, shows a strong concentration in the USA (30 articles, corresponding to 27.52% of the total sample), making it the most studied context. Europe and Asia follow, with 27 and 26 articles, respectively, while Africa and Oceania (represented solely by Australia) are the least represented, with 12 and five articles, respectively. The economic components within the sociodemographic factors illustrated in Figure 1 tend to be more favourable in developed economies, which, in turn, attract greater research attention and help explain the observed geographical distribution.

The predominance of studies conducted in the USA and Europe is not unexpected, as these regions comprise many of the world’s most developed economies and host a large proportion of research activity. However, the relatively high representation of studies in Asia—closely approaching that of Europe—may be considered less anticipated, particularly given the historical dominance of research in developed economies. Prior studies conducted in developed contexts (e.g., Castro-González et al., 2020; Shen, 2014) have recommended greater attention to emerging and developing regions. The growing representation of Asian countries, many of which are emerging or developing economies, may therefore reflect the increasing implementation of such recommendations.

Focusing specifically on developing economies, the African continent appears underrepresented, with only 12 studies, corresponding to 11.01% of the total sample. Half of these studies were conducted in a single country—South Africa (six studies)—indicating that many African countries remain promising fields for further research. Reyers (2019) and Sayinzoga et al. (2016), in studies conducted within African contexts, emphasise the importance of interventions to guide financial decision-making in countries where the majority of the population has very limited resources. Such interventions aim to address gaps left by the vulnerable socioeconomic context, which constrain individuals’ capacity to manage already scarce financial resources.

Although the number of studies in Asia is relatively higher, research is concentrated in just four countries—Indonesia, India, Malaysia, and Thailand, all classified as developing economies—which account for 17 of the 26 articles. Similar to the African continent, many Asian countries remain underexplored or entirely unexamined, most of which are developing economies. Consequently, these countries are prime candidates for future research examining the effects of FL and BF on saving and debt behaviours (Ananda et al., 2024; Shen, 2014).

3.4. Suggestions for Future Research

In this subsection, we first present the key suggestions from the studies in our sample (

Table 2. Future research agenda emerging from sample studies.

Suggestions	Related Citations
Conduct studies in underexplored fields, particularly in emerging and developing countries.	Ananda et al. (2024); Bapat (2020); Grohmann (2018); Sayinzoga et al. (2016).
Carry out longitudinal studies, experiments, and case studies, collecting data through interviews, observation, or hybrid methods to promote the greatest possible interaction between the researcher and the individuals investigated and to capture them in the greatest depth. From the perspective of the cumulative effect of multiple interventions across a lifespan, understand individuals’ saving and debt behaviours.	Batty et al. (2015); Białowolski et al. (2021); Castro-González et al. (2020); Cwynar (2022); Harahap et al. (2022); Lučić et al. (2023); Shen (2014); Steinert et al. (2020); van Deventer (2020); Wann et al. (2023).
Carry out studies that clearly differentiate subjective financial literacy (perceptions, self-confidence, or financial confidence) from objective financial literacy (reality).	Białowolski et al. (2021); Chotewattanakul et al. (2019); Cwynar (2022); Wann et al. (2023).
Carry out studies across different groups and segments (from children to adults), whether in a complementary or comparative way, and favour collaboration among social groups and multidisciplinary cooperation across areas.	Amagir et al. (2022); Lučić et al. (2023); Pangestu and Karnadi (2020); Steinert et al. (2020); Tomar et al. (2021); Wagner and Walstad (2023).
Conduct studies that include psychological, cognitive, physical, mental, and social well-being as variables to analyse individuals’ saving and debt behaviours.	Bapat (2020); Hauff and Nilsson (2020); Lučić et al. (2023); Shen (2014); Steinert et al. (2020); Tomar et al. (2021).

Source: Author’s own work.

), focusing only on the most significant suggestions rather than those that are relatively common or repetitive, such as changes to samples, countries, or variables. We then provide our own suggestions, along with supporting justification.

Our first suggestion is to examine FL and BF in relation to saving and debt behaviours in African countries, employing the different approaches outlined under code A in Table 1. This recommendation is supported by the geographical distribution of studies in our sample and aligns with the prior literature, particularly Ananda et al. (2024) and Sayinzoga et al. (2016), who specifically identify African countries as largely underexplored contexts in research on interconnections between FL and BF.

Second, we suggest examining knowledge transfer from FL and BF training, especially in rural, community-based settings. This recommendation is supported by evidence from Sayinzoga et al. (2016) that shows no spillover of knowledge within communities. Strengthening such transfer could support communal societies where daily life and economic activity are closely linked, particularly in rural Africa. According to Steinert et al. (2020), mobilising social cooperation between individuals who have benefited from interventions and those who have not may enhance the effectiveness of poverty-reduction programmes, including initiatives in education and financial inclusion for economically vulnerable social groups.

Third, we suggest examining debt behaviours and motivations in urban areas of developing economies, where social status often outweighs rational considerations. This recommendation is supported by Hadianto et al. (2023), who found that women’s credit card use is driven by identity and emotional status, leading to overspending. This perspective aligns with Morris et al. (2023), who suggest that research on household debt would benefit from a deeper examination of lifestyle and income factors, as perceived instant gratification appears to be a key driver of financial decisions.

Finally, we suggest examining the FL- and behaviour-motivated use of informal debt in developing economies. This recommendation is supported by evidence showing that households often prefer informal debt to formal and emerging debt, and more advantageous loans, which offer lower interest rates and potential tax benefits (Potocki, 2019; Sarpong-Kumankoma, 2023; Sommer et al., 2023). Given the limited development of financial systems in many developing economies, and drawing on financial inclusion assessment tools such as the OECD (2022), studying informal debt in these contexts appears particularly valuable. This should be complemented by considering overconfidence in debt management and financial knowledge, as Wann et al. (2023) link overconfidence to greater use of alternative financial services.

4. Conclusions

Financial literacy (FL) and behavioural finance (BF) have emerged as central determinants of individuals’ and households’ saving and debt behaviours. Although research on these topics has expanded over the past fifteen years, the evidence remains conceptually dispersed and methodologically heterogeneous, underscoring the need for an integrative synthesis. Guided by a theoretical framework that combines rational and behavioural determinants of financial decision-making, this S-SLR examined 109 studies from Scopus and Web of Science to map how FL and BF have been linked to saving and debt behaviours across thematic approaches, methodological traditions, and geographical contexts.

Our synthesis reveals that existing research—predominantly quantitative and concentrated in the United States, selected European countries, and a limited number of developing Asian economies—produces mixed findings regarding the influence of FL and behavioural factors on financing behaviours. While FL alone appears insufficient to fully explain saving and debt decisions, the interaction between FL and BF provides a more comprehensive and nuanced understanding of these behaviours. This is particularly evident in studies of saving behaviour, as it is the most frequently examined outcome. At the same time, evidence from developing economies suggests that FL interventions can help individuals navigate structural economic constraints and improve everyday financial practices, especially in contexts where behavioural biases and environmental pressures interact strongly.

Taken together, these findings highlight that financing decision-making is inherently complex and cannot be adequately explained by isolated constructs. Instead, it requires recognising the integrative and complementary roles of FL, BF, and classical and psychodynamic theories of consumer behaviour. This integrative perspective offers a more robust foundation for designing impactful interventions, strengthening researcher–participant engagement, and advancing multidisciplinary research agendas.

The review also identifies several promising directions for future research. Scholars increasingly call for expanding empirical work into emerging and developing economies, where contextual factors may reshape the interplay between FL, BF, and financial behaviours. Methodologically, there is a clear need for intervention-based, longitudinal, and experimental designs capable of capturing causal mechanisms and behavioural dynamics over time. Conceptually, future studies would benefit from incorporating psychological variables, underexplored motivations, and socio-cultural influences that shape financial choices. Moreover, the research gaps identified—particularly those related to knowledge-transfer mechanisms and the processes of debt acquisition and management in developing economies—may be especially well addressed through frameworks that integrate FL and BF, as these approaches consider a broader range of determinants than conventional policy-oriented models. Overall, this review advances the field by demonstrating that the relationship between FL, BF, and financing behaviours is best understood through a multidimensional and theoretically integrated lens. By synthesising dispersed evidence and identifying key conceptual and methodological gaps, the study provides a foundation for future research capable of generating deeper insights into how individuals make saving and debt decisions in diverse economic and cultural contexts.

Contribution and Limitations

This S-SLR synthesis study links FL and BF in relation to saving and debt behaviours, representing a novel focus compared with existing reviews that address FL and BF separately and/or that centre on investment decisions (e.g., Badola et al., 2023; Bhattacharjee & Singh, 2017; Silva et al., 2023). Our findings, supported by those of several authors cited in Table 2 (e.g., Ananda et al., 2024; Shen, 2014; Wagner & Walstad, 2023), highlight strong research potential in examining the interaction between FL and BF. The in-depth analysis of developing economies proved particularly valuable, revealing that FL training programmes, often combined with highly engaging research designs such as intervention and experimental approaches (Harahap et al., 2022; Lučić et al., 2023), are relatively well established in contexts where support for sound decision-making is most needed due to structural financial vulnerabilities. However, in many of these countries, there remains a lack of research integrating FL with BF, which would provide a more comprehensive understanding of financial decision-making.

Despite these contributions, the study has limitations. First, the S-SLR was restricted to two databases—Scopus and Web of Science—and did not account for journal quality metrics when selecting sample articles. Second, although the initial screening relied on database tools, the final selection was based on the authors’ content assessment, introducing a degree of subjectivity. Third, 13 articles met the inclusion criteria based on their abstracts but could not be accessed due to restrictions. This number was initially higher; however, efforts such as rerouting through academic contact networks with different institutional library access and direct email requests to authors enabled the retrieval of some articles that would otherwise have been inaccessible. These limitations may have led to the exclusion of relevant studies that could have strengthened this S-SLR’s findings.