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on Financial Literacy and Education |
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Issue of 2025–06–23
six papers chosen by Viviana Di Giovinazzo, Università degli Studi di Milano-Bicocca |
| By: | Radic, Ivana; Gardeazabal Monsalve, Andrea |
| Abstract: | This paper examines the transformative potential of blockchain-enabled digital identities in empowering smallholder farmers, with a specific focus on CIMMYT’s initiatives in the Global South. By providing farmers with secure, verifiable credentials and data wallets, these technologies address critical challenges in financial inclusion, supply chain traceability, and data governance. Leveraging case studies from CIMMYT’s partnerships with Bluenumber and Identi, the paper explores the application of blockchain to enhance data ownership, improve market access, and foster transparency within agrifood systems. Findings highlight how digital identities enable farmers to control and monetize their data, access financial services, and comply with traceability standards, thereby strengthening their position in global value chains. Despite significant potential, challenges such as digital literacy gaps, infrastructure limitations, and regulatory disparities persist. The paper concludes with recommendations for scaling these solutions, emphasizing region-specific adaptations, collaborative frameworks, and robust data governance to maximize impact and inclusivity. |
| Keywords: | smallholders; financial inclusion; value chains; blockchain technology; digital divide |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:cgiarp:172557 |
| By: | YANG, ZHANG (Department of Finance and Business Economics, Faculty of Business Administration / Asia-Pacific Academy of Economics and Management, University of Macau); JIANXIONG LIN (QIFU Technology, China); YIHE QIAN (Department of Finance and Business Economics, Faculty of Business Administration, University of Macau); LIANJIE SHU (Faculty of Business Administration , University of Macau) |
| Abstract: | MachiAs a key enabler of poverty alleviation and equitable growth, financial inclusion aims to expand access to credit and financial services for underserved individuals and small businesses. However, the elevated default risk and data scarcity in inclusive lending present major challenges to traditional credit assessment tools. This study evaluates whether machine learning (ML) techniques can improve default prediction for small-business loans, thereby enhancing the effectiveness and fairness of credit allocation. Using proprietary loan-level data from a city commercial bank in China, we compare eight classification models—Logistic Regression, Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, XGBoost, and LightGBM—under three sampling strategies to address class imbalance. Our findings reveal that undersampling significantly enhances model performance, and tree-based ML models, particularly XGBoost and Decision Tree, outperform traditional classifiers. Feature importance and misclassification analyses suggest that documentation completeness, demographic traits, and credit utilization are critical predictors of default. By combining robust empirical validation with model interpretability, this study contributes to the growing literature at the intersection of machine learning, credit risk, and financial development. Our findings offer actionable insights for policymakers, financial institutions, and data scientists working to build fairer and more effective credit systems in emerging markets. |
| Keywords: | machine learning, financial inclusion, small business, China, credit risk assessment |
| JEL: | G21 G32 C53 O16 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:boa:wpaper:202532 |
| By: | Robin Middelanis; Bramka Arga Jafino; Ruth Hill; Minh Cong Nguyen; Stephane Hallegatte |
| Abstract: | Most disaster risk assessments use damages to physical assets as their central metric, often neglecting distributional impacts and the coping and recovery capacity of affected people. To address this shortcoming, the concepts of well-being losses and socio-economic resilience—the ability to experience asset losses without a decline in well-being—have been proposed. This paper uses microsimulations to produce a global estimate of well-being losses from, and socio-economic resilience to, natural disasters, covering 132 countries. On average, each $1 in disaster-related asset losses results in well-being losses equivalent to a $2 uniform national drop in consumption, with significant variation within and across countries. The poorest income quintile within each country incurs only 9% of national asset losses but accounts for 33% of well-being losses. Compared to high-income countries, low-income countries experience 67% greater well-being losses per dollar of asset losses and require 56% more time to recover. Socio-economic resilience is uncorrelated with exposure or vulnerability to natural hazards. However, a 10 percent increase in GDP per capita is associated with a 0.9 percentage point gain in resilience, but this benefit arises indirectly—such as through higher rate of formal employment, better financial inclusion, and broader social protection coverage—rather than from higher income itself. This paper assess ten pol icy options and finds that socio-economic and financial interventions (such as insurance and social protection) can effectively complement asset-focused measures (e.g., construction standards) and that interventions targeting low-income populations usually have higher returns in terms of avoided well-being losses per dollar invested. |
| Date: | 2025–05–21 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11129 |
| By: | Katharina Hartinger (Johannes-Gutenberg University, Germany); Erik Sarrazin (Johannes-Gutenberg University, Germany); David J. Streich (Catholic University Eichstätt-Ingolstadt) |
| Abstract: | Digitalization in banking is leaving elderly clients at risk of losing access to financial services, but little is known about technology adoption at an advanced age. We develop and evaluate training interventions to foster internet banking adoption in a field experiment with more than 25, 000 elderly clients of a large German savings bank, of whom we randomize 333 into training. Our administrative banking panel data allows us to account for selection on observables and assess the sustainability of treatment effects. After the interventions, the share of clients who use internet banking increases by 26 percentage points in the treatment group relative to a matched control group. In terms of sustainable usage, the share of online transactions increases by 13 percentage points and remains elevated four months later. An extensive placebo analysis suggests that as much as 85% of the effect can be causally attributed to the training interventions. We find that training boosts non-technical adoption skills and reduces key adoption barriers. Treatment effects are larger for women and those not in charge of household finances. We further estimate intent-to-treat effects and predict dropout along the entire multi-stage adoption process to shed light on practical considerations when rolling out large-scale technology adoption interventions in this age group. Specifically, we show that the type of training (self-guided versus social learning) impacts dropout differentially despite similar treatment effects overall, with the social learning treatment being more inclusive. |
| Keywords: | technology adoption, internet banking, financial inclusion, digitalization, non-cognitive skills |
| JEL: | O33 G21 I21 J24 D12 D91 C93 |
| Date: | 2025–06–17 |
| URL: | https://d.repec.org/n?u=RePEc:jgu:wpaper:2505 |
| By: | Adeeth Cariappa, Ajjikuttira Girish; Khed, Vijayalaxmi; Singaraju, Niyati; Gartaula, Hom N. |
| Abstract: | This report examines the digital landscape in the Eastern Indian states of Bihar and Odisha, focusing on disparities in digital access, literacy, and technology utilization. Using gender-disaggregated data from 1, 034 households, the findings reveal significant gender, social, and regional inequities. Women, especially from marginalized communities, face reduced access to digital devices, limited operational skills, and low internet usage for agricultural needs. Key barriers include high device costs, limited digital literacy, and inadequate local-language content. Despite challenges, a strong demand for digital skills training emerges, particularly among women and younger populations. The current utilization of mobile internet primarily revolves around communication and entertainment, with minimal use for agriculture-related activities. The report underscores the necessity for tailored digital literacy programs, localized content, and affordable technology to bridge these divides. Addressing these gaps can enhance the adoption of digital tools, fostering inclusive growth and improved agricultural outcomes in the region. |
| Keywords: | technology; rural development; socioeconomic aspects; digital agriculture; India; Southern Asia |
| Date: | 2024–12–11 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:cgiarp:169888 |
| By: | Jalal Moustakim (FSJES - Faculty of Legal, Economic, and Social Sciences of Fes, USMBA - Université Sidi Mohamed Ben Abdellah [Fès]); Mohammed Baaddi (USMBA - Université Sidi Mohamed Ben Abdellah [Fès], FSJES - Faculty of Legal, Economic, and Social Sciences of Fes) |
| Abstract: | This study assesses the impact of digital literacy on employee well-being in the banking sector. Introducing the Digital Literacy Empowerment and Well-being Model (DLEW Model), with psychological empowerment and self-efficacy as mediating variables, and technostress and organizational support as moderators. This study synthesizes existing literature in digital literacy and employee well-being. Theories like Technology Acceptance Model (TAM), Social Cognitive Theory (SCT), and the Job Characteristics Model (JCM) are used. The DLEW Model is used to explain and facilitate the proposed relationships between variables. This model shows that digital literacy enhances employee well-being through a solid psychological empowerment and self-efficacy. Technostress, the stress people feel when using or adopting with new tech, is proposed as moderator variable, to moderate the relationship between digital literacy and psychological empowerment. A factor that might weaken the positive push that digital literacy gives to psychological empowerment. On the other hand, if employees feel the presence of their organizational support, it can be stronger the link between digital literacy and self-efficacy. So, in short, less stress and more support means better digital skill and well-being. Since The DLEW Model is still theoretical, it's important for future research to put it to the test in different types of organizations and industries. We need to know the validity of these propositions and its applicability across various workplace situations. Unlike existing literature, the study makes a unique contribution by proposing a comprehensive theoretical framework, the DLEW Model shows the crucial role of digital literacy in shaping employee well-being and performance. It provides groundwork for future empirical studies. |
| Abstract: | Cette étude évalue l'impact de la littératie numérique sur le bien-être des employés dans le secteur bancaire. Elle introduit le Modèle d'Autonomisation par la Littératie Numérique et le Bien-Être (Modèle DLEW), avec l'autonomisation psychologique et l'auto-efficacité comme variables médiatrices, et le technostress ainsi que le soutien organisationnel comme variables modératrices. Cette recherche synthétise la littérature existante sur la littératie numérique et le bien-être au travail. Des théories telles que le Modèle d'Acceptation de la Technologie (TAM), la Théorie Sociale Cognitive (SCT) et le Modèle des Caractéristiques du Travail (JCM) sont mobilisées. Le Modèle DLEW sert à expliquer et à illustrer les relations proposées entre les différentes variables. Ce modèle montre que la littératie numérique améliore le bien-être des employés grâce à une forte autonomisation psychologique et une auto-efficacité accrue. Le technostress, défini comme le stress ressenti lors de l'utilisation ou de l'adoption de nouvelles technologies, susceptible d'affaiblir la relation positive entre la littératie numérique et l'autonomisation psychologique. En revanche, le soutien organisationnel perçu par les employés peut renforcer le lien entre littératie numérique et auto-efficacité. En résumé, moins de stress et plus de soutien conduisent à de meilleures compétences numériques et à un bien-être accru. Étant donné que le Modèle DLEW reste pour l'instant théorique, il est essentiel que de futures recherches l'évaluent dans divers types d'organisations et de secteurs. Il s'agit de vérifier la validité de ces propositions et leur applicabilité dans différentes situations professionnelles. Contrairement à la littérature existante, cette étude apporte une contribution originale en proposant un cadre théorique complet. Le Modèle DLEW met en évidence le rôle crucial de la littératie numérique dans la construction du bien-être et de la performance des employés, et ouvre la voie à de futures recherches empiriques. |
| Keywords: | Digital Literacy, Electronic banking, Psychological Empowerment, Self-Efficacy, Employee Well-being, Technostress, Motivation |
| Date: | 2025–05–20 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05078258 |