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on Financial Literacy and Education |
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Issue of 2026–04–20
five papers chosen by Viviana Di Giovinazzo, Università degli Studi di Milano-Bicocca |
| By: | Lacaza, Rutcher M.; Pesa, Nikka C.; Agner, Mary Grace R. |
| Abstract: | This paper examines how digital financial platform engagement influences financial inclusion in the Philippines and explores how financial institutions are deploying artificial intelligence (AI) in enhancing these platforms. It combines nationally representative data from the World Bank Global Findex (2021), institutional indicators from the International Monetary Fund (IMF) Financial Access Survey (2016–2024), and qualitative insights from financial institutions and policy experts. From the demand side, a Digital Financial Engagement Index was constructed based on individuals’ usage of mobile payments, online banking, and digital financial services. Results reveal that digital financial engagement is a strong and consistent determinant of financial inclusion: individuals who actively use digital financial platforms are significantly more likely to own and use formal financial accounts. However, several barriers persist. The lack of money, high perceived costs, documentation issues, and low trust remain key constraints among Filipino adults, particularly among low-income groups. From the supply side, institutional data from the IMF Financial Access Survey (2016–2024) and insights from Key Informant Interviews (KIIs) reveal that financial infrastructure has expanded moderately. While AI adoption remains nascent and largely concentrated among large, digitally advanced financial institutions, AI technologies such as fraud detection, credit scoring, and chatbots are increasingly embedded in the digital platforms where consumers transact. In contrast, smaller cooperatives and savings and loan associations continue to face structural and resource-related barriers to adoption. The convergence of demand- and supply-side evidence highlights that digital financial engagement serves both as a driver and an indicator of financial inclusion, while AI adoption within these platforms has the potential to further enhance access, security, and user experience. Overall, this study provides new empirical evidence that digital financial engagement significantly enhances financial inclusion in the Philippines. The study also documents how financial institutions are strategically deploying AI within these digital platforms, providing insights for responsible AI adoption that can support inclusive financial services. By strengthening digital infrastructure, promoting financial and digital literacy, and ensuring responsible AI adoption, the Philippines can transform digital financial platforms into a true catalyst for inclusive and sustainable growth. Comments to this paper are welcome within 60 days from the date of posting. Email publications@pids.gov.ph. |
| Keywords: | digital financial engagement, artificial intelligence, financial inclusion, digital platforms, Philippines |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:phd:dpaper:dp_2026-03 |
| By: | Scott A. Wolla |
| Abstract: | Teaching economic reasoning boosts financial literacy, helping students make smarter personal finance decisions using tools like the ‘PACED’ model. |
| Keywords: | financial literacy; economic reasoning; decisionmaking; personal finance |
| Date: | 2026–04–08 |
| URL: | https://d.repec.org/n?u=RePEc:fip:l00100:103014 |
| By: | M. Tedde |
| Abstract: | The inclination to guess rather than to admit a lack of knowledge by responding "Don't know" can explain why investors fail the surveys intended to assess their financial competence. Using MiFID test answers and trading data, we investigate whether investors who admit their ignorance and select the "Don't know" answers trade less, a!ord lower transaction costs, and achieve better (net) returns than investors who prefer to guess and select the wrong answers. Additionally, we show that among investors who fill in the MiFID test multiple times, those who select the "Don't know" answers trade less, pay lower transaction costs and perform better than the guesser investors. |
| Keywords: | D53;D91;G11;G41;G53 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:cns:cnscwp:202601 |
| By: | Tabea Bucher-Koenen; Luisa Wallossek; Joachim Winter |
| Abstract: | Default settings strongly increase pension enrollment, especially when savings incentives are high and choices are complex. We show that the effect is weaker when incentives are low, options are simple, and opting out is easy. We study the nationwide introduction of auto-enrollment for low-income employees in Germany's public pay-as-you-go pension system. We find that automatic enrollment raises participation by 23 percentage points, though most individuals actively opt out. Linking administrative and survey data shows that the default effect is stronger when enrollment incentives are higher and among individuals who lack knowledge of their enrollment status. |
| Keywords: | default-setting, auto-enrollment, pensions, financial literacy |
| JEL: | D14 H55 J26 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12605 |
| By: | Dikgang, Johane; Magambo, Isaiah; Amadu, Festus O.; Magnier, Alexandre |
| Abstract: | During economic crises, urban policymakers must assess whether housing assistance helps prevent evictions. This study explores the link between housing assistance and eviction risk and how household financial capacity influences this relationship. Using 207, 203 observations from the Understanding America Study during COVID-19 and applying recursive bivariate probit models with instrumental variables, we find that housing assistance correlates with a 4.3% decrease in the likelihood of eviction (a 15.6% relative reduction). Notably, among households with credit access, this effect increases to 6.2%, or 44% more than the overall average. We observe a notable inverted- U pattern: households with one to two credit sources see reductions over 39%, whereas those with three or more sources experience much smaller effects, around 4.1%, or a nearly tenfold difference. This challenges the idea that greater financial access always enhances outcomes. The mechanism analysis suggests that this pattern reflects financial stability rather than over-leveraging: households with three or more credit sources tend to be more creditworthy and less dependent on assistance. The results hold across various estimation methods. Although our instrumental variable approach has limitations, the consistent heterogeneity patterns across multiple strategies increase confidence in the finding that housing assistance and moderate credit access work well together. These insights imply that housing assistance programs could be more effective when combined with financial inclusion efforts that focus on credit quality over quantity, with important implications for preventing urban displacement during economic downturns. |
| Keywords: | housing assistance, eviction prevention, financial capacity, instrumental variables, urban policy |
| JEL: | I38 R21 R28 C26 H53 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1735 |