Shaping digital financial wellbeing through digital financial literacy and financial inclusion: Evidence from gender and residential groups in India

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Type of the article: Research Article

Abstract
Financial inclusion has become a critical driver of inclusive growth; however, disparities in digital access, literacy, and usage limit improvements in financial well-being, particularly across gender and residential groups. This study examines how digital financial literacy influences digital financial inclusion and financial wellbeing among digital consumers in the Delhi National Capital Region of India. This study employed an online structured survey administered between August and October 2025, yielding a sample size of 431. Using structural equation modelling, the results indicate that infrastructure accessibility (β = 0.521), knowledge and awareness (β = 0.379), digital financial skills (β = 0.277), motivation and attitude (β = 0.223), and social and institutional support (β = 0.215) significantly enhance digital financial literacy (all p < 0.001). Digital financial literacy strongly influences digital financial inclusion (β = 0.684, p < 0.001) and financial wellbeing (β = 0.509, p < 0.001), whereas digital financial inclusion further improves financial wellbeing (β = 0.479, p < 0.001). The indirect effect of digital financial literacy on financial wellbeing through digital financial inclusion is also significant (β = 0.328, p < 0.001). Necessary condition analysis confirmed that all five antecedents are essential for achieving higher digital financial literacy levels. Descriptive and ANOVA analyses reveal significant mean-level differences across gender and residential groups, providing evidence that these demographic factors condition the digital financial outcomes. The findings highlight that digital financial literacy and infrastructure are central to enhancing financial wellbeing, with implications for the design of gender-sensitive and context-responsive financial inclusion policies.

Acknowledgments
The Institutional Human Ethics Committee of the Central university of Jammu, with the reference number CUJ/IHEC/11, granted ethical approval for the study.

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    • Figure 1. Theoretical framework
    • Figure 2. Structural model
    • Table 1. Demographic characteristics
    • Table 2. Descriptive statistics
    • Table 3. Construct reliability and validity
    • Table 4. Discriminant validity assessment (HTMT and Fornell-Larcker criterion)
    • Table 5. Model fit summary
    • Table 6. Structural model assessment
    • Table 7. NCA results and interpretation
    • Table 8. Mean assessment of all factors across gender categories
    • Table 9. One-way ANOVA assessment of all factors across gender categories
    • Table 10. Mean assessment of all factors across residential status
    • Table 11. One-way ANOVA assessment of all factors across residential status
    • Table A1. Questionnaire items
    • Data curation
      Parveen Yadav, Saurav Meena, Arun Yadav
    • Investigation
      Parveen Yadav, Rohit Bhagat, Arun Yadav
    • Methodology
      Parveen Yadav, Vinay Kumar, Saurav Meena
    • Writing – original draft
      Parveen Yadav, Saurav Meena, Sumanjeet Singh
    • Conceptualization
      Vinay Kumar, Saurav Meena, Sumanjeet Singh
    • Supervision
      Vinay Kumar, Sumanjeet Singh, Rohit Bhagat
    • Writing – review & editing
      Vinay Kumar, Rohit Bhagat, Arun Yadav
    • Formal Analysis
      Sumanjeet Singh, Rohit Bhagat, Arun Yadav