Digital Financial Inclusion in South African Townships: Qualitative Interview Data

South African township communities are the focus of this qualitative dataset on digital financial inclusion. The data was created by Sean Nkosi and last updated on May 5, 2026, investigating barriers and adaptive strategies for fintech adoption. It is based on thematic analysis of semi-structured interviews, examining factors like digital literacy, trust, and usage behaviors.

Use Cases

• Analyzing barriers to fintech adoption based on themes like limited digital literacy and high data costs mentioned in the description.
• Modeling hybrid financial behaviors based on the described adaptive strategies of combining cash with selective digital use.
• Studying trust and security concerns in digital finance based on described issues like scams and unauthorized deductions.
• Investigating the socio-technical drivers of technology acceptance based on the application of the UTAUT framework mentioned in the description.

Strengths

• Data file size is 853.9 KB, indicating a contained and likely focused dataset.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse and adaptation.
• Based on a described qualitative methodology using semi-structured interviews and thematic analysis.

Limitations

• Row count is unknown, which may limit suitability assessment for quantitative tasks.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset's 853.9 KB size suggests a limited scope, likely containing summary or coded qualitative data rather than large-scale survey results.

Provenance

Source

Sean Nkosi via figshare

Collection Method

Qualitative thematic analysis of semi-structured interviews, drawing on the FSCA’s Digital Financial Inclusion Trends Study.

Freshness

Last updated 2026-05-05 11:18:07

Geography

South Africa, focusing on townships