Avalilação PREreview de Beyond Digital Transactions: Explaining the Compliance–Autonomy Gap in Microfinance Borrowers’ Adoption of Digital Financial Services in Jharkhand, India

PREreview: Administrative Friction and the Structural Limits of the Compliance–Autonomy Gap

Reviewer: Julian Rodriguez, Jr., FRSA, MRES, M.ISRM (ORCID: 0009-0007-9332-0140)

Target Preprint: Beyond Digital Transactions: Explaining the Compliance–Autonomy Gap in Microfinance Borrowers’ Adoption of Digital Financial Services in Jharkhand, India (Alok Kumar Yadav, 2026, DOI: 10.20944/preprints202609.0486.v1)

1. Summary & Core Contribution

The author addresses a critical, frequently obscured vulnerability in digital financial inclusion metrics: the disconnect between mandatory transactional compliance and genuine user autonomy. Evaluating 663 active microfinance borrowers in Jharkhand, India, Yadav demonstrates a stark empirical disparity—84.9% adoption for mandatory digital loan repayments versus only 12.1% for autonomous fund transfers. The introduced Compliance–Autonomy Gap and Trust-Enabled Phygital Adoption Framework (TEPAF) provide an essential empirical critique against treating top-down transaction volume as proxy evidence for broad-based digital financial capability.

2. Systems-Level Analysis & Technical Considerations

From an administrative systems and institutional risk perspective, the empirical findings reveal three primary structural mechanics:

• Algorithmic Deference in Supervisory Oversight: Institutional oversight bodies routinely rely on aggregate digital transaction counts to gauge inclusion metrics. This creates a state of Algorithmic Deference, where regulators assume downstream user capability based on mandatory digital footprints while remaining blind to structural coercion and administrative friction at the local execution layer.

• Trust Asymmetry as Operational Friction: The empirical identification of high MFI trust ($M = 4.37$) paired with low technology trust ($M = 3.38$) highlights a fundamental operational barrier. When automated platforms replace human intermediaries without establishing underlying system confidence, execution gatekeepers default to enforcing institutional compliance rather than enabling autonomous user capacity.

• Econometric Integrity & Model Distortion: The author transparently identifies severe multicollinearity and heteroscedasticity within the reported OLS regression model. In regulatory policy design, relying on linear coefficients derived under high multicollinearity risks generating distorted intervention strategies.

3. Recommendations for Future Iterations

1. Econometric Re-estimation: The author should consider re-estimating the empirical data using robust standard errors, structural equation modeling (SEM), or regularized regression techniques (e.g., Ridge/LASSO) to resolve coefficient-level distortion caused by multicollinearity.

2. Integration of Intent Metrics: Future iterations of the TEPAF framework should incorporate structural audit indicators that distinguish whether software architecture is engineered primarily for institutional compliance collection or for user-side financial self-determination.

3. Supervisory Metric Realignment: Financial inclusion regulators must update public policy frameworks to track transaction diversity and operational independence rather than raw transaction volume, preventing artificial inflation of financial inclusion data.

Conclusion

Yadav’s paper offers a timely and vital empirical warning for digital finance policy. Distinguishing between forced transactional compliance and autonomous engagement is necessary for designing administrative frameworks that support genuine socio-economic resilience.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they used generative AI to come up with new ideas for their review.