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August 22, 2026
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August 22, 2026
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August 22, 2026
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August 21, 2026
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Capacity-based taxation targets undeclared pouch-packing machinery used for clandestine pan masala and tobacco production and untaxed clearances.
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India’s DBT: Boosting Welfare Efficiency - Report Reveals ₹3.48 Lakh Crore in Savings and 16-Fold Increase in Beneficiaries.

April 21, 2025

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Introduction

India’s Direct Benefit Transfer (DBT) system has helped the country save an estimated ₹3.48 lakh crore till 2024 by plugging leakages in welfare delivery, according to a new quantitative assessment by the BlueKraft Digital Foundation. The report also finds that subsidy allocations have been halved from 16 percent to 9 percent of total government expenditure since the implementation of DBT, reflecting a major improvement in the efficiency of public spending.

The assessment evaluates data from 2009 to 2024 to examine the impact of DBT on budgetary efficiency, subsidy rationalisation, and social outcomes. It shows how the shift from paper-based disbursals to direct digital transfers has ensured that public funds reach the people they are meant for. One of the key features of DBT is the use of the JAM trinity, which stands for Jan Dhan bank accounts, Aadhaar unique ID numbers and mobile phones. This framework has enabled targeted and transparent transfers on a massive scale.

To capture the full extent of its impact, the report introduces a Welfare Efficiency Index. This index combines fiscal outcomes such as savings and reduced subsidies with social indicators like the number of beneficiaries reached, offering a clear picture of how well the system is working. The index has risen nearly threefold from 0.32 in 2014 to 0.91 in 2023, reflecting a sharp increase in both effectiveness and inclusion.

At a time when governments across the world are rethinking how to strengthen social protection, the DBT model presents valuable lessons in aligning financial prudence with equitable governance.

Key Findings

Budgetary Allocation Trends

The data on subsidy allocations reveals a significant shift post-DBT implementation, highlighting improvements in fiscal efficiency despite a surge in beneficiary coverage.

  • Pre-DBT Era (2009–2013): Subsidies averaged 16% of total expenditure, amounting to ₹2.1 lakh crore annually, with considerable leakages in the system.
  • Post-DBT Era (2014–2024): Subsidy expenditure decreased to 9% of total expenditure in 2023-24, while beneficiary coverage surged 16-fold from 11 crore to 176 crore.
  • COVID-19 Outlier: A temporary spike in subsidies occurred during the 2020–21 fiscal year due to emergency fiscal measures. However, efficiency rebounded following the pandemic, further validating the system's long-term effectiveness.

Subsidy Allocation Trends (2009-2024)

The reduction in subsidy burden, despite a significant increase in coverage, underscores DBT’s role in optimising fiscal allocations. By eliminating ghost beneficiaries and middlemen, the system redirected funds to genuine recipients without proportional increases in the budget.

Sectoral Analysis

A detailed breakdown of sector-specific impacts shows how DBT has particularly benefited high-leakage programmes.

  • Food Subsidies (PDS): ₹1.85 lakh crore saved, accounting for 53% of total DBT savings. This was largely due to Aadhaar-linked ration card authentication.
  • MGNREGS: 98% of wages were transferred timely, saving ₹42,534 crore through DBT-driven accountability.
  • PM-KISAN: ₹22,106 crore saved by deleting 2.1 crore ineligible beneficiaries from the scheme.
  • Fertilizer Subsidies: Sales of 158 lakh MT of fertiliser were reduced, saving ₹18,699.8 crore through targeted disbursement.

Sectoral Impact Analysis

These sector-specific savings highlight DBT’s disproportionate impact on high-leakage programs, such as food subsidies and wage schemes like MGNREGS. The system’s role in biometric authentication and direct transfers has been crucial in improving efficiency and curbing misuse.

Correlation and Causality Findings

The correlation analysis further underscores the effectiveness of DBT in improving welfare delivery.

  • Strong Positive Correlation (0.71): There is a strong positive correlation between beneficiary coverage and DBT savings, signifying that as coverage expanded, savings increased.
  • Negative Correlation (-0.74): There is a significant negative correlation between subsidy expenditure as a percentage of total expenditure and welfare efficiency, highlighting the reduction in waste and leakages facilitated by DBT.

Heat-map showing correlation between key variables

The heat-map analysis quantifies the relationship between budget allocations, DBT savings, and welfare efficiency. As DBT savings increased, subsidy allocations decreased, demonstrating that DBT improved targeting while reducing leakages. This enabled the government to expand welfare programs, reaching more beneficiaries without increasing fiscal outlays. The inverse relationship between subsidy expenditure and efficiency challenges critiques of “declining welfare spending” and affirms DBT’s role as a powerful tool for fiscal optimisation.

Welfare Efficiency Index (WEI)

As part of the methodology for assessing the impact of the Direct Benefit Transfer (DBT) system, the Welfare Efficiency Index (WEI) was developed as a composite metric to measure efficiency gains across various dimensions. The WEI comprises three weighted components:

DBT Savings (50% weight): This component captures the direct reduction in leakage, normalised against the maximum observed savings of ₹3.48 lakh crore.

 

Subsidy Reduction (30% weight): Measures the decline in subsidy expenditure as a percentage of the total national budget.

 

Beneficiary Growth (20% weight): Assesses the expansion in the number of beneficiaries, adjusted for population growth.

The rise in the WEI from 0.32 in 2014 to 0.91 in 2023 quantifies systemic improvements, emphasising that efficiency gains stem from multi-dimensional factors—not merely budget cuts. This index provides a replicable model for global policymakers to evaluate welfare reforms.

The WEI surged, driven by:

  • DBT Savings (50% weight): ₹3.48 lakh crore cumulative leakage reduction.
  • Subsidy Reduction (30% weight): A decline from 16% to 9% of total expenditure.
  • Beneficiary Growth (20% weight): A 16-fold expansion in coverage.

Conclusion

The Direct Benefit Transfer (DBT) system has proven to be a transformative tool for India’s welfare delivery, significantly enhancing the efficiency of public spending and expanding the reach of social benefits. Over the past decade, DBT has not only reduced fiscal leakages by ₹3.48 lakh crore but also ensured that subsidies are better targeted, with a marked decline in subsidy allocations as a percentage of total expenditure. The rise in the Welfare Efficiency Index (WEI) underscores the success of DBT in optimizing fiscal resources while broadening coverage for millions of beneficiaries. The sectoral savings, particularly in high-leakage programs like food subsidies, MGNREGS, and PM-KISAN, illustrate how the system’s integration of Aadhaar and mobile-based transfers has addressed inefficiencies and curbed misuse.

As per the report by the BlueKraft Digital Foundation, this data-driven assessment demonstrates that fiscal prudence and inclusivity can go hand-in-hand, offering valuable insights for policymakers worldwide looking to refine their own social protection models. As governments grapple with balancing fiscal constraints and social equity, India’s experience with DBT presents a compelling case for the efficacy of direct transfers in fostering both economic and social development. The lessons learned from this success story can guide global efforts to make welfare systems more efficient, transparent, and inclusive.

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Santosh Kumar/ Sheetal Angral/ Saurabh Kalia

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