Ladki Bahin Yojana: 92 Lakh Beneficiaries Cut | CLAT

CURRENT AFFAIRS | JULY 13, 2026

One of India’s most talked-about welfare schemes has just undergone a dramatic pruning. After a verification exercise, Maharashtra has removed roughly 92 lakh beneficiaries from the Mukhyamantri Majhi Ladki Bahin Yojana — about 38% of the scheme’s peak base of 2.43 crore women. The cut, revealed through RTI data, opens a window into how India’s cash-transfer state actually works, where it leaks, and how eligibility is policed.

For CLAT aspirants this story is a compact case study in welfare administration, Aadhaar-based verification, constitutional audit institutions and the perennial debate over “freebies” — all wrapped around numbers ripe for data-interpretation questions.

What the scheme is, and what happened

The Ladki Bahin Yojana transfers ₹1,500 per month to women aged 21–65 from families earning below ₹2.5 lakh a year. Launched ahead of the 2025 Assembly elections, it is widely credited with helping the ruling alliance return to power — a textbook example of a targeted cash transfer with visible political payoff.

But scale invites scrutiny. When the state ran its beneficiary rolls through a verification filter, about 92 lakh names fell out. The single biggest reason was incomplete e-KYC — 62 lakh beneficiaries (67% of the cuts) had not completed the electronic Know-Your-Customer authentication that links a beneficiary to a verified Aadhaar-seeded bank account.

The anatomy of the cut

The RTI data offers an unusually detailed breakdown of why beneficiaries were removed. Reading it teaches how eligibility filters actually operate in a large DBT scheme.

Two figures stand out for their oddity: roughly 29,000 male beneficiaries and 8,000 government employees had somehow been enrolled in a scheme meant only for low-income women. These illustrate the classic twin failures of any large welfare programme — inclusion errors (wrong people getting benefits) and exclusion errors (deserving people left out).

Leakage, targeting and the audit trail

The removal of ineligible names is, in one sense, the system working: verification is supposed to weed out those who do not meet criteria. But it also raises hard questions. If 62 lakh women were dropped purely because e-KYC was incomplete, how many of them were genuinely eligible but simply could not navigate the digital authentication? This is the tension at the heart of Aadhaar-linked welfare — the same de-duplication that curbs fraud can also become a barrier for the poorest and least digitally literate.

The CAG‘s earlier flagging of deficiencies in budget control adds a fiscal dimension. Cash-transfer schemes of this size — running into tens of thousands of crores annually — strain state finances, and audit institutions exist precisely to keep such spending accountable to the legislature.

The bigger welfare picture

Ladki Bahin belongs to a growing family of women-centric cash-transfer schemes across Indian states, most directly comparable to Madhya Pradesh’s Ladli Behna Yojana. Overlap with other schemes matters too: 3.6 lakh women were removed because they already receive Sanjay Gandhi Niradhar Yojana benefits, reflecting rules that prevent double-dipping across welfare programmes.

The freebies debate and the Constitution

Cash-transfer schemes launched just before elections sit at the heart of India’s long-running “freebies” (or revdi) debate. Critics argue that such promises distort the level playing field of elections and strain public finances; defenders call them legitimate welfare and a tool of social justice. The Supreme Court examined this tension in S. Subramaniam Balaji v State of Tamil Nadu (2013), where it held that promises of free goods in an election manifesto do not by themselves amount to a “corrupt practice” under electoral law, but directed the Election Commission to frame guidelines on manifesto promises within the Model Code of Conduct.

The constitutional anchors here are worth remembering. Article 14 guarantees equality before the law, which is why classification of beneficiaries (by income, age, gender) must be reasonable and non-arbitrary. The Directive Principles of State Policy — especially Articles 38, 39 and 46 — direct the State to reduce inequality and promote the welfare of the people, giving cash-transfer schemes a constitutional rationale even though they are not judicially enforceable rights.

Inclusion versus exclusion: the DBT dilemma

The Maharashtra episode crystallises the central dilemma of Aadhaar-linked welfare. On one side, de-duplication through Aadhaar seeding genuinely removes ghost beneficiaries, ineligible men, and duplicate entries — saving public money. On the other, rigid digital requirements like e-KYC can wrongly exclude the very people a scheme is meant to serve: elderly women, those without smartphones, or residents of areas with poor connectivity. The Supreme Court in K.S. Puttaswamy v Union of India (2018), while upholding Aadhaar for welfare delivery, cautioned that no one should be denied benefits merely for want of Aadhaar authentication.

The lesson for policymakers is that a “clean” beneficiary list is not automatically a “fair” one. Robust grievance-redress — a clear route for a wrongly-removed woman to re-verify and be reinstated — is what separates a genuine anti-leakage drive from a silent exclusion of the deserving poor. How Maharashtra handles appeals from the 62 lakh dropped for incomplete e-KYC will be the real test of the exercise.

DBT, JAM and the architecture of modern welfare

Schemes like Ladki Bahin ride on infrastructure India has built over the past decade, often summarised as the JAM trinity — Jan Dhan bank accounts, Aadhaar identity, and Mobile connectivity. Together these allow a state to transfer money directly to millions of verified accounts with minimal leakage, bypassing the old chain of intermediaries where funds often went missing. DBT has genuinely reduced leakage in schemes ranging from LPG subsidies to MGNREGA wages, and the government estimates large cumulative savings from de-duplication and the elimination of fake beneficiaries.

But the Maharashtra numbers show the flip side of that efficiency. When eligibility is enforced through a database, an incomplete field — a missing e-KYC, an un-seeded Aadhaar, a mismatched name — can instantly cut off a real person. The technology does not know the difference between a fraudster and a poor woman who could not reach a service centre. That is why the design of the appeal process is as important as the design of the filter. A fair scheme must make it as easy to get wrongly-removed names restored as it was to remove them.

The Maharashtra clean-up is a reminder that a welfare scheme’s headline reach and its verified reach can be very different numbers. For students of law and public policy, the interesting question is not just who was removed, but whether the process of removal was fair, transparent and gave genuinely eligible women a chance to correct their records — a question that touches equality, natural justice and the promise of the welfare state itself.