{"id":488,"date":"2026-04-24T16:40:26","date_gmt":"2026-04-24T11:10:26","guid":{"rendered":"https:\/\/majhi.in\/?page_id=488"},"modified":"2026-05-06T13:29:50","modified_gmt":"2026-05-06T07:59:50","slug":"part-2-reading-b-w-the-lines","status":"publish","type":"page","link":"https:\/\/majhi.in\/?page_id=488","title":{"rendered":"Part-2: Reading b\/w the lines"},"content":{"rendered":"\n

Part 2<\/strong>: MFI repayment machine is adversely impacting State\u2019s welfare spending\/ DBT<\/h2>\n\n\n\n

The convergence of high-interest microfinance debt and the influx of government Direct Benefit Transfers (DBT) has created a controversial economic cycle in rural Uttar Pradesh. As MFIs moved to a “risk-based pricing” model following RBI’s 2022 regulatory overhaul, interest rates in UP\u2019s rural pockets have climbed, leading to a phenomenon where government welfare funds are effectively being “recycled” back into the private financial sector<\/strong> to service high-cost debt.<\/h4>\n\n\n\n

1. The Interest Rate Escalation (2020\u20132025)<\/strong><\/h3>\n\n\n\n

Before April 2022, the RBI capped MFI interest rates (usually around 21\u201322%). The “Regulatory Framework for Microfinance Loans, 2022”<\/strong> removed these caps, allowing MFIs to set rates based on their “cost of funds” and “risk.” In rural UP, which has seen rising delinquencies, MFIs have pushed rates significantly higher.<\/h4>\n\n\n\n
Year<\/strong><\/th>Avg. MFI interest rate<\/strong><\/th>Effective Cost to Borrower*<\/strong><\/th>RBI Policy Context<\/strong><\/th><\/tr><\/thead>
2020\u201321<\/td>21.50%<\/td>~23.5%<\/td>Capped under old regime; COVID moratoriums.<\/td><\/tr>
2021\u201322 <\/td>21.80%<\/td>~23.8%<\/td>Post-COVID recovery; high operational costs.<\/td><\/tr>
2022\u201323 <\/td>23.50%<\/td>~25.5%<\/td>RBI Deregulation: Interest caps removed.<\/td><\/tr>
2023\u201324 <\/td>25.20%<\/td>~28.0%<\/td>Risk-based pricing; UP rates hit 26%+.<\/td><\/tr>
2024\u201325 <\/td>26.8% <\/td>~30.0%<\/td>Peak Rates: Focus on recovering NPAs in UP.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
*Effective cost includes processing fees (1-2%) and mandatory insurance premiums.<\/em><\/h6>\n\n\n\n

2. The “DBT Soak” Effect: Diverting Welfare to Debt<\/strong><\/h3>\n\n\n\n

The “Soak Effect” occurs because MFI collection cycles (weekly or fortnightly) are often timed to coincide with the arrival of government DBT funds (PM-Kisan, Gas Subsidies, or MGNREGA wages). Instead of being used for nutrition or farm inputs, these funds are immediately handed over to MFI field officers.<\/h4>\n\n\n\n
DBT Scheme<\/strong><\/th>Typical payout (A)<\/strong><\/th>Avg. Monthly MFI EMI (B)<\/strong><\/th>% of DBT “Soaked” by Debt<\/strong><\/th><\/tr><\/thead>
 PM-Kisan (Tranche)<\/td>\u20b92,000<\/td> \u20b92,800 \u2013 \u20b93,500<\/td> 100%+ (Entire tranche consumed)<\/td><\/tr>
 Ujjwala (Gas subsidy)<\/td> ~\u20b9300<\/td> \u20b92,800 \u2013 \u20b93,500<\/td> ~10% of monthly EMI<\/td><\/tr>
 MGNREGA (monthly) <\/td> ~\u20b94,200<\/td> \u20b92,800 \u2013 \u20b93,500<\/td> ~70% to 85% <\/td><\/tr>
 Old Age Pension <\/td>\u20b91,000<\/td> \u20b92,800 \u2013 \u20b93,500<\/td> 100% (Diverted to household debt)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

The impact is compounded by “Multiple Lending”<\/strong>, where a single rural woman in UP often holds 3 to 4 active loans from different MFIs, making her total monthly EMI higher than her total DBT income.<\/h4>\n\n\n\n

3. Social Tension and “Debt-Traps” in Rural UP<\/strong><\/h3>\n\n\n\n

The combination of high rates and aggressive collection has led to localized social unrest. In districts like Basti, Gorakhpur, and Deoria<\/strong>, there have been reports of “MFI-Free Village” boards and local political leaders intervening to stop MFI field officers from entering villages.<\/h4>\n\n\n\n
Metric<\/strong><\/th>Social Implication<\/strong><\/th>2020-21<\/strong><\/th>2022-23<\/strong><\/th>2024-25<\/strong> (Est)<\/th><\/tr><\/thead>
 Multiple Lending <\/td> Extreme over-leveraging; defaults.<\/td>1.8 Loans\/ borrower<\/td>2.6 Loans\/ borrower<\/td>3.4 Loans\/ borrower<\/td><\/tr>
PAR 30[1]<\/a> (NPA Risk) <\/td> Rising defaults; aggressive collections.<\/td>4.50%<\/td>8.20%<\/td>12.5%<\/td><\/tr>
 Field Harassment complaints<\/td> Conflict between Field Officers and Villagers.<\/td>Low<\/td>Moderate<\/td>High<\/td><\/tr>
 “Loan for Loan” cases <\/td> Borrowing from MFI-B to pay MFI-A.<\/td>15%<\/td>28%<\/td>42%<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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[1]<\/a>        PAR 30 (Portfolio at Risk > 30 days) is a key financial metric used by banks, MFIs (Microfinance Institutions), and NBFCs to measure the percentage of a loan portfolio that has at least one payment overdue by 30 days or more. It serves as an early warning signal of credit risk and potential future Non-Performing Assets (NPAs), indicating that borrowers are experiencing financial stress.<\/em><\/h6>\n\n\n\n

4. Qualitative Analysis: Why This is Happening in UP<\/strong><\/h3>\n\n\n\n
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