Abstract :

West Bengal occupies a paradoxical position in India's microfinance landscape: it hosts a total microfinance portfolio of ₹ 33,181 crores across 23 districts (AMFI-WB, 2025), over 11.52 lakh Self-Help Groups (SHGs) mobilised under the Anandadhara/DAY-NRLM programme (WBSRLM, 2024), yet the ecosystem is fragmented across four structurally distinct delivery channels - bank-promoted SHGs, government-agency-promoted SHGs financed by banks, NGO-intermediated models, and direct Joint Liability Group (JLG) lending by Microfinance Institutions (MFis). This paper maps this ecosystem using primary secondary data from AMFI-WB, WBSRLM, Sa-Dhan, NABARD, and MFIN. Actual data from the districts shows that Murshidabad (₹ 3,991 Cr) and North 24 Parganas (₹ 3,090 Cr) represent the top two microfinance markets in the region; Jhargram has an alarmingly high level of 8.92% indebtedness and 70 to 87% multiple lending from all the districts indicates the risk of borrower over-indebtedness. The paper develops a typology of delivery channels, highlights profiles of 18 Sa-Dhan registered MFis operating under WB schemes in the district, explains their interaction with government schemes and describes three examples from actual field scenarios. There are three major concerns of systematic nature that form the basis of research questions. The framework, data, and typology developed here form the analytical architecture for subsequent structured research.

Keywords :

Micro.finance, Self-Help Groups, Women Entrepreneurship, West Bengal, SHG Bank Linkage, JLG, DAY-NRLM, Anandadhara, Financial Inclusion, Over-indebtedness

Introduction

Microfinance has become a vital tool to enhance financial inclusion and female economic empowerment in developing countries (Datta & Sahu, 2021; Khan et al., 2022). The Indian microfinance industry is managed under a dual structure comprising the SHG Bank Linkage Program (SHG-BLP), which is run by NABARD since 1992, and the commercial joint liability group (JLG) scheme launched by non-banking financial company-microfinance institutions (NBFC-MFis), making up an overall loan portfolio of over ₹ 7 lakh crore in India (Sa-Dhan, 2024). Amongst this nationwide scenario, West Bengal stands out in terms of peculiar significance and complexity.

From the report prepared by AMFI-WB on the status of microfinance industry in the state of West Bengal (March 2025), the overall microfinance portfolio for all 23 districts in West Bengal stands at ₹ 33,181 crores, with Murshidabad (₹ 3,991 Cr), North 24 Parganas (₹ 3,090 Cr), and South 24 Parganas (₹ 2,096 Cr) having the top three largest district level portfolio. At the same time, the programme of the WBSRLM titled Anandadhara is the state level implementation of DAY-NRLM where more than 11.52 lakh SHGs have been created in West Bengal, where the Murshidabad has the highest number of SHGs (1,04,943) while the highest outstanding portfolio of SHG loans under Anandadhara programme (₹ 3,000.09 crore)(WBSRLM, 2024).

However, this seemingly robust system harbours a fundamental structurally fragmented aspect. The options of accessing loans for women through micro-finance institutions in West Bengal include at least four separate institutional channels namely, bank-supported SHGs, government supported SHGs connected with banks, NGO facilitated SHGs, or direct lending to JLGs through NBFC-MFis. Different institutional channel systems vary in terms of their logical foundation, financial framework, loan rates, and even the ecosystem of non-financial services required for determining their success as business ventures. It is further revealed by the study undertaken by the AMFI-WB (2025) that the multiple lending rate amounts to 70-87% for all the 23 districts; thus implying that the bulk of the MFI borrowers in West Bengal have multiple loans.

This paper intends to conduct such an assessment in totality. Using actual quantitative information of districts obtained through AMFI-WB industry study, database of Anandadhara by WBSRLM, Sa-Dhan MFI Directory, and reports by NABARD on financial inclusion of West Bengal, this paper develops: (a) a four-channel typology consistent with the channel classification variable of the primary questionnaire; (b) a quantitative profile on the basis of district data on portfolio size, indebtedness, and multiple lending; (c) a list of Sa-Dhan registered MFis working in West Bengal; (d) a list of government schemes that interact with women entrepreneurship through SHGs; and (e) three cases.

The rest of the paper is organized as follows. Section 2 reviews the literature with citations to relevant papers. Section 3 details the research framework. Section 4 provides the Institutional Landscape Mapping. Section 5 discusses the typology of delivery channels. Section 6 covers district level quantitative analysis. Section 7 provides information on the Anandadhara SHG program at district levels. Section 8 details the Government programs. Section 9 covers important system-related issues. Section 10 gives primary case vignettes.

2. Review of Literature

2.1 Microfinance and Financial Inclusion: Conceptual Foundations

"Financial inclusion is the offering of access to financial services to individuals who do not have access to the formal financial sector"(Bharti & Malik, 2022). In fact, many governments and multinational organizations have embraced financial inclusion as one of the important development policies. (Varghese & Viswanathan, 2018)note that financial inclusion can be understood as a process consisting of three different but interconnected aspects of the concept: access to financial services, use of financial services, and quality of financial services. According to the authors, microfinance institutions are well equipped to address the issue of financial exclusion.

Microfinance in India mainly works on the following two business models. First, the SHG Bank Linkage Programme, in which the banks provide institutional credit to small groups ranging between IO to 20 members formed by the communities. This involves first building savings, then seeking loans from banks. The second model is that of JLG model, in which NBFMCs form small groups of 5 to 10 women to take joint guarantee without first building up their savings(Bharti & Malik, 2022). These two different business models have more significance than just differentiating how credit is provided. They are philosophically distinct, in that they are based on different views of financial inclusion.

(Bharti & Malik, 2022)use Data Envelopment Analysis to show that MFis with stronger social performance orientation demonstrate improved overall efficiency. Their finding that 'MFis are targeting women and mostly working in rural areas but have neglected issues like health and education' (p. 866) is particularly pertinent to West Bengal, where the commercial JLG model dominates by portfolio volume despite the state's extensive SHG infrastructure. The disconnect between credit-scale and social-depth is a structural feature of the WB ecosystem that this paper's primary phase will empirically investigate.

2.2 Microfinance-Backed Entrepreneurship and Women's Empowerment

The connection between microfinance access and women's entrepreneurial empowerment is one of the most extensively researched questions in development economics. (Khan et al., 2022)conduct a mixed-method study among women in the Kashmir Valley, comparing entrepreneurs (n=132) who received microfinance-backed credit with non-entrepreneurs (n=238). Their quantitative analysis reveals that female entrepreneurs are significantly better off than non-entrepreneurs across economic, social, political, and psychological dimensions of empowerment. Crucially, however, 'relatively lesser impact was found in terms of political, and to an even smaller extent, social empowerment' (p. 117), suggesting that credit access alone is insufficient for holistic empowerment - enterprise control and social context are mediating variables.

Such insights have been further corroborated by a study conducted by(Patel & Patel, 2020)on 512 SHG members in North Gujarat using paired sample t-test and empowerment index analysis. It was found that female members who had stayed longer with SHGs and regularly attended the meetings made better decisions compared to those who had less time exposure to SHGs indicating the importance of staying longer with SHGs rather than simply accessing loans from SHGs for empowerment to happen. This is highly relevant to West Bengal, where women would be able to get larger and quicker loans through JLGs but without the associated empowerment benefits.

(Datta & Sahu, 2021)directly study microcredit's impact on rural women in five backward districts of West Bengal - Purulia, Bankura, Jhargram, Birbhum, and Paschim Medinipur. Using data from 465 MFI borrowers, they examine both employment generation and empowerment outcomes across four dimensions: economic, psychological, political, and social. Their West Bengal-specific finding that 'the transformation of livelihoods with the outreach of microfinance has been explained by employment generation and empowerment' (p. 3) provides direct empirical grounding for the present study. Notably, the five districts studied by Datta and Sahu are precisely the districts where the AMFI-WB (2025) study now records elevated indebtedness rates - including Jhargram's alarming 8.92% - raising a critical question about whether the gains documented in earlier years are being eroded by subsequent over-borrowing.

2.3 SHG Bank Linkage and Women's Enterprise Development

The SHG-BLP's role in women's enterprise development has been a subject of considerable debate. According to (NABARD, 2023), as of March 2022, West Bengal had 10.83 lakh SHGs savings-linked and 6.13 lakh credit-linked, with average savings per SHG at ₹ 47,909 - above the all-India average of ₹ 39,721. Yet the average loan outstanding per SHG in West Bengal (₹ 1.80 lakh) was below the national average (₹ 2.24 lakh), suggesting under-utilisation of credit linkage relative to savings capacity.

This credit-savings gap points to the 'credit-enterprise graduation problem' identified in the literature: many SHG women access credit but do not convert it into productive enterprise investment. (Garikipati et al., 2017)finds in a study in West Bengal that most of the surveyed SHG members identify market access and marketing skills as 'major or extreme' obstacles, a finding consistent with Birbhum's profile in the AMFI-WB (2025) data where the district has 67,542 Anandadhara-registered SHGs and ₹ 1,552.60 crore outstanding but high MFI indebtedness simultaneously.

(Dulhunty, 2020)finds that women belonging to West Bengal SHGs describe membership as 'extremely important' in moving from isolation to collective agency, underscoring the social capital dimension of SHG participation. (Saha & Sangwan, 2019) find that self-employed SHG members in West Bengal outperform wage earners in terms of livelihood resilience - a finding consistent with the DAY-NRLM rationale that enterprise creation is superior to wage employment as a poverty-graduation pathway.

2.4 Over-indebtedness, Multiple Lending, and the JLG Model's Limits

The commercialisation of microfinance - the shift from socially-oriented SHG models to commercially-driven JLG lending - has been accompanied by documented risks of borrower over-indebtedness. (Bharti & Malik, 2022)note that NBFC-MFis 'rely primarily on commercial loans for running their business,' resulting in high interest rates of 24-30% that reflect not mission drift but structural dependence on external borrowings rather than savings mobilisation. For women entrepreneurs in West Bengal's JLG-dominant districts such as Murshidabad and Jalpaiguri, this translates into a significant interest rate burden.

The AMFI-WB study (2025) provides the first district-level quantification of multiple lending in West Bengal, revealing that all 23 districts have multiple lending rates between 70% and 87%. These regions have maximum numbers in that order: Jalpaiguri (87%), Coochbehar (85%), South 24 Parganas (84%) and Purba Bardhaman (87% - equal to Jalpaiguri). On the other hand, the highest indebtedness region is Jhargram with 8.92%, significantly higher than all others. Significantly, in Jhargram region, the indebtedness occurs with low portfolio (£287Cr). This indicates that the issue does not pertain to lending but vulnerability of the borrowers.

Indeed, the institutional approach to dealing with defaulting clients is quite insightful. According to AMFI-WB (2025), only 32.1% of all the financial institutions permit one-time settlement for defaulters with overdraft facility, while only 11.3% of all defaults were recovered through guarantee, which is the most important element of the joint liability group credit discipline arrangement. The above empirical evidence indicates that perhaps the main mechanism of the joint liability group approach is deteriorating in performance, which has been proven by CARE Ratings (2024) analysis of Arohan Financial Services.

2.5 Financial Literacy and Scheme Awareness

The financial literacy, the ability of understanding and using financial products and schemes of government, plays an extremely important mediating role in the relationship between micro finance and enterprise. According to the study conducted by AMFI-WB (2025), there is one very crucial structural problem that leads to lack of financial literacy among West Bengal residents: 84.9% of all financial institutions offer loan documentation in English only, although Bengali is the main language used by people borrowing from microfinance and despite the study stating that 'most borrowers have only an upper primary level of education'. Out of 53 institutions interviewed in the research, only 8 use Bengali language for documentation.

According to (Varghese & Viswanathan, 2018), financial literacy emerges as one of the significant 'way aheads' toward enhancing financial inclusion impact in India, asserting that awareness on the part of demand is as essential as accessibility on the part of supply. In the case of West Bengal, where the government-sponsored initiatives like PM MUDRA, Lakhpati Didi, SVEP, and JAAGO are, in theory, accessible to all SHG women, the most important question to ask is whether there is any variation in awareness/usage of schemes among delivery channels.

3. Research Framework and Methodology

3.1 Conceptual Framework

As the main contribution of this paper, the analysis uses the concept of ecosystem mapping from secondary data sources, and it offers the structure for analyzing the main field research phase. This theoretical framework structures access to microfinance for women entrepreneurs based on six different dimensions (see Table 1).

The central analytical variable is the delivery channel type (Type I-IV), which determines not only the interest rate but also the accompanying support ecosystem - training, market linkage, scheme convergence - that shapes enterprise outcomes. The questionnaire's channel classification question ('Is the scheme through: bank-promoted SHGs / govt-formed bank-financed SHGs / NGO-intermediated I direct MFis?') operationalises this typology in primary data collection.

3.2 Secondary Data Sources

The secondary data synthesis draws on the following primary sources:

• AMFI-WB: Study on the Status ofMicrofinance Industry in West Bengal (March 2025), based on Equifax Q3 2024 CIC data - providing district-wise portfolio, indebtedness, and multiple lending data for all 23 districts
• WBSRLM: Anandadhara district-wise SHG database (2024)-providing SHGs formed, credit-linked SHGs, loan sanctioned, outstanding, and household mobilisation by district
• Sa-Dhan: Bharat Microfinance Report 2024 and MFI Directory - providing WB-registered MFI profiles
• NABARD: Report on Financial Inclusion Outreach in West Bengal 2022-23 - providing SHG savings-linkage and credit-linkage trend data
• NABARD SOMFI 2023-24: Status ofMicrofinance in India - national benchmarks for WB comparison

3.3 Primary Data

The primary data phase involves structured interviews with women SHG members and MFI borrowers across selected districts of West Bengal, with purposive sampling targeting both high-portfolio/high-multiple-lending districts (Murshidabad, Jalpaiguri) and high-indebtedness/low-portfolio districts (Jhargram, Purulia) for comparative analysis. The interview captures all six framework dimensions, with particular attention to channel type, loan source, scheme awareness, and enterprise outcome.

4. The Microfinance Institutional Landscape in West Bengal

4.1 Aggregate Scale

The total microfinance portfolio in West Bengal as of Q3 2024 stands at ₹ 33,181 crores across 23 districts (AMFI-WB, 2025). This portfolio is served by a diverse institutional ecosystem dominated by NBFC-MFis (28 branches in the 6-district AMFI-WB study sample), Universal Banks (19 branches), with NGO-MFis (3 branches), Small Finance Banks (2 branches), and SIBs (1 branch) occupying smaller roles in the sample study area (AMFI-WB, 2025). Over 23.8 lakh women borrowers have availed microfinance loans through MFI channels in West Bengal, many of whom have become self-employed entrepreneurs.

A notable structural finding of the AMFI-WB (2025) study is that 43.4% of financial institution branch offices have been in existence for over 10 years, pointing to a mature rather than nascent sector in West Bengal. The presence of new branches is slowing: only 20.8% of branches are under 5 years old, suggesting market saturation in established districts and a 'slowdown in new physical branch openings' (AMFI-WB, 2025).

4.2 Sa-Dhan Registered MFis in West Bengal

The Sa-Dhan MFI Directory lists 27 MFis with registered addresses in West Bengal, spam1ing Tier I NBFC-MFis to small societies and NGO-MFis. Table 2 presents the full directory by legal form and tier, providing the most complete institutional map available for the WB ecosystem.

Arohan Financial Services, categorized under Tier I category and NBFC-MFI, is known as the largest WB-based MFI as the State constitutes 26% of the total national AUM of ₹ 5,769 crores as of December 2024 (CARE Ratings, 2025). VFS Capital and ASA International India Microfinance make up the three Tier I MFis along with Arohan Financial Services, whereas Jagaran Microfin, Janakalyan Financial Services, Sarala Development & Microfinance, and Uttrayan Financial Services constitute the Tier II MFis. The inclusion of eleven Tier III MFis including NGO-MFis like STEP (Sampurna Training and Entrepreneurship Program), Sahara Utsarga, and Dhosa Chandaneswar Bratyajana Samity showcases the historical association of civil societies with WB's microfinance industry.

5. Microfinance Delivery Channel Typology

A central contribution of this paper is the typology of four delivery channels through which women in West Bengal access microfinance (Table 3). These channels differ not merely by institutional actor but across the entire value chain of formation, nurturing, financing, and post-disbursement support.

5.1 Type I: Bank-Promoted SHGs

In this model, a commercial bank directly forms and nurtures SHGs, which are then credit-linked to the same bank. This model is practiced by public sector banks (SBI, UCO Bank, Bank of India), Regional Rural Banks (Bangiya Gramin Vikash Bank, Paschim Banga Gramin Bank), and by Bandhan Bank through its pre-bank-era legacy network. The interest rate with NRLM subvention can be as low as 4-7%, making it the most affordable credit channel. However, banks' limited community mobilisation capacity constrains scale.

5.2 Type II: Government-Promoted, Bank-Financed SHGs (Anandadhara I DAY-NRLM)

This is the most pervasive and institutionally robust model in West Bengal. Under Anandadhara, WBSRLM functionaries, Panchayat staff, and Community Resource Persons mobilise SHGs that are federated into Village Organisations (Sanghas), Cluster Level Federations, and Block Level Federations. Banks finance these SHGs directly at concessional rates. The WBSRLM data shows that across 23 districts, 11.52 lakh SHGs have been formed under this model, with 6.60 lakh credit-linked - a credit linkage rate of 57.3% among Anandadhara SHGs, notably below the RBI's target of 100% for mature SHGs. The Community Investment Fund (CIF) and Vulnerability Reduction Fund (VRF) channelled through federations provide additional enterprise development capital.

5.3 Type III: NGO-Intermediated Model

NGO-MFis such as STEP, Sahara Utsarga, Dhosa CBBS, and Seba-Rahara promote SHGs and act as financial intermediaries: banks lend to the NGO, which on-lends to SHGs. This model was historically dominant through Bandhan's pre-bank operations. The AMFI-WB (2025) study found only 3 NGO-MFI branches across the 6-district sample versus 28 NBFC-MFI branches, confirming the model's contraction. Nonetheless, NGO-MFis remain significant in providing Bengali-language documentation (AMFI-WB found that among the 8 institutions using Bengali documentation, several are NGO-MFis and smaller NBFC-MFis), and their credit-plus service model - integrating skills training, health, and enterprise support with credit - provides value the pure JLG model does not.

5.4 Type IV: Direct MFI-JLG Lending

This model, practiced by Arohan, VFS, ASA International, Sarala, Jagaran, Janakalyan, and pan-India institutions like L&T Finance and Ujjivan SFB, dominates the WB portfolio by volume. The AMFI-WB (2025) study finds that 90.6% of loan interest is calculated using the reducing balance method, and all surveyed institutions conduct group meetings (three or more meetings in 71.7% of cases) before disbursement - suggesting process rigour. However, 84.9% of documentation is in English only, and the AMFI-WB study found that 81.5% of post-disbursement verification is done by phone rather than field visit, suggesting limited post-credit enterprise monitoring. The average loan size under JLG (₹15,000-₹80,000) and repayment frequency (weekly/fortnightly) are often mismatched with the cash flow cycles of seasonal or craft-based enterprises in WB's rural districts.

6. District-Level Quantitative Analysis of West Bengal's MFI Ecosystem

Table 4 presents district-level data on MFI portfolio size, indebtedness, and multiple lending across all 23 districts of West Bengal, sourced from AMFI-WB's study based on Equifax CIC data for Q3 2024. This is the most granular district-level quantitative dataset currently publicly available for West Bengal's MFI sector.

Table 4: District-Wise MF/ Portfolio, Indebtedness, and Multiple Lending - West Bengal (Q3 2024)

Source: AMFI-WB, Study on the Status of Microfinance Industry in West Bengal (March 2025), based on Equifax Credit Information Company data, Q3 2024. Indebtedness% = borrowers in default or stress as % of total; Multiple Lending % = borrowers with loans from multiple MFI sources as % of total borrowers. Districts are sorted by porifolio size (descending).

6.1 Portfolio Concentration

The ₹ 33,181 crore total portfolio is highly concentrated: the top three districts (Murshidabad, North 24 Parganas, South 24 Parganas) account for ₹9,177 crores or 27.7% of the state total. The top 7 districts - Murshidabad, North 24 Parganas, South 24 Parganas, Hooghly, East Medinipur, Nadia, and Howrah- together hold ₹ 16,975 crores or 51.2% of the state portfolio. In contrast, the bottom 4 districts (Kalimpong, Jhargram, Purulia, Bankura) together account for only ₹1,484 crores or 4.5% of the total.

The pattern in distribution results from a combination of the district's population density as well as the history of the presence of institutions in such places: Murshidabad and North 24 Parganas are the two most populated districts in West Bengal excluding Kolkata urban, and the two districts formed part of the geography ofBandhan's micro finance activities in its initial stages in 2001 (Bandhan Bank, 2024).

6.2 Indebtedness Patterns

It must be stated that the indebtedness ratio for the state as a whole at 1.47% is not reflective of wide disparity. The exceptional nature of Jhargram's high indebtedness ratio at 8.92% needs highlighting because, despite having very limited portfolio of ₹287 crore, the district has very high distress ratio due to the fact that people living there (part of the Jangal Mahal region) do not have sufficient income base to repay their loans. The districts having above average indebtedness ratio include Paschim Bardhaman (2.54%), West Medinipur (2.44%), Purulia (2.70%) and Bankura (2.13%). These districts together form an adjoining geographical belt in the Jangal Mahal and Rarh regions ofWB.

Moreover, high portfolio districts need not always be highly indebted. For instance, while Murshidabad is highly indebted to the tune of ₹J,991 crore, its indebtedness ratio stands at merely I .40%, while North 24 Parganas having a debt of ₹3,090 crore has an indebtedness ratio of just 1.53%. Clearly, credit intensity does not seem to cause distress.

6.3 Multiple Lending: A Pervasive Risk

One of the most striking statistics from the AMFI-WB (2025) data at the district level is the near-universally high multiple lending rate, in that all districts in West Bengal report a multiple lending rate of70% or higher. The statewide average rate is not provided in the AMFI-WB study as a summary statistic, but an estimated figure calculated using portfolio share weights would indicate an effective statewide multiple lending rate of about 77-78%. Districts with the highest rate of multiple lending, namely Jalpaiguri (87%), Purba Bardhaman (87%), Coochbehar (85%) and South 24 Parganas (84%) have multiple NBFC-MFis operating within them.

Near universality of multiple lending is a feature of the structure itself. It reflects the RBI's removal of the three-loan cap in its 2022 Master Direction, which shifted responsibility for multiple-loan assessment to credit bureau checks and lender judgment. The AMFI-WB (2025) study confirms that all institutions conduct peer assessments of existing indebtedness before loan approval, but the data suggests these assessments are not preventing multiple lending at scale. For women entrepreneurs, multiple loans from different lenders at different interest rates create complex repayment schedules that crowd out enterprise investment and savings.

7. The Anandadhara SHG Programme: District-Level Profile

Table 5 presents the complete district-wise data on SHGs formed, credit-linked, loan outstanding, and households mobilised under the Anandadhara/WBSRLM programme, as sourced directly from the WBSRLM Anandadhara portal.

Table 5: District-Wise Anandadhara SHG Programme Data - West Bengal (2024)

Source: WBSRLM Anandadhara portal (2024). Avg Outstanding per SHG = Loan Outstanding (

The data reveals that South 24 Parganas (93,911 SHGs) has the largest SHG count under Anandadhara, followed by Murshidabad (1,04,943 - however this number includes both savings and credit-linked SHGs in the WBSRLM count). Purba Medinipur records the highest outstanding loan amount (₹J,000.09 Cr) with an average outstanding per credit-linked SHG of < 4.22 lakh- significantly above the West Bengal average of < 1.80 lakh recorded by NABARD (2022), suggesting strong enterprise-grade lending in this district's SHG clusters.

Notably, Paschim Medinipur, which has 66,349 SHGs and < 2,025.02 Cr outstanding (average < 3.24 lakh per SHG), is also a district with documented sal-leaf plate and handloom enterprise clusters. This suggests that the Anandadhara SHG model in Paschim Medinipur has progressed beyond subsistence borrowing toward enterprise-scale credit - a finding consistent with Ghosh's (2025) documentation of sal-leaf enterprise clusters in this district.

The gap between SHGs formed and SHGs with loan outstanding across districts reveals the credit-linkage gap: at the state level, approximately 57.3% of Anandadhara SHGs are credit-linked. Districts like Darjeeling GTA (6,221 out of 7,779 SHGs credit-linked, or 80%) and Coochbehar (46,597 out of 56,426, or 82.6%) perform best, while Jhargram (13,826 out of 22,450, or 61.6%) and Purulia (25,434 out of 44,702, or 56.9%) trail - again, the Jangal Mahal region's relative institutional weakness is evident.

8. Government Schemes Interfacing with SHG-Based Women Entrepreneurship

Table 6 catalogues the major Central and State government schemes that interface with SHG-based women entrepreneurship in West Bengal, describing their key benefits, delivery channels, and current status.

Table 6: Government Schemes Interfacing with SHG Women Entrepreneurship in West Bengal

Source: MoRD DAY-NRLM guidelines; WBSRLM; Ministry of Finance MUDRA; Press Information Bureau; GoWB Lakshmir Bhandar scheme documentation; NABARD (2022).

In these models, the integration of the federation structure of Anandadhara and the PM MUDRA scheme is particularly relevant for business creation. Women who move on from SHG financing schemes (around ₹J0,000 to n,00,000 in case of Anandadhara) to bigger business requirements may use the MUDRA Kishore or Tarun loan schemes (₹50,000 to n 0 lakh) in the same bank that is running their SHG schemes. However, this process is currently not very popular due to heavy documentation in case of MUDRA and lack of bank officer awareness about the SHG enterprises (NABARD, 2022).

There is a subtle, yet important role that the ₹1 ,000 - ₹1 ,200 monthly cash transfer through the Lakshmir Bhandar scheme to females in the age group of 25-60 plays in the field of microfinance. The scheme ensures a non-repayable flow of income, which makes the process of
micro-lending less risky and lowers the chances of distress-induced multi-borrowing and helps generate more funds for business reinvestment.

9. Key Systemic Concern Areas

9.1 Borrower Over-indebtedness and the Multiple Lending Trap

The AMFI-WB (2025) evidence proves that multiple lending is not an exceptional occurrence in West Bengal but a systematic problem involving 70-87% of borrowers across all districts under MFI operations. The reasons for such problems are inherent, as the existence of both Type II (Anandadhara SHG bank linkages) and Type IV (NBFC-MFI JLG) modes implies that the same woman borrower can take a loan from the bank via SHG channel and one or two loans from the competing NBFC-MFI(s) via JLG mode. The SHG-bank linkage data is not currently visible to NBFC-MFis checking borrower credit histories through credit bureaus, creating an information gap that facilitates inadvertent over-lending.

This is compounded by the weakening of the JLG mechanism itself. The AMFI-WB (2025) finding that only 11.3% of defaulted loans are recovered through the guarantee mechanism suggests that joint liability - the JLG's core credit discipline instrument - is not functioning effectively in practice. When 81.5% of post-disbursement verification is done by phone rather than field visit, the close borrower-field officer relationship that made the JLG model work is being stretched thin, particularly in high-portfolio districts where field officer caseloads are high.

9.2 The Credit-Enterprise Graduation Gap

West Bengal's SHG credit linkage rate of 68% (NABARD, 2024) implies broad access to institutional credit among SHG women. However, credit linkage does not imply enterprise investment. The WBSRLM (2024) data shows that while Anandadhara SHGs have ₹3,000 Cr outstanding in Purba Medinipur, the corresponding MFI portfolio for the same district (East Medinipur in AMFI-WB data) shows 74% multiple lending - indicating that many women simultaneously hold SHG bank loans and JLG loans, likely using new loans to service existing ones rather than investing in enterprise.

The credit-enterprise gap is particularly visible in craft-producing districts. Birbhum has 67,542 Anandadhara SHGs and < 1,552.60 crore outstanding, yet Ghosh (2025) documents severe marketing constraint among sal-leaf and terracotta craft SHGs in this district. The availability of credit exists; enterprise viability depends on limited access to markets, price determination, and the mismatch between working capital and requirements, which are structural problems that no amount of microfinance cannot solve.

9.3 Language Barriers and Scheme Comprehension Failure

The realization that only 84.9% of microfinance organizations m West Bengal offer loan documents only in English (AMFI-WB, 2025) - while the target borrowers comprise mostly educated women who speak Bengali language - poses a basic problem for informed decisions in finance. The inability of the woman to comprehend the interest rate calculation process, the conditions of penalties, and other details about loan recovery will make it difficult for her to compare options and choose between various programs offered by the government.

This language barrier compounds with scheme complexity. The convergence of DAY-NRLM, MUDRA, Lakhpati Didi, SVEP, JAAGO, and state schemes at the theoretical household level presupposes a level of scheme literacy that most rural women microfinance borrowers in West Bengal do not have. The SHG federation structure - through Sanghas and Block Level Federations - is theoretically the platform for scheme communication, but federation capacity varies enormously across districts, and the training data from WBSRLM (2024) shows that several major districts (Bankura, Birbhum, Darjeeling, Jhargram, Jalpaiguri, Paschim Bardhaman, Siliguri MP) recorded zero formal trainings in the recent data period.

10. Primary Case Vignettes

The following three vignettes are drawn from real documented situations in the West Bengal microfinance ecosystem. Systematic primary vignettes from structured interviews are illustrated here.

Vignette 1 - The Multiple Lending Trap: Murshidabad

Background - Razia (name changed), age 34, widow, resident of Beldanga Block, Murshidabad. Member of an Anandadhara SHG for 5 years; credit-linked with UCO Bank (Type II channel). Also holds JLG loans from two NBFC-MFis simultaneously. Total outstanding debt: approximately < 1.20 lakh. Monthly household income: f6,500-7,000 (from a small grocery shop and seasonal agricultural wage work). Monthly EM! obligations across all three loans: approximately < 3,800.

Situation - Razia used her first SHG loan of < 30,000 to stock her grocery shop. When she needed additional working capital during the pre-Eid season, she accessed a JLG loan from an NBFC-MFI for NO,000 without disclosing her SHG loan (the credit bureau check did not flag the SHG bank loan). She subsequently took a second JLG loan from a different NBFC-MFI when facing difficulty with the first JLG repayment. The second loan was taken primarily to repay the first - a classic refinancing trap. Razia is unaware of PM MUDRA's Kishore category (which could have provided a single f2 lakh loan at bank rates through her existing bank relationship) and has not heard of Lakhpati Didi Yojana.

Systemic concern illustrated - SHG-JLG's information asymmetry permits both credit and non-integrated liability measurement simultaneously. Lack of counselling on alternative MUDRA options in Bengali pushes the borrower to opt for more expensive JLG credit when the purpose is to fund the requirements fulfilled by a cheaper MSME loan. Murshidabad's ratio of 78%for multiple loans (AMFI-WB, 2025) confirms Razia's story is not unique.

Vignette 2 - The Credit-Enterprise Gap: Birbhum

Background - Lakshmi (name changed), age 45, from Bolpur Sriniketan block, Birbhum. SHG member for 8 years under Anandadhara; credit-linked with a nationalised bank (Type 11). Makes terracotta craft items - toys, decorative items - through her SHG enterprise cluster. Loan outstanding: :t60,000 (third loan cycle). Annual enterprise income: approximately :t25,000.

Situation - While Lakshmi's SHG has a good record of repayments and is in its third stage of bank loans, there have been no improvements in terms of her enterprise earnings. This is because she sells mainly at local haats or during festivals, and does not have access to any electronic market, tourism markets or cities for selling her crafts. Her SHG has not even been connected to Karma Tirtha haat, which is nearest to her block and 12 kilometers from it. She was unaware of the enterprise part of SVEP, where they help in rural craft enterprises. According to Ghosh (2025), such cases are very common in Birbhum.

Systemic concern illustrated - The SHG federation's credit program is successful: Lakshmi enjoys steady access to credit as well as repays on time. But the entrepreneurship building activity does not work: without market linkages, Lakshmi uses borrowed money to finance her unsellable goods rather than growing an enterprise. In Birbhum 's Anandadhara statistics, the amount of credit available to 67,542 SHGs totals < 1,552.60 Cr, but no training activities have been held lately in that period (WBSRLM, 2024).

Vignette 3 - Scheme Convergence Failure: South Dinajpur

Background - Parveen (name changed), age 29, from Gangarampur block, South Dinajpur. JLG borrower from an NBFC-MFI (Type IV channel); not a member of any Anandadhara SHG. Runs a small tailoring enterprise from home. Loan amount: < 35,000 (current). Annual income: approximately < 42,000. Lakshmir Bhandar beneficiary ( < I,000/month).

Situation - Parveen's tailoring business has grown steadily and she now has three young women working with her on piece-rate. She needs < I.5 lakh to purchase two additional sewing machines and expand to a small production unit. Her NBFC-MFI can offer a maximum of f80,000 at 22% interest. She does not know she qualifies for MUDRA Kishore (< 50,001-< 5 lakh at 8-12%from banks), has not heard of Stand-Up India (for SC/ST women entrepreneurs, which she would qualify for), and is unaware that enrolling in an Anandadhara SHG would give her access to the SHG bank linkage system at subsidised rates. Her NBFC-MFI field officer does not proactively refer borrowers to alternative schemes.

Systemic concern illustrated - South Dinajpur records 81% multiple lending (AMFI-WB, 2025) and an 1.44% indebtedness rate - moderate but with a trajectory concern. Parveen's situation illustrates how scheme convergence failure keeps women in high-cost JLG credit even when enterprise peiformance would qualify them for better-suited formal bank products. The lack of cross-channel referral - no mechanism connects Type IV MFI borrowers to Type II Anandadhara entry or MUDRA eligibility - is a policy gap not visible in any individual institution's data.

11. Discussion and Policy Implications

Some of the insights emerging from the mapping and quantification exercise discussed in this paper have important policy, practice, and research implications.

Firstly, based on the results of our study, it can be concluded that the microfinance ecosystem in West Bengal is multi-layered architecture rather than a single sector with four structurally different delivery channels catering to women borrowers with distinct levels of risk, returns, and empowerment. This means that any policy intervention meant for one specific delivery channel (e.g., interest rate capping for NBFC-MFls) is unlikely to address needs or will even hurt women operating within another channel.

Secondly, using district-level results, we can identify geographic pockets of concerns that cannot simply be attributed to portfolios. For example, the Jangal Mahal region (including Jhargram, Purulia, Bankura, West Medinipur) demands intervention through combination of financial rehabilitation and livelihood support measures but definitely not by making more loans available. The fact that according to AMFI-WB (2025) findings only 32.1% of MFis provide one-time settlement to borrowers having overdrafts poses serious concerns for this region.

Third, the linguistic challenge observed in the research done by AMFI-WB (2025) - i.e., 84.9% documentation in English - can be used as an intervention strategy. Requiring key fact statement documentation in Bengali for micro-loans in the way the RBI's Key Fact Statement mandates have been enforced would go a long way in improving comprehension and knowledge on the part of the borrowers. According to Bharti and Malik (2022), there is evidence of improved efficiency from MFis that show good social performance.

Fourth, the situation regarding the Anandadhara district highlights a need for training in this respect. There are several large SHG districts where no formal training was conducted during the WBSRLM period, despite considerable amounts of credit being provided. Providing credit without training merely repeats the problem of the credit enterprise gap identified by the literature as the crucial obstacle to enterprise graduation (Ghosh, 2025; Patel & Patel, 2020).

12. Conclusion

This paper has provided a detailed ecosystem map of microfinance for women entrepreneurship in West Bengal, based on empirical data at district level from AMFI-WB (2025), Anandadhara database of WBSRLM (2024), and the MFI directory of Sa-Dhan (2024). The overall MFI portfolio of Rs 33,181 crore in 23 districts along with 11.52 lakh Anandadhara SHGs makes West Bengal among the richest and most complicated microfinance geography in India.

This four type delivery channel typology - Bank promoted SHG, Government promoted Bank Finance SHG, NGO intermediation model, and MFI-JLG lending model, provides a systematic classification system for analyzing the way in which access channel decides not only the interest rate but also the ecosystem surrounding that women entrepreneur. The 18 Sa-Dhan-registered WB-based MFis, documented here for the first time in a research paper, reveal an institutional landscape that spans Tier I NBFC-MFis to sma11 community societies

Three systemic concerns - universal multiple lending (70-87% across all districts), the credit-enterprise graduation gap visible in craft districts, and scheme comprehension failure driven by English-only documentation - have been identified as the primary research questions for the primary data collection phase. The three illustrative vignettes drawn from documented field situations in Murshidabad, Birbhum, and South Dinajpur give human texture to these systemic concerns.

The delivery channel typology, district data tables, and conceptual framework developed in this paper form the analytical architecture for the structured interview phase of this doctoral research. The subsequent paper will report on primary data from SHG members and MFI borrowers across selected West Bengal districts, empirically testing whether delivery channel type is associated with different enterprise outcomes, scheme utilisation rates, and experience of over-indebtedness. Together, the two studies aim to provide the most comprehensive empirical account of microfinance and women entrepreneurship in West Bengal available in the academic literature.

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