Data collection might be the key to access to finance for women entrepreneurs

While there are numerous studies and initiatives focused on improving women entrepreneurs’ access to credit, these projects have been conducted in silos. Given this asymmetry, there is a need for the government and banks and financial institutions to work together to design a coherent and comprehensive program that provides a data-driven approach to solving the challenges associated with access to finance in India, especially for women. to give In addition, research from previous existing studies, supplemented with data collected by local, state, and national authorities can inform and optimize interventions to improve financial access in the country.

The problem of flooded databases

The MasterCard 2022 Women Entrepreneurs Index showed that India is among the countries with the lowest ranking of women entrepreneurship in the world. Especially in the post-pandemic period, collecting and analyzing data on women’s entrepreneurship is more necessary than ever. According to recent reports by the World Bank and several other organizations, women-owned businesses were hit hard during the pandemic. Factors such as personal challenges, including home care responsibilities are significantly considered as a major barrier to women running a business. The lack of comprehensive data on the financial performance of women-owned businesses, particularly in the MSME sector, has seen them as high risk, affecting their credibility. In a recent survey by ICRIER and NABARD, it was found that 60.5% of MSME owners find it difficult to access credit. Additionally, 47.7% of owners stated that it is harder to get a loan as a woman due to existing gender bias.

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Women’s contribution to the Indian economy is poorly measured with limited indicators in historical surveys that fail to inform decision making. There are even fewer nationally representative datasets that track the performance of different types of women-owned firms across states. Financial institutions need to create a support structure that allows them to positively assess the credit risk profile of women-led companies.

Despite existing scorecards such as the Women’s Entrepreneurship Index by the Global Institute for Entrepreneurship and Development, there is limited insight into within-country differences in policy, the entrepreneurial ecosystem, and the business capacity of entrepreneurs. As a result of these measurement gaps, there is no methodology to assess and address the gaps in India’s entrepreneurial ecosystem for women.

Gaps in existing policies

In addition, existing schemes do not have a customized approach that reflects the needs of rural women entrepreneurs. Statistics from the All India Debt and Investment Survey 2019 show that the number of women with bank deposits is growing rapidly, with 80.7 percent of women in rural India and 81.3 percent in urban India having bank deposits. have. However, this has not led to access to credit.

Traditionally, financial inclusion policies in India focused on the importance of savings over access to credit. Today, there is a need for women to access capital through alternative means and to change the perception of risk coverage in rural areas. While adequate funding is available through various schemes, there is a need for a robust credit enhancement mechanism to provide loans to women entrepreneurs. For example, strategic collaborations between banks and financial institutions and National Rural Livelihood Mission (NRLM) authorities can develop appropriate credit assessment techniques and tools for financial institutions, which in turn can help disburse loans to women entrepreneurs in Help all over the country.

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This is only possible through increased visibility in women-led businesses and then removing barriers with specialized financial products.

Simplify future data collection

Consistent quantitative and qualitative data on the typology (in terms of turnover, investment, sector, geography, etc.) of women entrepreneurs and their credit needs will help design a robust and forward-looking program for the financial empowerment of women entrepreneurs. In this effort, quantitative and qualitative data—credit applications, business cash flow cycles, movable assets, and financial footprints—will be essential for credit-enhancing mechanisms and assessment tools to overcome inherent barriers in the entrepreneurial ecosystem.

Before insights can be used to inform interventions, learnings from successful past validation trials must be organized. Several pilot studies have been initiated by financial institutions such as Mann Deshi, BASIC, MFIs and fintech companies such as Centrum, Aye Finance and RedCarpet, which have looked at CIBIL-like ratings and assets while evaluating credit proposals. Importantly, the results of these projects are neither documented nor readily available to inform future frameworks. These learnings are also yet to be transferred to public sector banks to create a comprehensive mechanism that brings processes, technology and people together. Doing so will enable the use of reliable and relevant data in the decision-making process for crediting women entrepreneurs.

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In the future, it is necessary to establish a mechanism and institutionalize a process for systematic data collection and evaluation. In addition, facilitating partnerships between financial institutions and policy makers is crucial to transfer research and transform it into meaningful frameworks. Such implementations are not possible without the help of political will. The government is pushing hard for digital adoption and is working to create comprehensive data infrastructure and platforms for ease of doing business, such as the National Data Analytics Platform (NDAP), which is a step towards real-time monitoring and data collection. It is of quality.

Data-based policy making and program creation is the starting point for unlocking the huge economic potential of women entrepreneurs in the country.

The author is a co-founder of the Global Alliance for Mass Entrepreneurship (GAME).

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