Independent Research and Policy Advocacy

Workshop on Measuring Access to Finance

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Given the scope of Microfinance in India, it is imperative to measure access and impact of finance to understand its benefits and challenges.   Amy Jensen Mowl, Programme Head, Longitudinal Studies, at the Centre for Micro Finance (CMF) on March 24, 2010, conducted a three-hour workshop for the members of IFMR Trust (presently known as Dvara Holdings), where she shared some of the key themes, data sources, important indicators and research processes for measuring access to finance.

She divided the session into five broad aspects: Motivation—importance and relevance of data on measuring access to finance; measuring approaches; the underlying concepts on access to finance; headline and core Indicators; and sources of data on access to finance in India.

Measuring access to financial services is of vital significance. While addressing this issue, Amy emphasized the importance of data at addressing policy issues and evaluating impact of access within and across countries. In this context, she highlighted some of the pertinent questions that need to be addressed to impact the specific and unique needs of the poor. Some of the questions that she elaborated included how access to finance is important to the poor and who are excluded, which type of financial services should be available for maximum impact on poverty alleviation, what services are most important for them and what challenges they face while seeking them.

Amy at the workshop

Currently, while data exists on the broad benefits of financial access, there is a dearth of data on the effect of access to financial services on particular population groups, such as the poor.  This is largely because  data collection is very time consuming and expensive, apart from the lack of clarity of the underlying concepts.

When measuring access, Amy discussed the need for both supply and demand side data. We can use supplier data (regulator surveys and bank surveys) and user data (enterprise survey and household survey) for this purpose. For example, regulator surveys (such as RBI surveys) provide reliable data, though with some limitations such as non-coverage of the informal sector. User data can be sourced from village level surveys, household surveys and enterprise surveys. While discussing the issue of generalizing data from one location in India, Amy acknowledged that while rich data are available (such as from the Centre for Monitoring the Indian Economy) they cannot be generalized.

While enlisting good quality data sources, Amy mentioned The Centre for Monitoring Indian Economy (CMIE), National Council of Applied Economic Research (NCAER), and National Sample Survey Organisation (NSSO) in India and Finscope survey, British Household Panel Survey and DFID’s Young Lives Programme (on childhood poverty) outside India.

Amy also shared some of methods and processes used for data collection in her research, which is a 15-year study on understanding the impact of access to financial services in the urban and rural areas in Tamil Nadu. Started three years ago, her study covered 10,000 households – half of them in the rural areas. Highlighting the elaborate and time-consuming process involved in data collection, she pointed to her intensive research surveys that took an average of eight hours to survey each household.

While discussing the core and headline indicators, she described the four-fold classification of population groups in her survey:

  • Banked – households that have access to bank services
  • Formally included –  households that have access to banks, formal institutions and other financial institutions
  • Financially served – households that have access to banks, other formal institutions as well as informal sources (informal sources do not include borrowing from family and friends)
  • Financially excluded – individuals who do not fall under any of the three aforementioned categories

On the issue of generalizing the results of her study in Tamil Nadu, it was pointed out that it was possible primarily because of the large sample size that takes care to cover sufficiently diversified population groups in the rural and urban areas in India.

Amy concluded by highlighting the importance of data collection in the context of evolving financial services in India, and stressed the need to raise the bar in data collection, and effective use of the data collected.

Anita Sharma and Natalie Colatosti of IFMR Advocacy contributed to this post.

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2 Responses

  1. Thanks Amy for doing this. Good measures of the state of access to finance is an important pre-requisite for us to advocate for change

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