The India Map of Financial Inclusion visualizes two main facets of financial inclusion at the state and district level within India: banking correspondents (BCs) and microfinance institutions (MFIs). These datasets draw on the State Level Bankers’ Committees “Financial Inclusion Plan” data and MIX’s collected data tracking the quarterly progress of MFIs currently operating within each district. By uniting these two important datasets against a backdrop of demographic and development data for the first time, it becomes possible to gain insights on the geographic relationships of two key channels in the financial inclusion landscape. This will allow the user to gain a more comprehensive view onto the access point and supply of financial services to low income households and their businesses.
Each state in India has a State level Banker’s Committee (SLBC), the purpose of which is to act as the main coordination body for financial institutions within a given state. These committees, each convened and housed by a designated “lead bank”, are also responsible for authoring certain development plans for their state. One such plan, the Financial Inclusion Plan (FIP), outlines the location and number of banking correspondents (BCs) to be set up in each district within villages of more than 2000 persons by December 2012, as mandated by the government. The data layer that you see on this map was collected from each SLBC’s individual website, where FIPs are made public. Links to each SLBCs’ respective websites, individual FIP, and the datasets themselves are included in a spreadsheet available for download here. When hovering over each district on this data layer, an interactive pop-up box provides users with supplemental information indicating the name of the district and state, the total number of planned BCs and the bank set to host the majority of BCs within that district. If two or more such banks tied hosting the majority of BCs, we used both (or all) of their names as this value. In addition to the source file and our aggregated file representing what we chose to map of the FIP plans, we are also providing a folder full of the raw data from each SLBC website as well as the cleaned-up machine readable formats used to create the file for our map. Please note that FIPs’ implementation is at various levels of completeness across India.
Four layers within this map offer insight into the number of points of service (defined as branch locations) for each MFI as of June 30, 2012, and then the number of MFIs operating in each district the total number of outstanding loans per district and the total amount of loan portfolio in each district for the fiscal quarter ending on March 31, 2013. Please note again that if two or more MFIs tied for having the most branches in a district or state, we used both (or all) of their names as the value of “MFI with Most Branches” within the points of service layer. These data are sourced directly from the respective MFIs, which have been gathered together by our field unit in India. MIX works in partnership with the Small Industries Bank of India (SIDBI) to collect these layers of data.
The map shown on the initial load of this page shows the combined MFI points of service and the SLBC layers to allow for a more immediate comparison of the two datasets. Please note that a value of “No Data” has been given to districts with no SLBC data, as the data do not clearly indicate whether there are no BCs in these districts or that there is a discrepancy between what the state and what MIX’s shapefile consider to be its districts. This point is elaborated further in the shapefiles and boundaries section.
All the colors displayed in this map are scaled based on the 25th, 50th, 75th and 90th percentiles of the respective dataset they represent. The circles are scaled based on these and the 10th percentile, additionally. This guarantees a view into the relative extremes of each dataset, rather than employing an absolute scale. The 25th, 50th, 75th and 90th percentiles for the shaded contextual data are displayed in the legend of each layer.
The population and literacy contextual layers are sourced from the 2011 Indian Census. These data were aggregated from the state specific entries posted on this site and are available for download as an aggregate whole here. Included in the download are the following indicators:
Please note that all Indian census figures are preliminary.
The CRISIL Index measures financial inclusion in India based on CRISIL’s own methodology as outlined in their June 2013 report (downloadable here). The three major parameters of the score are (1) bank penetration, (2) deposit penetration and (3) credit penetration. CRISIL has defined scores that determine a high, above average, below average and low level of financial inclusion. Please note, however, this map shows the 25th, 50th, 75th and 90th percentiles of the data itself and thus uses a different scale than CRISIL’s. Additionally, 37 districts from the CRISIL dataset are not present in this map. They are relatively new districts and as such are not contained within the GADM shapefile. Finally, some districts have averaged values as they had two sets of district values representing them in the CRISIL dataset. These include:
All of these contextual layers are sourced from the District Level Household and Facility Survey, specifically the 2007-8 survey, which was conducted by the International Institute for Population Sciences and funded by the Indian Ministry of Health and Family Welfare. These four layers, then, represent survey estimates of district values.
The map files representing national, state and district boundaries are sourced largely from Global Administrative Areas (GADM), an international database of geographic files (shapefiles) covering every country in the world. The data are maintained by contributors working at the International Rice Research Institute and the University of California, Berkeley’s Museum of Vertebrate Biology. The shapefiles are drawn primarily from the Centers for Disease Control and the UN Geographic Information Working Group’s “Second Administrative Level Boundaries” project. Some additional boundaries were added using the Demographic Health Survey of 2006 and a small manual construction on the part of MIX of the Shaksgam Valley, which is based on this map image. The map used is thus a product primarily based on the GADM and DHS databases.
While there is, in general, significant agreement between datasets, there is no definitive list of districts or corresponding shapefiles produced by the Indian Government. Various sources from the state and central government of India, the SLBC sites and this international dataset disagree about the exact boundaries and number of districts. We have only included districts that are present within the MIX’s constructed shapefile (sourced very largely from GADM and DHS) and so the districts in this shapefile that are not present in the Indian Census or District Level Household and Facility Survey data receive values of “No Data” for all values in the interactive on-hover boxes and choropleth shadings. It is important to keep in mind that, in these instances, this stems from a lack of consensus regarding India’s districts and not a genuine lack of data for that “district.” Conversely, districts present within the Indian Census or District Level Household and Facility Survey that are not also within the MIX’s shapefile are not mapped, though the data pertaining to them from these sources are available for download here.