Data Dictionary

Column Type Label Description
id int4 index
region text Region
center text Center
branch text Branch
address text Address
longitude numeric Longitude
lattitude numeric Latitude
bank_group text Bank Group
population_group text Population Group
domestic_overseas text Branch Service Type
type text Service Unit
status_type text Status
bank text Bank Name
micrcode text MICR Code
license_number text License Number
ifsccode text IFSC Code
part_1_code text Part-1 Code
closed_reason text Reason for Closed
license_date text License Date
actual_open_date text Open Date
state_code text State Code
state_name text State Name
district_code text District Code
district_name text District Name
subdistrict_code text Sub District Code
subdistrict_name text Sub District Name

Additional Information

Field Value
Data last updated December 3, 2024
Metadata last updated December 3, 2024
Created unknown
Format CSV
License No License Provided
Created2 months ago
FrequencyOther
Size569,507
Additional infonan
Data extraction pagehttps://data.rbi.org.in/DBIE/#/banking-outlet
Data insightsData Insights that can be drawn from dataset :Geographical Distribution: The dataset allows for analysis of the geographical distribution of bank outlets and ATMs, highlighting areas with high or low banking service penetration.Operational Status: By examining the status of branches and ATMs, one can identify trends in banking infrastructure development and closures.Bank Group Analysis: The data enables comparison between different bank groups (e.g., public sector vs. private sector) in terms of their reach and presence.Service Availability: Insights into the types of services provided (e.g., full-service branches vs. ATMs) and their distribution across different regions.Demographic Correlation: Analysis of the dataset in conjunction with population data can reveal how well banking services are aligned with population density and distribution.Infrastructure Growth: Tracking the license and open dates provides insights into the growth and expansion of banking infrastructure over time.
Data last updated12-10-2023
Data retreival date01-12-2023
Datastore activeTrue
District no11
Gp no0
GranularityPoint
Has viewsTrue
Id5b62f0cb-7a39-4509-be7a-9aee0a9992b9
Idp readyFalse
MethodologyThe dataset is compiled by the Reserve Bank of India (RBI) from its extensive network of regulated banks and financial institutions. It includes data on the geographical location, operational status, and other relevant details of bank outlets and ATMs. The information is gathered through regulatory filings, surveys, and administrative records maintained by the RBI.
No indicators2
Package id91edc2db-6e83-4cb1-9d67-8b86d64e5ef4
Position2
Skurbi-bank_outlets_and_atms-pl-ot-meg
Stateactive
States uts no1
Tehsil no38
Url typeupload
Years covered1900-2023
Methodology The dataset is compiled by the Reserve Bank of India (RBI) from its extensive network of regulated banks and financial institutions. It includes data on the geographical location, operational status, and other relevant details of bank outlets and ATMs. The information is gathered through regulatory filings, surveys, and administrative records maintained by the RBI.
Similar Resources
Granularity Level Point
Data Extraction Page https://data.rbi.org.in/DBIE/#/banking-outlet
Data Retreival Date 01-12-2023
Data Last Updated 12-10-2023
Sku rbi-bank_outlets_and_atms-pl-ot-meg
Dataset Frequency
Years Covered 1900-2023
No of States/UT(s) 1
No of Districts 11
No of Tehsils/blocks 38
No of Gram Panchayats 0
Additional Information nan
Number of Indicators 2
Insights from the dataset Data Insights that can be drawn from dataset :Geographical Distribution: The dataset allows for analysis of the geographical distribution of bank outlets and ATMs, highlighting areas with high or low banking service penetration.Operational Status: By examining the status of branches and ATMs, one can identify trends in banking infrastructure development and closures.Bank Group Analysis: The data enables comparison between different bank groups (e.g., public sector vs. private sector) in terms of their reach and presence.Service Availability: Insights into the types of services provided (e.g., full-service branches vs. ATMs) and their distribution across different regions.Demographic Correlation: Analysis of the dataset in conjunction with population data can reveal how well banking services are aligned with population density and distribution.Infrastructure Growth: Tracking the license and open dates provides insights into the growth and expansion of banking infrastructure over time.
IDP Ready No