A few days ago, we all read about how low the property tax collection rate was in Bangalore. A mere 20% paid their property tax in Bengaluru. Unacceptable for a city like Bengaluru.
“#GIS #bigdata #machinelearning analysis: Bengaluru & Jaipur collect only 5% to 20% of their potential property taxes. #EcoSurvey Ch 14″
Very interesting data has been captured in Chapter 14 of the Economic Survey FY2016-17 (page xiv). Frankly, it is very heartening to see the government has captured such details. Not sure why they haven’t acted upon it to increase the property tax collections. Extracts from this section are mentioned below,
- The primary source of own revenue for urban local bodies is the property tax. Based on assessment of 36 cities, the study revealed the current property tax (Rs 4,400 crore / $680 million) could be increased to as much as Rs 22,000 crore / $3.4 billion.
- Using satellite imagery from LANDSAT program from joint National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS).
- The survey estimates the built-up area in Bangalore which can be compared with the local authority BBMP’s tax paid records, a mere 20% were paying their property taxes.
Link Power & Water Bill with Property Tax Records
Possibly the government is already working on a solution to identify the property tax evaders. If the databases of various departments talk to each other it is not that difficult to identify the property tax evaders.
- To begin with, identify the buildings that have electricity connection from BESCOM.
- Reasonably sure the address in BESCOM and property tax records will not match. Addresses in India are generally complex & can be hilarious.
- Anyway, figure out a way to map BESCOM customers with BBMP’s database. It can be done.
- BESCOM should mandate property owners to provide “SAS base application number (property id)” issued by BBMP. Terminate the electricity connection if this property id is not provided within a year. This way the govt can capture the section of property owners who just don’t pay their property taxes.
- For those who pay property tax make it mandatory for taxpayers to enter their BESCOM customer ID when they pay their property tax. Make this mandatory. But then these are not the people evading tax but could be underreporting the area of their property (will get to this soon).
- It is now important for the databases of BESCOM & BBMP to exchange data (we could connect the two using Aadhaar too).
- Under Reporting the built-up area – BBMP can pull the yearly data of electricity consumption (month-wise) from BESCOM database.
- Using machine learning on the huge databases from BESCOM and BBMP is not that difficult to figure out what is the acceptable range of power consumption in units per square feet of built-up area.
- For e.g., if an independent house has a super built-up area of 3,000 sq feet but pays property tax for just 1,000 sq feet is that difficult to identify this tax evader? How can a property of 1,000 sq feet size continuously consume the power of a typical 3,000 sq feet house? There are always exceptions but this can at least plug the leakage to a great extent.
- The same experiment could be done with water bills too (BWSSB). But many localities in Bengaluru don’t have water connection from BWSSB yet.
Identifying Tax Defaulters of Vacant Sites & Buildings
By doing a little deep analysis of the data of property taxpayers it is easy to come up with the list of properties who have defaulted. For e.g. in a particular street if house number #100, #102, #103, #108 have paid the property tax the algorithm can identify the missing properties – #101, #104, #105, #106, #107.
The only problem is that addresses in India are not that straight forward (For e.g. Old No 3, New No 1037/A). However machine learning can figure out a pattern of addresses and a simple algorithm can nail property tax defaulters, i.e. only if the government is interested.
Also see,
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