
Raja Abhishek For NIRC 2024
over 1 year ago
ā¢View on š
šš¼š® ššæš®š°šøš šš¼šš» š¼š» šš¦š§ ššš®š±š²šæš š¶š» š§š®š š¶ šš»š±ššššæš ššš»š±šæš²š±š š¼š³ š°š®šÆ š¼šš»š²šæš š®š»š± šæš²š»šš®š¹ šÆššš¶š»š²ššš²š š³š®š°š² š»š¼šš¶š°š²š š³š¼šæ š®š¹š¹š²š“š²š± šš®š š²šš®šš¶š¼š». [img:EzEmumjgDw]
In a recent crackdown, the Goa state tax department has issued notices to approximately 260 taxi operators suspected of bypassing Goods and Services Tax (GST) regulations. This action follows a three-month investigation using data intelligence gathered from various sources, including the Income Tax department, Regional Transport Office (RTO), banks, and other agencies.
Data Intelligence Exposes Tax Evaders The investigation revealed that numerous individuals operating taxi, rent-a-cab, and rent-a-bike businesses, possessing more than 10-12 vehicles, were not registered under GST and failed to pay the required taxes.
Under GST laws, businesses with an annual turnover exceeding Rs. 40 lakh for goods and Rs. 20 lakh for services must register and pay GST. The tax department determined that taxi businesses with 5-6 vehicles or more likely exceed the Rs. 20 lakh threshold, making them liable for GST.
RTO Data Key to Identifying Defaulters The department utilized RTO data to identify potential tax evaders by cross-referencing vehicle ownership with PAN card details and GST registration status. This revealed a significant number of unregistered businesses operating without paying GST.
Notices Issued, Further Action Underway The identified individuals have been issued notices and given 2-3 weeks to respond and provide evidence supporting their non-liability for GST. The tax department will then determine the tax liability of each operator and take further action accordingly.
Digitization Aids Tax Compliance This initiative highlights the increasing use of digitization and data analytics by tax authorities to ensure compliance and curb tax evasion. The ease of collating and comparing data from various sources allows for efficient identification of potential defaulters.
Page created with TweetHunter
Write your own