The tax administration is strengthening the use of artificial intelligence, data analytics and integrated government datasets to identify inconsistencies, assess potential tax risks and make taxpayer scrutiny more targeted.
The emerging approach goes beyond examining individual returns. Tax authorities can analyse information across Income Tax Returns, GST returns, e-invoices, e-way bills, registrations, Annual Information Statement (AIS) data and historical taxpayer records to identify unusual patterns and discrepancies requiring further examination.
On the GST side, analytics-based systems are being used to identify potential risks involving fake registrations, suspicious input tax credit chains, unusual transactions and possible tax-evasion patterns. Platforms such as DGRAM and BIFA support risk identification and exception-based analysis using GST-related data.
GST scrutiny can also involve reconciliation of GSTR-1, GSTR-3B, GSTR-2B, e-way bills and e-invoices. Automated analysis may highlight differences in reported turnover, outward supplies and ITC, including transactions involving suppliers whose registrations were later cancelled or whose tax liabilities were not properly discharged.
State tax administrations are also developing data-analytics capabilities for identifying cases that may require scrutiny or audit. The broader integration of GST, income-tax, customs and other government information could provide authorities with a more comprehensive view of taxpayer transactions and compliance patterns.
For businesses, the increasing use of automated risk detection makes continuous reconciliation and proactive identification of tax discrepancies more important. Potential areas of scrutiny may include unusual refund claims, excess ITC, GST short payments and inconsistencies between accounting records and tax filings.
However, AI-based systems are expected to function primarily as risk-identification and decision-support tools rather than replacements for tax officers. Final verification, assessment and tax-related decisions would continue to require human examination and professional accountability. CASansaar