MoneyControl Article RatingFrom GST 2.0 to GST 3.0: What the 57th GST Council must deliver - Moneycontrol.com
- Bias Rating
-50% Medium Left
- Reliability
5% ReliableLimited
- Policy Leaning
-50% Medium Left
- Politician Portrayal
N/A
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
27% Positive
- Liberal
- Conservative
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Bias Meter
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Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
63% : The rate architecture is simpler, GSTAT is finally operational, tax collections remain robust, and the digital compliance ecosystem - from e-invoicing to IMS - has significantly enhanced transparency and enforcement.60% : Spread the Gains of Digitalisation To its credit, GST has steadily evolved into a technology-driven tax ecosystem.
55% : Tax liabilities are increasingly system-generated, returns are auto-populated, and data analytics have become central to compliance monitoring and enforcement.
55% : Yet the success of a tax system is measured not only by how well it is designed, but by how seamlessly it functions for those who comply with it.
55% : A tax system that is faster, more predictable and genuinely taxpayer-centric will do more to improve voluntary compliance than any additional layer of regulation.
50% : The next phase of GST reforms should focus on making compliance simpler, administration more predictable and technology work as effectively for taxpayers as it does for the tax administration.
49% : Refunds under Inverted Duty Structure Inverted duty structure where a business pays more tax on inputs than it collects on outputs, generating accumulated credit that it cannot utilise, remains the most persistent structural grievance under GST.
45% : However, the gains from digitalisation have largely accrued to the tax administration rather than taxpayers.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.
