kathimerini.gr
Greece Launches AI-Powered Tax Evasion Crackdown
Greece's Independent Authority of Public Revenue (IAPR) will launch targeted electronic cross-checks in 2025 to combat tax evasion using AI and big data, aiming to collect €1.7 billion this year, focusing on taxpayers with 10,000-20,000 EUR incomes and disproportionate spending.
- What is the immediate impact of Greece's IAPR's 2025 initiative to combat tax evasion through electronic cross-referencing?
- The Independent Authority of Public Revenue (IAPR) in Greece is launching targeted electronic cross-checks in 2025 to identify undeclared income and combat tax evasion. This will involve AI, big data, and digital platforms to broaden the tax base and improve collection rates, focusing on taxpayers with disproportionate expenses relative to their declared income (10,000-20,000 EUR).
- How will the IAPR's use of technology, such as AI and big data analytics, affect the effectiveness of tax collection and enforcement?
- The IAPR's strategy uses data cross-referencing to detect inconsistencies between declared income and actual economic activity. This includes cash real estate transactions, undeclared income (domestic and foreign), Airbnb rentals, and individuals with 10,000-20,000 EUR incomes and high spending. The goal is to improve tax administration efficiency and increase tax revenue.
- What are the long-term implications of this IAPR initiative on the Greek economy, including its impact on tax revenue, tax compliance, and government spending?
- The IAPR's initiative leverages technology for enhanced tax compliance. The use of electronic books (myDATA), appodixi application, POS-cash register integration, and a complaint platform will strengthen enforcement. Over 120,000 cross-checks are planned, with estimated taxes sent to over 10,000 taxpayers who previously under-reported income. This targets significant tax evasion cases.
Cognitive Concepts
Framing Bias
The framing is overwhelmingly positive towards the AADE's initiative. The headline and introduction emphasize the effectiveness and technological advancements, creating a sense of inevitability and success. The potential for errors or the impact on honest taxpayers is downplayed. The use of strong verbs like "δρομολογεί" (initiates) and "πάταξη" (suppression) sets a decisive and aggressive tone.
Language Bias
While written in Greek, the translation reveals a tendency towards strong, action-oriented language that portrays the AADE's actions in a positive light. Terms like "πάταξη" (suppression) and phrases emphasizing the detection of tax evasion create a sense of urgency and effectiveness. More neutral phrasing could be used.
Bias by Omission
The article focuses heavily on the planned actions of the AADE, but omits discussion of potential counterarguments or challenges to these measures. It doesn't explore potential negative consequences of the increased scrutiny or the possibility of errors in the automated systems. Furthermore, it lacks information on the success rate of similar initiatives in the past, which would provide valuable context.
False Dichotomy
The article presents a somewhat simplistic 'good guys vs. bad guys' narrative: the AADE is working to combat tax evasion, implying a clear dichotomy between honest taxpayers and evaders. This ignores the complexities of the tax system, the possibility of unintentional errors, and the varying degrees of tax evasion.
Sustainable Development Goals
By using technology to detect and deter tax evasion, the Greek government aims to increase tax revenue and reduce the inequality gap. This action directly contributes to fairer distribution of wealth and resources, a core tenet of SDG 10. The focus on those with disproportionate spending relative to declared income specifically targets those who may be avoiding their fair share of tax contributions, thus contributing to a more equitable society.