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Cyprus Recorded Highest Non-Performing Loans In The European Union: An In-Depth Analysis

Cyprus recorded the highest non-performing loans across the European Union in 2024, signaling significant vulnerabilities within public sector balance sheets, according to Eurostat data.

Government Guarantees Under the Microscope

Eurostat’s report reveals that government guarantees remain the most prevalent form of contingent liabilities among EU nations, typically providing backing for both liabilities and occasionally assets of third parties. Notably, the Netherlands led with government guarantees reaching 31.0 per cent of GDP, followed by Finland at 17.0 per cent and Italy at 14.6 per cent of GDP. In stark contrast, Ireland, the Czech Republic, and Bulgaria each maintained guarantees at or below 1 per cent of GDP.

Central And Local Government Roles

The analysis confirms that, in most cases, central governments serve as the primary guarantors. However, certain countries, including Finland, Sweden, France, and Denmark, exhibited significant involvement from local government bodies, underscoring diverse governance approaches in risk management across the EU.

Public Corporations And Off-Balance Liabilities

Beyond contingent liabilities, Eurostat detailed stark differences in liabilities held by public corporations outside the general government. Germany, for instance, faced the highest level at 84.4 per cent of GDP, while the Netherlands, Luxembourg, and France followed closely. Conversely, Cyprus, Slovakia, Spain, and Romania reported substantially lower levels, with Cyprus at an exceptionally modest 7.3 per cent of GDP.

Cyprus’ Elevated Non-Performing Loans

Of particular concern, Cyprus recorded non-performing loans equating to 9.0 per cent of GDP – a figure that dwarfs those of other EU nations, where levels remained below 1 per cent. Additional data from Croatia, Greece, and Sweden indicate marginally higher figures, yet they pale in comparison to Cyprus’s predicament.

Off-Balance Public-Private Partnership Liabilities

Liabilities linked to off-balance sheet public-private partnerships remain largely contained, not exceeding 2 per cent of GDP in any member state. Portugal, Slovakia, and Latvia reported the highest shares in this category, with liabilities primarily tied to motorway construction projects.

Copyright Law Struggles To Keep Up With AI Training

Courts Are Still Applying Old Copyright Rules To AI

AI companies train models on enormous amounts of published material, including books, articles and academic research. Whether using that content without authors’ permission violates copyright law remains unresolved.

Much of the debate centres on fair use, which allows copyrighted material to be used without permission in certain circumstances. Courts consider factors such as the purpose of the use, how much material was involved and its impact on the original market.

Anthropic Case Sets An Important Precedent

A major case involving Anthropic and a group of authors provided one of the clearest rulings so far. Judge William Alsup found that using copyrighted books to train AI models was lawful, comparing the process to people reading and studying literature before creating something new.

Anthropic was nevertheless ordered to pay $1.5 billion in a settlement. The penalty concerned books the company had obtained from illegal online libraries rather than the AI training itself.

For AI companies, that distinction could prove significant because it separates studying copyrighted material from directly copying it.

Competition Could Be The Key Issue

A case involving Thomson Reuters and Ross Intelligence offers a different perspective. A court ruled that Ross could not claim fair use after using Reuters’ copyrighted material to develop a competing AI-powered legal research platform.

The decision suggests courts may be less willing to consider AI training fair use when copyrighted content is used to build a product that directly competes with the original.

For authors, an unresolved question is whether AI-generated content should be considered competition for the works used to train these models.

The Law Has Yet To Catch Up

US copyright law predates generative AI by decades, leaving courts to apply old principles to new technology. Questions also remain over copyright protection for AI-generated works. In Thaler v. Perlmutter, a court ruled that material created entirely by AI cannot receive copyright protection.

Major AI companies remain involved in copyright litigation, and different courts could reach different conclusions. For now, there is no universal rule: the legality of AI training will depend on the circumstances of each case and how courts ultimately interpret copyright and fair use.

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