Digital Banks Poised To Reshape Competitive Landscape For Traditional Lenders In Cyprus

by THEFUTURE.TEAM

March 11, 2026

Banking Concentration And Monetary Policy Transmission

A study released by the Central Bank Of Cyprus has shed light on the challenges posed by high market concentration in the banking sector. Authored by Aris Avgousti and Stephani Michael of the Centre For Strategy And Policy Production, the analysis indicates that a concentrated financial market delays the transfer of central bank interest rate adjustments to retail deposit and lending rates, particularly affecting non-financial corporations.

The Dynamics Of Market Power And Competition

The report underscores how a competitive banking ecosystem is paramount to the efficient transmission of monetary policy decisions. In areas where dominant banks exert significant market power, policy rate changes are reflected in bank rates more sluggishly and less effectively. This phenomenon not only affects the cost of credit but also has broader implications for inflation and the overall functioning of the financial system.

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Policy Implications And Structural Adjustments

The findings suggest that enhanced competition can tighten spreads between loan and deposit rates, ultimately improving credit access for consumers and businesses. In markets with higher competitiveness, banks tend to adjust their rates with greater agility, thereby supporting more effective monetary policy. These structural insights are particularly relevant as the economic landscape adapts to the evolving directives of the European Central Bank.

The Impact Of Digital Innovation

The increasing presence of digital banks is set to disrupt traditional banking practices. Digital platforms adjust rates more rapidly than their brick-and-mortar counterparts, intensifying competition and compelling domestic banks to innovate. However, the study cautions that this shift must be balanced with rigorous regulatory practices to mitigate the potential for excessive risk-taking by new market entrants.

Conclusion

In today’s evolving financial environment, promoting a competitive and transparent banking sector is crucial for safeguarding economic stability and driving growth. As digital transformation accelerates, stakeholders must ensure that new and existing players operate on a level playing field—balancing innovation with prudent oversight to sustain long-term financial resilience.

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Copyright Law Struggles To Keep Up With AI Training

by News Editor

August 24, 2026

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.

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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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