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Euro Area Banks Tighten Credit Standards Amid Mounting Economic Risks

Euro area banks have implemented a modest tightening of credit standards for loans and credit lines to enterprises in the third quarter of 2025, as revealed by the European Central Bank’s October 2025 Bank Lending Survey, marking a net tightening of 4 percent.

Selective Contraction In Credit Policies

While banks maintained unchanged credit standards for housing loans intended for property purchase, they adopted a moderate tightening for consumer credit and other household lending, registering a net tightening of 5 percent. This shift from the previously unchanged standards in the second quarter highlights banks’ recalibrated risk management amid evolving economic conditions.

Heightened Economic Uncertainty And Sectoral Caution

In response to pervasive geopolitical uncertainties and fluctuating trade risks, banks have intensified their scrutiny of lending practices. The tightening of credit is primarily driven by rising risk perceptions related to the economic outlook, prompting institutions to exercise greater caution when extending new loans.

Loan Demand And Competitive Shifts

Despite a slight 2 percent net increase in loan demand from firms, overall enterprise borrowing remains subdued. Conversely, demand for housing loans surged by 28 percent, fueled by improved market sentiment and declining lending rates, whereas consumer credit demand remained almost stagnant at 1 percent due to diminished consumer confidence.

Funding, Liquidity, And Future Outlook

Access to retail and wholesale funding exhibited broad stability, with marginal easing noted in money markets, securitisations, and particularly debt securities. The ECB’s measured reduction of its monetary policy asset portfolio has exerted a neutral overall impact on market financing conditions, despite an observed rebalancing of sovereign bond holdings. Looking ahead to the fourth quarter of 2025, banks foresee credit standards remaining stable for firms, with incremental tightening for housing and further tightening for consumer credit alongside a continued rise in loan application rejections.

Conclusion

The survey findings underscore a prudential shift in euro area banks’ lending practices amid accelerating economic and geopolitical uncertainties. As institutions balance the challenges of tightened credit conditions with fluctuating loan demand, the evolving landscape calls for vigilant risk management and strategic recalibration to sustain financial stability.

Meta Unveils Muse Wonder Models In A Bid For Frontier AI Leadership

Meta has introduced two new AI models, Muse Wonder and Muse Wonder Full, signalling a more ambitious move into frontier AI. The releases build on Muse Spark but target more demanding tasks, including coding, while placing greater emphasis on long-term memory and personalised assistance.

Larger Models Target More Demanding Tasks

Unlike Muse Spark, which was designed for low latency and lightweight use, Muse Wonder and Wonder Full are significantly larger and, according to Meta, more capable. The company reports stronger benchmark performance and improvements on demanding workloads, including coding.

According to Meta’s model card, both models achieved benchmark results comparable to Fable 5.1 and GPT-6 Astra in the company’s internal testing. Meta described the release as “the next step on our scaling ladder and a major leap toward personal superintelligence” in its announcement.

Pricing Reflects Meta’s Frontier Ambitions

The models’ pricing places them in the premium AI segment. Through the Meta Model API, Muse Wonder will cost $4 per million input tokens and $20 per million output tokens, putting it in a similar pricing tier to GPT-6 Sol and Opus 5.5.

Muse Wonder Full, by contrast, will not be offered through the API. Meta says it will be exclusive to Muse Code subscribers, tying access to its most advanced model to a premium product. Both models will also power the Muse agent.

Long-Term Memory Takes Centre Stage

Meta is increasingly positioning its AI strategy around assistants that can support users over time rather than respond only to individual prompts. A central part of that approach is what the company calls “active memory”: the ability to retain, organise and synthesise information provided by users across extended periods.

Meta points to the MemoryBench benchmark, which evaluates systems designed for continual learning and memory construction. The company says Muse Wonder now outperforms Fable, Opus and Astra on this measure.

“We put a tremendous amount of effort into making sure your model can remember what’s important to you over days, weeks, months, and beyond,” research scientist Kavya Kopparapu said in a launch video.

New Models Follow Meta’s AI Reorganisation

The launch is also significant within Meta’s broader AI strategy. It is the company’s first frontier-model release since Scale AI founder Alexandr Wang reorganised its AI operations in August 2025. Meta has since introduced Muse Spark and the Muse agent, while making fewer high-profile model announcements than competitors such as OpenAI and Anthropic.

The new models were trained at Meta’s Prometheus data centre in central Ohio, which came online earlier in 2026, according to the company. The facility highlights the growing importance of infrastructure in the race to develop advanced AI systems, where performance depends not only on algorithms and data but also on computing capacity, data-centre investment and access to capital.

As competition intensifies, Muse Wonder and Wonder Full represent a broader bet on larger models, persistent memory and premium AI products. Their longer-term significance will depend on how their reported capabilities translate into real-world performance and whether users find enough value to pay for access.

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