A scuff on your bag, a dent in your mug – and suddenly it feels like time for a new one

Would this bother you? 500px/Getty ImagesImagine you have a bag you really like. It felt like “the one” when you bought it.

Over time, it starts to look worn. There are some scuffs on it. Nothing is actually wrong with the bag, and it still works exactly as it should. Yet, once you notice those imperfections, you start thinking about buying a new one to replace it.

Headwind or tailwind? How banks interpret borrowers’ AI exposure

General-purpose technologies create large opportunities but make their distribution across firms difficult to assess in real time. We use banks as interpreters of the rise of generative AI by studying lender-specific probability-of-default (PD) estimates for private firms in four large euro-area economies. As public attention to AI rises after ChatGPT, banks lower assessed default risk for borrowers in highly AI-exposed industries by about 5%. The reassessment is weaker for labor-intensive firms and stronger among lenders with pre-existing industry expertise.

Regulatory incentives and the structure of euro area money markets

This paper quantifies the regulatory cost of short-term money market transactions and analyses how post-global financial crisis prudential reforms shape the structure of euro area money markets and the redistribution of central bank reserves. As the stock of reserves declines with the normalisation of the European Central Bank’s balance sheet, trading in money markets is becoming increasingly important to banks’ liquidity management. As the related money market volumes rise, regulatory constraints may become a more visible determinant of trading activity and short-term rate formation.

Headwind or tailwind? How banks interpret borrowers’ AI exposure

General-purpose technologies create large opportunities but make their distribution across firms difficult to assess in real time. We use banks as interpreters of the rise of generative AI by studying lender-specific probability-of-default (PD) estimates for private firms in four large euro-area economies. As public attention to AI rises after ChatGPT, banks lower assessed default risk for borrowers in highly AI-exposed industries by about 5%. The reassessment is weaker for labor-intensive firms and stronger among lenders with pre-existing industry expertise.

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