ECB stress test shows most banks don’t include climate risk in credit models


Environmental protesters take to the streets throughout an illustration by Fridays for Future within the monetary district of Frankfurt, Germany, in August final yr.

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The outcomes of the European Central Financial institution’s first local weather danger stress take a look at present that the majority euro zone banks don’t sufficiently incorporate local weather danger into their stress-testing frameworks and inside fashions.

In a report published Friday, the ECB mentioned the findings reaffirm the view that banks should sharpen their concentrate on local weather danger.

It comes at a time of extreme warmth and scarce rainfall in southern Europe, rising vitality costs and the prospect of a halt to the region’s gas supplies from Russia in retaliation in opposition to sanctions imposed over the Kremlin’s onslaught in Ukraine.

To make certain, the world’s main local weather scientists have warned humanity has reached “now or never” territory to stave off the worst of what the local weather disaster has in retailer.

“Euro space banks should urgently step up efforts to measure and handle local weather danger, closing the present knowledge gaps and adopting good practices which might be already current within the sector,” Andrea Enria, chair of the ECB’s supervisory board, mentioned in an announcement.

A complete of 104 banks participated within the take a look at, which is the primary of its variety, the ECB mentioned, offering data over three modules, or classes. These included their very own local weather stress-testing capabilities; their reliance on carbon-emitting sectors; and their efficiency underneath completely different eventualities over a number of time horizons.

The outcomes of the primary module discovered that roughly 60% of banks don’t but have a local weather danger stress-testing framework.

Equally, the ECB mentioned most banks don’t embody local weather danger of their credit score danger fashions and simply 20% take into account local weather danger as a variable when granting loans.

As for the reliance of banks on carbon-emitting sectors, the ECB mentioned that on combination, virtually two-thirds of banks’ revenue from non-financial company prospects stems from greenhouse gas-intensive industries.

In lots of instances, the report discovered banks’ “financed emissions” come from a small variety of massive counterparties, which will increase their publicity to emission-intensive sectors.

Throughout the third module, the outcomes had been restricted to 41 straight supervised banks to make sure proportionality towards smaller banks. It required lenders to challenge losses in excessive climate occasions underneath completely different transition eventualities.

The outcomes warned that credit score and market losses may quantity to round 70 billion euros ($70.6 billion) on combination this yr for the 41 straight supervised banks.

The ECB famous, nonetheless, that this “considerably understates the precise climate-related danger” because it displays solely a fraction of the particular hazard. This was due, partly, to a shortage of accessible knowledge.

“This train is an important milestone on our path to make our monetary system extra resilient to local weather danger,” mentioned Frank Elderson, vice-chair of the ECB supervisory board. “We count on banks to take decisive motion and develop strong local weather stress-testing frameworks within the quick to medium time period.”

ECB President Christine Lagarde beforehand mentioned the central financial institution was taking steps to include local weather change “into our financial coverage operations.”

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The ECB mentioned it collected each qualitative and quantitative data, with a view to assessing the sector’s local weather danger preparedness and gathering finest practices for coping with climate-related danger.

The report concluded that the majority banks would wish to work additional on bettering their stress take a look at frameworks’ governance construction, knowledge availability and modeling methods.

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