ECB puts counterparty credit risk guide under the microscope
12 February 2020 Frankfurt
Image: Shutterstock
The European Central Bank (ECB) has launched a public consultation on its guide to assess how banks calculate counterparty credit risk (CCR).
The guide outlines the methodology it uses to assess the internal models banks apply to calculate their exposure to counterparty credit risk.
Additionally, the guide describes how the ECB will assess the advanced methods banks use to calculate the own funds required to account for the risks related to credit valuation adjustments.
In addition, it indicates how ECB banking supervision intends to assess the internal CCR models used by directly supervised banks, ECB noted.
According to the ECB, it will draw on the approaches already defined by the European Banking Authority for other risk types.
CCR emerges when banks trade in derivatives and in transactions where securities are used to borrow or lend cash, such as repurchase agreements.
The ECB highlighted that the “guide aims to harmonise supervisory practices related to internal CCR models and to provide transparency regarding the methodologies the ECB uses to assess the components of these models during investigations”.
“The guide should not be construed as going beyond the current applicable European Union and national laws and is therefore not intended to replace, overrule or affect said laws,” the ECB adds.
Meanwhile, it was noted that the guide was drafted in close cooperation with the national competent authorities and benefited from the feedback received from institutions on a first version of the guide that was made available in December 2017.
The consultation on the guide will end on midnight CET on 18 March 2020.
The ECB's call for industry input came short before it was revealed that IHS Markit is set to incorporate Credit Benchmark’s credit risk analytics, Consensus Analytics, into its platform.
In a statement on the deal, IHS Markit explains that by enriching its platform with Credit Benchmark's consensus analytics it can independently evaluate risk-return exposure based on the credit quality and liquidity of counterparty assets.
The guide outlines the methodology it uses to assess the internal models banks apply to calculate their exposure to counterparty credit risk.
Additionally, the guide describes how the ECB will assess the advanced methods banks use to calculate the own funds required to account for the risks related to credit valuation adjustments.
In addition, it indicates how ECB banking supervision intends to assess the internal CCR models used by directly supervised banks, ECB noted.
According to the ECB, it will draw on the approaches already defined by the European Banking Authority for other risk types.
CCR emerges when banks trade in derivatives and in transactions where securities are used to borrow or lend cash, such as repurchase agreements.
The ECB highlighted that the “guide aims to harmonise supervisory practices related to internal CCR models and to provide transparency regarding the methodologies the ECB uses to assess the components of these models during investigations”.
“The guide should not be construed as going beyond the current applicable European Union and national laws and is therefore not intended to replace, overrule or affect said laws,” the ECB adds.
Meanwhile, it was noted that the guide was drafted in close cooperation with the national competent authorities and benefited from the feedback received from institutions on a first version of the guide that was made available in December 2017.
The consultation on the guide will end on midnight CET on 18 March 2020.
The ECB's call for industry input came short before it was revealed that IHS Markit is set to incorporate Credit Benchmark’s credit risk analytics, Consensus Analytics, into its platform.
In a statement on the deal, IHS Markit explains that by enriching its platform with Credit Benchmark's consensus analytics it can independently evaluate risk-return exposure based on the credit quality and liquidity of counterparty assets.
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