Dear,
Next Sunday October 26th, 2014 at 12:00 PM (CET) the European Central Bank (ECB) will make public the results of its assessment, checking the health of the 130 biggest banks of the euro area.
https://www.ecb.europa.eu/press/pr/date/2014/html/pr141010.en.html
Controlling the solvency of the financial system is the main responsibility of a bank’s supervisor. If he detects that a bank is undercapitalized, immediate actions must be taken, from requesting its recapitalization or blocking the bank’s dividends policy, till forcing its liquidation.
The regulatory capital that a bank must hold is a percentage of its Risk Weighted Assets, which must be big enough for covering future losses generated by borrowers not fulfilling their obligations. Currently, the regulatory capital calculation is determined by the Basel 3 agreement; but both, the required percentage of the Risk Weighted Assets and its calculation has changed over the time.
http://www.bis.org/bcbs/basel3.htm
We’ll analyze in a future post why the measuring of solvency has changed over the years, but today we’ll look at the difficulties of performing this calculation.
Calculating the Risk Weighted Assets requires looking at the future, and building a statistical model for determining the probability of default of the bank counterparts (PD), the bank’s exposure to the counterpart at the moment of default (EAD), and the share of the asset that is lost when the counterpart defaults (Loss Given Default).
Let’s have a look at the main challenges of the European case, there’re two difficulties for achieving efficient and comparable results of the capital analysis.
- Different national regulations. For instance, every country has different insolvency, liquidation and debt restructuring regulations. This has a direct impact in the value of the collaterals, the EAD and the RWA.
- Technical difficulties.
The first point requires European coordination for establishing a single regulatory framework; this is happening already, and it will be reinforced by the ECB, as it becomes the unique supervisor in the Eurozone.
The second point is the most interesting, even if the regulation requires more transparency (and it will); providing this transparency today is technically impossible.
We mentioned above that the RWA calculation relies in a statistical model; which as any statistical calculation requires looking at a sample data whose behavior can be extrapolated to a bigger group.
Current banking systems are running on obsolete and non-integrated technologic infrastructures with heterogeneous data-models. Building statistically reliable models in these conditions is simply impossible.
Most, in fact all, banks use simplifications for covering the lack of accurate data for building their statistical models.
This is what the FED said about these models, after reviewing this year US banks solvency tests.
“Banks made assumptions that weren't always well documented or supported, did only cursory validation checks in some cases, and made assumptions without knowing if they were doable”
http://www.reuters.com/article/2014/10/17/us-banks-fed-stresstests-idUSKCN0I626Q20141017
This is the main competitive advantage of SAP Banking; a holistic and deeply integrated information system capable of supporting accurate and transparent capital calculations.
In a financial system of scarce capital, what could be more important than managing it efficiently?
We’ll analyze this value proposition in detail in future posts; but for the moment, let’s wait for the results of next Sunday solvency tests, I think they’re going to be interesting.
Looking forward to read your opinions.
Next Sunday October 26th, 2014 at 12:00 PM (CET) the European Central Bank (ECB) will make public the results of its assessment, checking the health of the 130 biggest banks of the euro area.
https://www.ecb.europa.eu/press/pr/date/2014/html/pr141010.en.html
Controlling the solvency of the financial system is the main responsibility of a bank’s supervisor. If he detects that a bank is undercapitalized, immediate actions must be taken, from requesting its recapitalization or blocking the bank’s dividends policy, till forcing its liquidation.
The regulatory capital that a bank must hold is a percentage of its Risk Weighted Assets, which must be big enough for covering future losses generated by borrowers not fulfilling their obligations. Currently, the regulatory capital calculation is determined by the Basel 3 agreement; but both, the required percentage of the Risk Weighted Assets and its calculation has changed over the time.
http://www.bis.org/bcbs/basel3.htm
We’ll analyze in a future post why the measuring of solvency has changed over the years, but today we’ll look at the difficulties of performing this calculation.
Calculating the Risk Weighted Assets requires looking at the future, and building a statistical model for determining the probability of default of the bank counterparts (PD), the bank’s exposure to the counterpart at the moment of default (EAD), and the share of the asset that is lost when the counterpart defaults (Loss Given Default).
Let’s have a look at the main challenges of the European case, there’re two difficulties for achieving efficient and comparable results of the capital analysis.
- Different national regulations. For instance, every country has different insolvency, liquidation and debt restructuring regulations. This has a direct impact in the value of the collaterals, the EAD and the RWA.
- Technical difficulties.
The first point requires European coordination for establishing a single regulatory framework; this is happening already, and it will be reinforced by the ECB, as it becomes the unique supervisor in the Eurozone.
The second point is the most interesting, even if the regulation requires more transparency (and it will); providing this transparency today is technically impossible.
We mentioned above that the RWA calculation relies in a statistical model; which as any statistical calculation requires looking at a sample data whose behavior can be extrapolated to a bigger group.
Current banking systems are running on obsolete and non-integrated technologic infrastructures with heterogeneous data-models. Building statistically reliable models in these conditions is simply impossible.
Most, in fact all, banks use simplifications for covering the lack of accurate data for building their statistical models.
This is what the FED said about these models, after reviewing this year US banks solvency tests.
“Banks made assumptions that weren't always well documented or supported, did only cursory validation checks in some cases, and made assumptions without knowing if they were doable”
http://www.reuters.com/article/2014/10/17/us-banks-fed-stresstests-idUSKCN0I626Q20141017
This is the main competitive advantage of SAP Banking; a holistic and deeply integrated information system capable of supporting accurate and transparent capital calculations.
In a financial system of scarce capital, what could be more important than managing it efficiently?
We’ll analyze this value proposition in detail in future posts; but for the moment, let’s wait for the results of next Sunday solvency tests, I think they’re going to be interesting.
Looking forward to read your opinions.
