Implementing a Capital Optimization model with SAP Bank Analyzer.

Dear,
The Financial System is in the middle of a Systemic Transformation, from a Business Model based in Volume to a Business Model based in Efficient Management of Capital.

The increasing Capital Requirements levels (specially after the implementation of Basel IV), low growth rates of the Global Economy and huge Global Debt (around $233 trillion) are putting a big pressure in Banks’ Solvency positions.

The pressure in the Banks’ Capital positions is not a temporary fashion, Capital scarcity is here to stay and makes Capital Optimization the main priority for Banks’ executives.

As you could see in previous blogs, in my opinion SAP Bank Analyzer is the best Capital Optimizer in the market.


https://www.linkedin.com/pulse/capital-optimization-clearing-houses-blockchain-sap-bank-frances/

https://www.linkedin.com/pulse/capital-optimization-trading-activities-sap-bank-analyzer-frances/

https://www.linkedin.com/pulse/capital-optimization-investment-activities-sap-bank-frances-gil/

http://sapbank.blogspot.com/2017/06/capital-optimization-and-business-case.html

http://sapbank.blogspot.com/2014/05/liquidity-and-capital-optimization-with.html

http://sapbank.blogspot.com/2016/03/impairment-calculations-and-capital.html

But for some reason that I can’t understand, it’s difficult to find voices explaining the Bank Analyzer capabilities as a Capital Optimizer.

I'll try to put my two cents for changing this with this blog.

1) The first step in a Capital Optimization process is measuring accurately the Capital consumed in every market segment that the bank is exposed to.

This is the main value proposition of the Integrated Financial and Risk Architecture of SAP Bank Analyzer.

Bank Analyzer – Credit Risk module will calculate the Risk Weighted Assets of every contract, every risk exposure of the bank’s portfolio, and consequently the Regulatory Capital consumed.

Once we know the Capital consumed by every Contract/Exposure, we can aggregate the Capital consumed according to the analytical dimensions that we have defined in the Bank Analyzer-Results Data Layer, and consequently we will know the Capital consumed in every market segment in which the bank operates.

Alternatively, the SAP Bank Analyzer Credit Portfolio also give us the Economic Capital consumed by market segment, and all the complementary parameters to the Capital consumed.

2) The second step in a Capital Optimization process is the efficient assignment of Collaterals to exposures for reducing the Risk Weighted Assets and the Capital consumed.

The assignment of Collaterals to Exposures is not always an static assignment. The 1 to 1 assignment of a Collateral to an exposure is just the trivial case, but it’s usual that several (n) exposures are assigned to several (m) collaterals.
In case (n) exposures are assigned to (m) collaterals there’s an Optimal Distribution of the Collateral portions to the Exposures, which reduces the Risk Weighted Assets, and consequently the Capital consumption. This is the basis of the Dynamic Management of Collaterals that we discussed in a previous blog, and we will analyze again in a future one.


https://sapbank.blogspot.com/2012/09/capital-management-chapter-v-dynamic.html

The Bank Analyzer – Credit Risk Module has strong capabilities for the Optimal Distribution of Collaterals to Exposures in the Level 2 of the Calculation of the Risk Weighted Assets. These capabilities look at the Probabilities of Default and Exposures at Default of the Exposures and the Collaterals Values, adjusting efficiently the assignment of Collateral portions to Exposures.

3) The third step of a Capital Optimization process is maximizing the Banks profit reducing the Capital Consumed. Every market segment has a potential expected profit, and every market segment has a potential Expected Loss, and consequently a potential Capital Consumption.

Optimizing Capital means identifying the market segments with higher Expected Profit weighted by the Expected Capital consumed of the market segment.

This is the most difficult element of a Capital Optimization process, because it requires a double-synchronized simulation, looking for a solution which minimizes the Risk Weighted Assets maximizing the Expected Profit.

This optimization engine is still not available, but the Integrated Financial and Risk Architecture of Bank Analyzer has been designed for having an Integrated and Reconcilable vision of Risk and Accounting (Profit).

The IFRA is the technical foundation for running cycles of simulation that Capital Managers should run for achieving the Optimal Planning of the bank’s portfolio, reducing the RWA and maximizing at the same time the expected Profit.

Finally, the future will require the automatic calculation and simulation of banks investments, for proposing the Optimal Sales and Execution planning of the Bank. I’ve personally worked in some of this models, by adapting the Theory of Constrains to portfolio management.

These simulations require very strong computing capabilities, but this is the value that SAP HANA provides for solving the problem.

Looking forward to read your opinions.

K. Regards,
Ferran.

www.capitency.com

Join the SAP Banking Group at: https://www.linkedin.com/groups/92860

Visit my SAP Banking Blog at: http://sapbank.blogspot.com/

Let's connect on Twitter: @FerranFrancesGi

Ferran.frances@capitency.com

Optimizing the Chart of Accounts in SAP Bank Analyzer Smart-AFI and the Universal Journal.

Dear,

Previous versions of SAP ECC and Bank Analyzer gave a preeminent importance to the Posting Key Figures over the GL-Accounts.

From the first SAP R3 release, the Costing Based Operating Concern of the Profitability Analysis module gave us a very flexible framework for building a complete multidimensional Profit and Loss analysis engine. The only difficulty is that the Costing Based Operating Concern is built on Key Figures which makes difficult its reconciliation with the Profit and Loss postings of the General Ledger which are built in GL-Accounts.

On the other hand, we could also use the Account Based Operating concern of the Profitability Analysis module, which provides a complete multidimensional Profit and Loss analysis engine built in GL-Accounts, fully reconcilable with the General Ledger Postings, but the reconciliation problem with the Costing Based Operating Concern remains.

In both cases, we are talking about non-financial related postings. Concepts like Fair Value or Risk-related Costs are very difficult to model in the Profitability Analysis Module of SAP ECC. For covering this gap, SAP developed something new.

The new concept was the SEM-Banking (Strategic Entreprise Management for Banks) module of SAP ECC (IS-Banking), which was the precursor of SAP Bank Analyzer, and the first tool capable of providing a Contract (or more exactly Position) based multi-dimensional Cost-Analysis framework for Banks. Again, SEM Banking was built on Key Figures (Costing Based Operating Concen), with the commented advantages in terms of flexibility and disadvantages in terms or reconciliation.

With Bank Analyzer, SAP solved the problem. In Bank Analyzer we don’t have a Cost Based “Operating Concern” and an Account Based “Operating Concern”, instead the Posting Key Figures and the GL-Accounts are integrated in the same structure (the RDL Result Type) and we can find both in the Financial Position Object.

Nevertheless, this improvement also brought some difficulties; in Bank Analyzer (before Smart-AFI) the Posting Key Figures and GL Accounts of the Accounting entries are not determined at the same time. The Posting Key Figures are determined first (from the Item Type of the BT or the Calculation Step), and later the GL-Accounts.

In fact, the accounting logic is technically configured in the Posting Key Figure (Key Figure Class) and there’s no configuration in the GL-Account, which in Bank Analyzer (before Smart-AFI) was merely the value of a Characteristic with no configuration.

As a consequence of this, it was technically possible to assign a GL-Account to a Posting Key Figure with a different accounting nature, generating serious inconsistencies on the Financial Statements of the Bank.

I’ve seen several clients with bad implementation of Bank Analyzer, with inconsistent Financial Statements, as a consequence of an incorrect configuration of the Posting Key Figures and GL-Accounts determination.

Bank Analyzer Smart-AFI has tackled the above problem simplifying the Accounting Logic Configuration. With Bank Analyzer Smart-AFI, the GL-Accounts are at the center of the Accounting Logic, and they are technically defined with the Accounting Role that they must play, reducing the risk of the inconsistent configurations mentioned above.

By the way, this is coherent with the new Accounting Logic of the Universal Journal of S4 HANA, where we don’t build the multidimensional Profit and Loss analysis engine with Cost Based or Account Based Operating Concerns. All the accounting entries are centrally posted in the Universal Journal, in the form of Coding Blocks and GL-Accounts.

As you can see, in Bank Analyzer Smart-AFI, the GL-Account has become a central pillar of the configuration, and consequently, the Chart of Accounts Optimization has become one of the most critical activities in a Bank Analyzer implementation.

Optimizing the Chart of Accounts has always been a key success factor in a Bank Analyzer implementation. Suboptimal definitions of the Chart of Accounts bring accounting systems difficult to maintain, and in some cases, inconsistent Financial Statements. Smart-AFI brings a new a more simplified accounting architecture. It’s the responsibility of the implementation team to take advantage of it.

Looking forward to read your opinions.

K. Regards,

Ferran.

www.capitency.com

Join the SAP Banking Group at: https://www.linkedin.com/groups/92860

Visit my SAP Banking Blog at: http://sapbank.blogspot.com/

Let's connect on Twitter: @FerranFrancesGi

Ferran.frances@capitency.com