Impairment Calculations and Capital Optimization with SAP Bank Analyzer.

Dear,
The Financial System is in a process of Systemic Transformation, from a model based in volume to a model based in Efficient Management of Capital.

We're moving to a new era of limited growth, and in an environment of limited growth a fractional reserve financial system suffers solvency tensions. Consequently, the regulators increase the capital requirements, forcing the financial institutions to reduce their leverage.

As free capital becomes scarce, it also becomes more expensive, driving the Systemic Transformation.

Financial Assets consume Capital in three main ways:
- Credit Risk.

- Market Risk.

- Operational Risk.

The Basel III agreement establishes the main metric for measuring the Capital consumed due to Credit Risk exposure of the Financial Assets, and builds the foundation for the calculating the Capital requirements of a Financial Institution.

The Basel III agreement distinguishes between the Expected and Unexpected Loss produced by a Credit Risk exposure, the first one must be covered by Impairment Provisions, and the second one by Capital.

A valid model of capital optimization must reduce the capital consumed on credit risk exposures by limiting both, the Expected and the Unexpected Loss at the same time.

The Internal Rating Based Approach, both Foundation and Advanced gives us an opportunity for building a holistic Credit Risk Optimization System, as the Credit Risk model used for determining the Probability of Default, and the Loss Given Default and Exposure at Default (in case of the Advanced Approach) can be used, with some adjustments, as a basis for determining the Impairment Provisions.

In this model, the Impairment Provision is compared with the Expected Loss; if the Expected Loss is higher than the provision, the excess of Expected Loss is reduced from the capital.

On the other hand, if the Expected Loss is lower than the provision, banks may recognize the difference in Tier 2 capital up to a maximum of 0.6% of credit risk-weighted assets.

For details you can look at http://www.bis.org/publ/bcbs128.pdf

This holistic management of Capital Requirements and Impairment Provisions requires a integrated modeling of Risk and Accounting, which is exactly the foundation of the Integrated Financial and Risk Architecture of SAP Bank Analyzer.

From release 8, SAP Bank Analyzer offers the Impairment Processes submodule, fully integrated with the Accounting for Financial Instruments module.


The Impairment Processes of Bank Analyzer offer:

- Automatic determination of the percentage of Expected Loss from the Rating and the Delinquency Bands of the Exposures.

- Dynamic classification of the Financial Assets in the Bad or Good book by processing the Impairment Events.

- Determination of the Accruing Status of the Impaired and Performing Assets according to the IFRS requirements.

- Determination of Expected Loss, Provision Amounts, Write-down and Write-off, and the unwinding for the Exposures, including Off-Balance Exposures by using Credit Conversion Factors.

- Posting of the Impairment Provisions on the Bank Analyzer sub-ledger fully integrated with the Accounting Processes.

- Transfer of the Impairment Provisions to the General Ledger and complete reconciliation of the Impairment Provisions between the sub-ledger and the General Ledger.

And this is just the beginning; as mentioned above, the Integrated Financial and Risk architecture of SAP Bank Analyzer opens the gate for more complete representations of the banks capital consumption, we'll talk about them in future blogs.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.
K. Regards,
Ferran.

Solvency II and SAP Insurance Analyzer.

Dear,
As you probably know, since January 1st 2016, all the European insurance companies must be compliant with the new Solvency II Directive.

The European Union Solvency II Directive represents a major change in the insurance industry regulation. The Directive's main priorities are increasing the solvency of the Insurance companies and harmonizing the EU regulation, with the final objective of achieving a solvent and single EU insurance market.

From some perspective, the Solvency II regulation represents to the insurance companies what the Basel III and the EU Bank Recovery and Resolution Directive represents to the European banks.

This is a major challenge on the Information Systems of the Insurance companies, just for giving an idea of the complexity of implementing these regulations, we must consider that the final implementation date has been delayed 4 years from the initial proposals. Initially, regulators looked at October of 2012 as the implementation date.

Among many other changes, implementing Solvency II has requested the creation of the European Insurance and Occupational Pensions Authority (EIOPA) that, with more competencies, replaces the Committee of European Insurance and Occupational Pensions Supervisors (CEIOPS).

The Solvency II Directive is structured in three main areas or Principles.
- Pillar 1 establishes the quantitative models which must prove that the insurance company has the capacity to fulfill its obligations, like determining the capital requirements.
- Pillar 2 sets out requirements for the governance and risk management framework that identify and measure the risk to which the insurance company is exposed, and the supervision model.
- Pillar 3 focuses on disclosure and reporting of the company risk exposures and capital requirements.

Additionally, Insurance companies must also be compliant with the IFRS standards, particularly IFRS 9 for Financial Instruments.

For helping insurance companies to meet with these regulations, SAP has delivered the Insurance Analyzer System.

https://help.sap.com/insurance-fsia

Technically the Insurance Analyzer system is an evolution of the Bank Analyzer system, it's also built following the principles of the Integrated Financial and Risk Architecture, providing the full potentiality of the Financial Database.

As Bank Analyzer, the Insurance Analyzer System provides two groups of functionalities or modules.
- SAP Accounting for Insurance Contracts, equivalent to the Accounting for Financial Instruments module of Bank Analyzer.
- Solvency Management for Insurers, equivalent to the Credit Risk Analyzer (Basel III) module of Bank Analyzer.

And as in Bank Analyzer, the Insurance Analyzer System is also structured in 4 Layers.
- Source Data Layer.
- Processes and Methods Layer.
- Results Data Layer.
- Analytical Layer

The final objective of this 4 Layer Architecture is providing a single source of truth for Accounting, Risk and Liquidity Information

As it happens with the banks, in which sophisticated reporting tools have to coexist with non-integrated, heterogeneous operational systems, often supported by manual processes and non-integrated spreadsheets, it's going to take years before the insurance companies are fully compliant with the Data Governance requirements of the new regulation.

During this transition, the Data Governance capabilities of the 4 Layers, Integrated Financial and Risk Architecture of Insurance Analyzer will be a great help.

On the Source Data Layer, we can integrate all the data, provided by heterogeneous legacy systems, in an homogeneous Data-model of Master, Operational and Market Data.
For Instance.- Many insurance companies lack on an integrated vision of their customers data. Customers data is spread among legacy systems with very limited integration with each other, which is a root cause for undetectable fraud and inaccurate risk management.

With Insurance Analyzer, the insurer company can integrate in the Source Data Layer all these divergent versions of their Customer data in a single and integrated repository, building the foundation for customer-centric analysis of profitability and risk management.

Transforming the whole landscape of an Insurance company will represent an enormous effort of systems migration that will require much of the company resources. Without the integrated risk & accounting vision of Insurance Analyzer, it's not possible to align the IT strategy on the direction of the new requirements of Solvency II and IFRS 9, which are going to be the main concern for the IT executives of the industry in the oncoming years.

At the end, the stability of the insurance industry is not just a European issue, the global industry is facing major challenges, as it moves to a model driven by efficient management of Capital, and very sensitive to risk management.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.
K. Regards,
Ferran.

Fulfilling IFRS-9 and IFRS-15 Sub-ledger requirements with SAP Bank Analyzer.

Dear,
One of the main concerns of the banks' IT executives today is the implementation of the International Accounting Standard IFRS 9 Standard, “Financial Instruments”

Impairment Calculations, Fair Value and Hedge Accounting adjustments represent a challenge for current Banking Information Systems and an opportunity to replace some of their components with modern technologies, like the Accounting for Financial Instruments module of SAP Bank Analyzer.

SAP Bank Analyzer covers the three main groups of calculation requirements of the IFRS-9 standard.

- Fair Value calculation of Over the Counter, Securities and Listed Derivatives contracts.- Financial Instruments and Financial Transactions. (Mark-to-Market, Cash Flow Discounting, Forward Transactions, Options, Futures and Structured Products).

- Impairment Adjustments.- Calculation of the Risk Provisions, write-down, write-off and the unwinding with full integration with Accounting.

- Hedge Accounting Adjustments for Fair Value, Cash-Flow and Portfolio Fair Value Hedging.

On the other hand, there's a common difficulty on understanding the implications of the IFRS requirements; many clients see IFRS 9 just as a reporting requirement that must be fulfilled before January 2018.

But limiting an IFRS compliance program to the IFRS 9 requirements is an incomplete vision of the implications of the new IFRS Regulatory framework. IFRS requirements must be seen as a transformation process, and not as unconnected pieces of regulation.

An interesting example of the above is the Accounting Standard IFRS 15 “Revenue from Contracts with Customers”.

IFRS 15 puts the focus in the Revenue Recognition of the customer contracts individually. While this standard has not been specifically designed for banks, underestimating the impact of the “Revenue from Contracts with Customers” in the bank's architecture would be a serious mistake.

Banks have to disclosue the revenues generated when they charge their customers for the services they're receiving; services like securities broking, wire transfers, accounts maintenance fees, etc. Accounting adjustments must be allocated to every customer contract, challenging portfolio-based adjustments, which are very common in the banking industry.

Bank Analyzer AFI (subledger scenario) provides a complete Financial Statement (Profit & Loss, Balance Sheet and Off-balance positions) per customer contract, and fully reconcilable with the General Ledger. This is the main requirement of IFRS 15.

By implementing the AFI module of SAP Bank Analyzer, we're not only fulfilling the accounting requirements of IFRS 9, but also preparing our system for the future requirements of IFRS 15.

We also must remember that Inefficient integration between the Operational and Analytical Systems limits the capacity of providing reporting Profit and Loss analysis functionalities on contract level.

Current Banking Information Systems, supported by Legacy systems suffer from inefficient integration between the Operational and Accounting Systems. Even some banks which have replaced some of their Information Systems in the last years have failed in improving the integration between their Operational and Analytical-Accounting Information Systems.

Typically, Operational and Analytical banking Systems come from different vendors with heterogeneous data-models, in which the incompatibilities between the data-models must be overcome with “reasonable” hypothesis developed as conversion routines in the Extraction and Transformation Layer.

In this scenario contract-base valuations and adjustments are usually replaced by portfolio-based adjustments which contradicts the requirements of IFRS 15.

SAP Banking has provided a seamless integration between the Operational and Analytical Banking components of Banking Services by using Integration Operational Analytics technology, this is the base for transferring all the necessary information to the Accounting System, according to the IFRS requirements.

As a conclusion, Financial institutions need to look at the IFRS requirements as a process; while IFRS 9 are increasing the effort on determining the value of the Financial Instruments and the recognitions of the related revenue, IFRS 15 puts the focus in reporting determining the revenue recognition contract by contract.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.
K. Regards,
Ferran.

Dynamic Collateral Management with SAP Bank Analyzer and the Blockchain.

Dear,

In my opinion, the Blockchain is the most important innovation of the Finance Technology in the last years.

The Blockchain represents to the Internet of Value, what the TCP IP Protocol represented for the Internet of Information 25 years ago.

In the same way that it was difficult to imagine Facebook, Amazon, Skype or Netflix 25 years ago, it's difficult to imagine the services that Blockchain will support in the future.

Today, we know that some services are about to be implemented in the Blockchain, some of the most important ones are:

International Payments.
http://www.ibtimes.co.uk/

Securities Trading.
http://www.wired.com/2015/12/

Both are major achievements in terms of efficiency and transparency, but today I'm going to focus on some implications of the second one.

As we discussed in previous blogs, we're in the middle of a systemic crisis whose main characteristic is Capital Scarcity, as a consequence Capital Optimization will be the priority of the Financial System that will emerge of this crisis.

Capital has many shapes, and one of the most important is collateral, consequently Efficient Management of Collaterals is a critical activity in Capital Optimization.

Securities are one of the most usual forms of collateral, they're liquid assets traded in an organized market which provides them an updated price.

Blockchain provides a revolutionary technology for the efficient trading of securities, as securities trading and ownership are moved to a public, efficient and structured database like the Blockchain, the opportunities of improving the use of these securities in collateral agreements also increase.

Efficient use collateral rights require reduce the Loss Given Default of the exposures by implementing risk mitigation techniques, but avoiding over-collateralization which freezes capital without generating any return.

But balancing collaterals and exposures in order or improving the Risk Adjusted Return on Capital (RAROC) is not an easy task. The Loss Given Default depends on the rating of the counterpart (or his Probability of Default), and the value of the collateral fluctuates every second. Consequently the assignment of Collateral portions of a Collateral Pool to the bank's exposures should be a dynamic activity, that must be adjusted as the market and counterparty situations change.

For instance, as the rating of the counterparty improves, or the collateral value increases, the LGD will be reduced till it achieves a limit (full collateralization) in which better rating or more col lateralization are not improving the Risk Weighted Assets. This collateral excess could be used as a guarantee in another transaction, like a Repurchase Agreement, which will improve the portfolio return, without compromising capital consumption.

On the other hand, if collateral value declines or counterparty rating gets worse, higher portions of the collateral pool will be required for reducing capital consumption.

But the above theory presents practical constrains; in order of facilitating the optimal distribution of collaterals we need some requirements to be covered.

- Accurate calculation of the collateralization levels of the bank's exposures.

- Efficient (including inexpensive transactions) trade of collateral rights.

SAP Bank Analyzer is the answer to the first request, Blockchain is the answer to the second.

With Bank Analyzer we can guarantee an accurate measure of the capital consumed by the bank's portfolio, individually or by portfolios.

Additionally, we can implement alerts in the Analytical Layer of Bank Analyzer Credit Risk Module, informing the Bank's Capital Manager of the exception situations (under or over capitalization) which will trigger his attention in order of taking corrective actions.

But we also need that the transaction costs (including fees, transaction speed and settlement risk) are reduced, because if not, the potential profits of managing dynamically the bank's collateral will be reduced by the transaction costs.

This is exactly what blockchain is offering us, efficient, inexpensive and transparent trading of securities rights.

But securitization and efficient management of collaterals also presents other challenges, we'll talk about them in future blogs.

Join the SAP Banking community at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.

May the Force be with you.

Ferran.

Total Loss Absorbing Capacity and SAP Bank Analyzer.

Dear,
Three weeks ago, the Financial Stability Board issued the final version of the Total Loss-Absorbing Capacity standard for global systemically important banks (G-Sibs).

http://www.financialstabilityboard.org/2015/11/tlac-press-release/

This standard will have a profound impact in the reconfiguration of the Financial System, and in my opinion, the development of the SAP Banking industry.

But what is the Total Loss Absorbing Capacity Standard  (TLAC) standard?

The TLAC standard is an evolution of the Basel III agreement, which establishes the Capital Requirements for 30 banks identified as global systemically important, and considered by the Basel Committee on Banking Supervision as “Too Big to Fail”.

According to the TLAC rule, From 1 January 2019, the Capital requirement  for G-Sibs will be at least 16% of their risk-weighted assets (RWA's), increasing to at least 18% from 1 January 2022.

There's an exception, particularly relevant for Chinese banks, which establishes that emerging market G-SIBs must meet the 16% RWA minimum TLAC requirement no later than 1 January 2025, and the 18% RWA minimum TLAC requirement before 1 January 2028.

Considering that Basel III rules require banks to meet a minimum total capital ratio of 10.5% by 2019, the TLAC rule nearly doubles the Capital requirements for global systemically important banks.

But the current economic environment of limited growth, increasing competition and very low interest rates, supposes a serious handicap for generating profits. Doubling capital requirements in 3-4 years, will force the G-SIBs to raise capital from external sources.

On the other hand, this is also going to have an impact in the non-global systemically important banks, as the market will identify them as less solvent, increasing their cost of capital.

We've discussed here, that the Financial System started in 2008 a systemic change, from a model based in Volume, to a model based in Efficient Capital Management, the TLAC standard is just another milestone in the transformation process.

Recently, we visited a customer for a Bank Analyzer-IFRS 9 (impairment) presentation, and he mentioned that it was difficult to get the necessary budget for the implementation project, because the project was purely regulatory, without a direct impact on the business.

Big mistake, the new regulation, limited economic growth and over-leveraged economy are making capital very scarce.

Capital is the most critical resource of a bank; consequently, capital scarcity is driving the systemic transformation towards capital efficiency, with a very deep impact in the business strategy and processes.

If capital efficiency is the priority, banking information systems must be aligned with the new paradigm, supporting capital optimization activities.

Keep in mind that optimizing a resource starts by measuring accurately this resource and the processes consuming it. The Integrated Financial and Risk Architecture of SAP Bank Analyzer is the answer to the first requirement, and the robustness,  completeness of the data model, and integration between the Transactional and Analytical components of SAP Banking is the answer to the second one.

That's why a Bank Analyzer IFRS (AFI) implementation should be identified as a business driven project. Managing a bank under the new paradigm, means managing the business processes with the objective of optimizing the capital consumption.

Impairment calculations measure the capital consumed due to the Expected Loss of a Credit Portfolio, and consequently, determine the capital available for lending an investing. If we don't understand this, we're not understanding the systemic change.

Join the SAP Banking community at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.
K. Regards,
Ferran.

BCBS 239 Principles and SAP Bank Analyzer.

Dear,
As you all know the starting of the Financial Crisis in 2007-2008 represented an inflexion point in the implementation of a regulatory framework in the Financial System.

A particularly important milestone is the document from the Basel Committee on Banking Supervision: "Principles for effective risk data aggregation and risk reporting".

http://www.bis.org/publ/bcbs239.pdf

The fourteen principles "recommended" by the committee define the architecture that banks have to implement in order of being compliant in the new financial system that is emerging from the Financial Crisis.

This represents a huge endeavor which will attract a very important part of the banks resources, and taking the wrong decision can seriously jeopardize the bank´s future capabilities.

Recently I had a very interesting conversation with a client about the capabilities of SAP Bank Analyzer for fulfilling IFRS 9 and IFRS 15 requirements.

During the conversation; the client mentioned that the current bank´s IT priority is the centralized management of risk data.

Actually, what they had in mind are the 14 principles of the Basel Committee, let´s see how the IFRA of Bank Analyzer is the best answer to them.

Principle 1
Governance – A bank’s risk data aggregation capabilities and risk reporting practices should be subject to strong governance arrangements consistent with other principles and guidance established by the Basel Committee.

SAP Bank Analyzer proposal.
The Financial Database is a centralized and robust repository of the risk data, and properly build, provides the Single Source of Truth for all the bank´s risk data, which is the foundation for strong reporting capabilities.

In a complex landscape of Transactional Systems, only the Source Data Layer of Bank Analyzer provides the Single Source of Truth for the bank´s Master and Transactional Data, which is currently spread in multiple systems with heterogeneous data-models.

Processing this Single Source of Truth data in an homogenous centralized system for calculating the Accounting and Solvency position of the bank is the responsibility of the Bank Analyzer - Process and Methods Layer.

Storing the calculation results in homogenous and consistent repository of metadata is the Results Data Layer main capability.

Finally, reporting this data with very strong analytical and reconciliation capabilities is the value proposition of the Analytical Layer.

Principle 2
Data architecture and IT infrastructure – A bank should design, build and maintain data architecture and IT infrastructure which fully supports its risk data aggregation capabilities and risk reporting practices not only in normal times but also during times of stress or crisis, while still meeting the other Principles.

SAP Bank Analyzer proposal.
Bank Analyzer fully supports the Stress Testing requirements for Solvency and Liquidity established by the Basel agreements. But more than that, the completeness of the data model, opens the gate to implement new risk engines for fulfilling future requirements, without modifying the data architecture.

Principle 3
Accuracy and Integrity – A bank should be able to generate accurate and reliable risk data to meet normal and stress/crisis reporting accuracy requirements. Data should be aggregated on a largely automated basis so as to minimise the probability of errors.

SAP Bank Analyzer proposal.
The Bank Analyzer architecture offers strong Extract and Transformation capabilities and a complete template of Primary Objects which will assure data accuracy, assuming of course  that the implementation team has the capacity and willingness to follow the SAP´s implementation best practices.

This is just an introduction. It´s very difficult to express in just one post the implications all these principles, but we will discuss this topic again in future posts.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.
K. Regards,
Ferran.

Optimizing Capital in Oil and Gas companies with SAP APO and Bank Analyzer - Chapter II.

Dear,

In the last blog we discussed how Capital Scarcity can hit very hard to Oil companies which are not ready to the challenges of this new scenario.

https://www.linkedin.com/pulse/optimizing-capital-oil-gas-companies-sap-apo-bank-analyzer-frances?trk=mp-reader-card

Today, we´ll look at some alternatives to improve the efficient management of Capital in Oil companies by combining the functionalities of SAP APO and SAP Bank Analyzer.

Some of the required functionalities are not available yet; current Bank Analyzer versions don´t have strong Market Risk Analyzers, including Value at Risk calculations. But these functionalities have been offered for years in SEM Banking (considered by many the precursor of Bank Analyzer), and in my opinion, it´s a matter of time that they´re included in Bank Analyzer.

Going back to the point, we saw in the previous blog that an Oil company with a very efficient Supply Chain can still face Capital tensions ending in bankruptcy due to the Oil Market Risk. 

What can we do for improving the business plan including this risk?

First thing we must understand is that a Production Order or a Storage Unit of a Volatile product, like Oil, can be represented in Finance by a Financial Transaction (or Financial Instrument), whose underline is the Volatile product (Oil).  With this integration, a potential Market Risk Analyzer engine of Bank Analyzer would be able of giving us the Expected Losses due to the Value at Risk of the Underline.

On the other hand, the company can hedge the potential Market Risk losses by selling the Oil to a customer. But then it will be exposed to potential losses due to Counterparty Risk. 

Again, representing the Sales Order Items as Financial Transactions in Bank Analyzer, and providing the Rating of the Business Partner to the Credit Risk Engine, the system will give us the Expected Losses of the Financial Transaction (including the Expected Loss at committing with a Sales Order, by using Credit Conversion Factors).

By calculating the consumed Capital due to Market Risk Volatility and Credit Risk of the Exposures, Bank Analyzer will give us the Free Capital of the Company in every planning cycle.

As Free Capital is a measure of the Market and Credit Risks that the company can tolerate without suffering Solvency tensions, it´s actually determining a bottleneck in the amount of Oil that the company can extract, refine, store, distribute and sell.

Bottlenecks of the Supply Chain are represented in SAP APO by Resources and Capacities; and the Supply Network Planner will generate Planned and Production Orders only if the company has available capacity.

Making an analogy, in the same way that the Oil Company will not extract more Oil than its refining capacity, the company should not extract more Oil than the amount of Volatility that it can support without becoming insolvent. And in case the Oil can be sold immediately, hedging the Market Risk Volatility, it shouldn´t extract more oil than the amount whose Credit Risk Expected Loss is higher than the Company´s free Capital.

The standard APO element for modeling this "Free Capital-Capacity", would be an APO-Supply Network Planning bucket Resource.

Nevertheless, the available and consumed Capacity in this resource will be provided by an external engine, the Free Capital Calculator of Bank Analyzer.

Simplifying, in case Volatility and Counterparty Risk is low, Bank Analyzer will represent the situation with available Capacity in the bucket resource. On the contrary when Volatility and Credit Risk are high, Bank Analyzer will communicate less available Capacity to the bucket Resource.

The company has also to look Capital Consumed by its Market Demand on the Long Term Demand Planning activities, we´ll see how to model it in a future post.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860

Looking forward to read your opinions.

K. Regards,

Ferran.