Integrated Management of Risk Exposures and Hedging Strategies with SAP Bank Analyzer.

Dear,
In a Financial System driven by Capital Optimization, reducing the Capital consumption is a priority, and one of the main activities for reducing the Capital consumption is the efficient application of risk hedging techniques.

A common mistake is confusing Hedge Management with Hedge Accounting.

Hedge Management is a Risk mitigation technique, whose foundation is mitigating the capital consumed in risk positions by using counteracting hedging transactions.

On the other hand, Hedge Accounting is an accounting concept, whose objective is reducing the volatility in the profit and loss account, of a company which is using derivatives, for hedging its risk exposures.

Effective Hedge Management requires 3 steps.

1) Accurate identification of the Gross Risk Exposures and Net Risk Exposures.

2) Selection of the Financial Instruments with capacity of Hedging the Risk Exposure.

3) Matching the Risk Exposures (Hedged Transactions) with the correspondent Hedging Transactions.

The Bank Analyzer Source Data Layer and the Reporting Capabilities of SAP HANA offer us an excellent technology framework for the efficient execution of the above steps.

In the standard scenario of the Credit Risk Module of Bank Analyzer, we use the Source Data Layer-Positions for Representing the Credit Risk Exposures, the SDL-Position must also be linked to the Financial Transaction (or Financial Instrument) which represents the Root Cause of the Risk Exposure (Normally the Commitment and Disbursement of a Financial Transaction/Instrument).

The Process and Methods Layer of Bank Analyzer will read the information provided by the Source Data Layer and it will calculate the Risk Weighted Assets, which is the foundation for determining the Capital Requirements.

But SDL-Positons can also represent other types of Risk Exposures, we just need to enhance them with additional Characteristics and Key Figures for storing the necessary data.

For Instance, a “Risk Type Characteristic” will facilitate the representation of Interest Risk exposures, and a “Nominal Value Key Figure” of the SDL-Position can represent the Nominal Value of the Interest Risk Exposure.

We still don’t have Value-at-Risk Calculation Processes in the Bank Analyzer-PML which would provide a commonly accepted estimation of the Potential Losses, but we can use the data for defining Hedging Strategies and identify the proper Hedging Transactions. The reporting capabilities of SAP HANA are the best option for this.

Traditionally, the management of Risk Exposures have been limited to Financial Investments, Financial Assets (Accounts Payable and Receivable), Financial Transactions (Commercial Paper), etc.

This is a limited vision of what Risk Exposures are; Risk Exposures belong to the World of the Facts, and they can be originated by Business Process belonging to the main company activities, strategic investments, speculative investments, etc.

Hedging Financial Instruments also belong to the world of the Facts, they’re Financial Instruments whose behavior counteracts the behavior of the Transactions that have generated the Risk Exposure.

For instance, as an Oil company refines and stores 10 Million Barrels of Oil, it gets exposed to the Volatility of the Oil Prices (Market Risk Exposure). The company, will Hedge the Market Risk with   a Sales Order of 10 Million Barrels of Oil. But as it’s Hedging the Market Risk Exposure, it will get exposed to the Default Risk of the “Sales Order Bill-To” (Counter-party). Additionally, if the Currency of the Sales Order is not the Currency of the Oil Company, it will also get exposed to the Volatility of Foreign Exchange Rate between the Company Currency and the Sales Order Currency.

But again, this is a limited vision of the reality. As the Oil company is refining and storing the  10 Million Barrels of Oil, it’s also getting exposed to the Risk that an accident destroys the facilities and pollutes the environment (Operational Risk). As a consequence, the company will suffer the losses of the destroyed facilities and the potential environmental fines.

The Oil company has two alternatives to hedge the risk;
- Signing an insurance policy with an insurance company.
- Investing in safer facilities and processes.

Deciding what’s the most efficient strategy requires estimating the expected cost of both alternatives. The first one requires Financial Capital (insurance policy fees), the second one requires Financial Capital (investing in improving the facilities and processes), and also Know-How (Intellectual Capital).

With Bank Analyzer we can manage the first alternative (traditional scenario), but we also can take advantage of  integrating Bank Analyzer with other SAP Enterprise Core Components for making possible the estimation of the expected costs of the second alternative. In my opinion this is something that other Hedge Management products can not provide.

I’m convinced that the Capital Optimization opportunities offered by SAP Bank Analyzer, combined with its integration capabilities with other SAP Products, makes it the best option.

I’ll try to give more examples in future blogs.

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

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

Let's connect on Twitter: @FerranFrancesGi

Looking forward to read your opinions.

Kind Regards,
Ferran.

Capital Optimization for Clearing Houses with Blockchain and SAP Bank Analyzer.

Dear,
The more the Systemic Crisis evolves, the more clear is that the new model of the Financial System will be based in the efficient Management of Capital.

Recently, the EU Regulatory body has announced that Central Counterparty Clearing Houses (CCPs) should be subject to  Recovery and Resolution proposals.

http://www.bloomberg.com/news/articles/2016-10-05/eu-readies-plans-for-clearing-crisis-the-next-too-big-to-fail

More or less at the same time, the Bank of England has announced that Clearing Houses should be subject to Stress Testing and Capital Requirements Calculations, in order of keeping a Capital buffer to cover potential losses during the Financial Instruments settlement.

http://www.reuters.com/article/boe-derivatives-clearing-idUSL5N188411

Remember that as a consequence of the 2008 Financial Crisis, it was decided that Derivatives should be traded in centralized Clearing Houses. This decision was translated to the regulatory body by the Title VII of the Dodd-Frank Wall Street Reform and Consumer Protection Act in the US, and by the European Market Infrastructure Regulation in Europe. Similar regulations have been also implemented in other jurisdictions.

https://www.sec.gov/spotlight/dodd-frank/derivatives.shtml

http://ec.europa.eu/finance/financial-markets/derivatives/index_en.htm

Now, we’re entering in a new phase of the transformation, as the regulator forces the Clearing houses to give more transparency to their Risk Exposures and holding higher Capital levels, as a buffer for potential losses on the Derivatives trading.

As Capital requirements and costs increase for the Clearing Houses, they will have to pass this cost to its counter-parties (Financial Instruments traders), and they will have to pass the costs to their counter-parties, and so on. At the end of the chain, the Capital costs will be higher to all the market participants.

The more expensive Capital is, the more incentives the market participants will have to optimize Capital and reducing its associated cost.

In the case of the Clearing Houses, we can easily identify two opportunities for Capital Optimization.

1) Reducing the settlement time. New distributed Ledger Technologies like Blockchain represent a big improvement on this. Blockchain offers Near Real Time Settlement between counter-parties; with this technology the Clearing House can reduce the time that the House is the counter-party for the market participants, and consequently reducing the Risk Exposures and the Capital cost.

The Risk for the Clearing Houses is that, the more the settlement times are reduced, the more chances are that the counter-parties settle their trades directly, killing the Clearing House business model. Anyway, this is a different matter and we’ll talk about it in a future blog.


2) With detailed and preemptive analysis of the Risk Exposures, which facilitates the efficient measurement and request of Collaterals to the market participants, and supporting the implementation of pricing strategies, escalated according to the expected Capital costs.

For supporting the analysis of the Risk Exposures, reporting the Capital Requirements and Risk Weighted Assets calculations, and Stress Testing Requirements, Clearing Houses can use the Credit Risk Module of Bank Analyzer.

Recently I had an interesting conversation with a colleague, very experienced in Bank Analyzer implementations. He mentioned that, although he agrees that Bank Analyzer can be used in non-banking organizations, the common opinion is that Bank Analyzer target should be only Banks.

I disagree, Banking regulation requesting higher Capital levels and more transparency in the reporting of the Risk exposures is a driver, which increases the Capital costs in the whole Financial System.

The Capital costs are transferred from the Banks to the other market participants, and make them look at the capital consumed in their business processes, in order of optimizing their Capital consumption.

At the same time, the regulator increases the number of companies and market participants, which must improve their Risk exposures reporting and increase their Capital levels.

Consequently, focus in Capital consumption is spreading from the Too big to fail Banks, to smaller Banks, Insurance Companies, Clearing Houses, market agents exposed to derivatives, and more.

At the end, this is the logical conclusion of a Financial System which is moving from a model based in Volume to a model based in Efficient Management of Capital.

Join the SAP Banking Group at: http://www.linkedin.com/e/gis/92860
Let's connect on Twitter: @FerranFrancesGi

Looking forward to read your opinions.

Kind Regards,
Ferran.