Capital Optimization and Holistic Management of Basel IV and IFRS-9 with the Integrated Financial and Risk Architecture of SAP Bank Analyzer and FPSL

 Dear:

As we discussed in previous posts, we are in the midst of a systemic transformation: from a volume-based financial system to one based on efficient capital management.

In a globalized financial system, efficient capital management requires a commonly accepted regulatory framework for measuring the capital consumed by a bank's assets.

The main sources of current banking regulation are the International Accounting Standards Board (IFRS) and the Basel Committee on Banking Supervision (Basel IV).

http://www.ifrs.org/About-us/IASB/Pages/Home.aspx

https://www.bis.org/bcbs/

The BCBS's primary responsibility is to establish capital requirements to ensure the financial stability of the banking system, while the IASB's primary responsibility is to establish fair valuations of assets.

In reality, both organizations address the same problem: the measurement of capital consumption, from different perspectives.

- IFRS. The Fair Valuation of a Financial Asset determines the provisions that adjust the Nominal Value of the Asset to a Fair Value, which includes the Cost of Risk.

- Basel IV. The capital requirements of an asset determine the capital consumed when investing (or lending).

It seems reasonable to establish some level of reconciliation between the two approaches.

Basel IV requires banks to accumulate capital during the expansion phase of the business cycle to cover possible losses during the contraction phase. These countercyclical capital requirements are not tied to any particular loan, so they are generic.

On the other hand, International Financial Reporting Standards establish the provisions that banks must recognize to cover losses in their portfolio due to events that have already occurred and will affect future cash flows.

Some of these losses come from detected bad loans, but others come from bad loans that we know exist in the portfolio, but that we have not yet detected. Therefore, we must evaluate the entire portfolio and adjust its value globally, also through a Generic Provision.

But the problem remains: how to determine the Fair Provision for a hidden bad loan?

An interesting approach to determining the value of these generic provisions uses the Internal Ratings-Based Approach to Credit Risk Calculation (Basel IV).

To calculate IRB Credit Risk, we must evaluate several components: Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and contract maturity (M).

In addition, the IRB method allows us to calculate the expected portfolio loss (PE), which corresponds to the expected loss of each loan, calculated with the following formula:

PE=PD*LGD*EAD

For our reconciliation exercise, we use the IRB method's Expected Loss concept, which is similar to the IFRS concept of Incurred Losses, but not exactly the same.

IRB Expected Losses are the average loss stream that internal rating calculation methods predict will materialize in a year, while IFRS Incurred Losses are the balance of losses existing in the portfolio at a given time, due to past events that will generate losses in the future.

Both Incurred Losses and Expected Losses are different from the annual manifest losses (annual default stream) and, consequently, from the annual stream of specific provisions.

However, we can calculate Incurred Losses under IFRS by estimating the annual stream of expected losses and the time elapsed from the event that causes the loan to default until the moment it becomes apparent. This period between the two events is called the Loss Identification Period (LIP).

For example, if the counterparty loses their job and becomes unable to meet their payment obligations 18 months later, the Loss Identification Period would be 18 months.

Therefore, if we know both quantities (the Expected Losses and the Loss Identification Period), we can estimate the Incurred Losses by multiplying them.

For example, if the calculated Expected Losses for our portfolio (IRB method) are $45 million per year and the average Loss Identification Period is 2 years, this means that the Incurred Loss in our portfolio is $90 million.

Incurred Losses (IFRS) = Expected Losses (IRB Method) * Loss Identification Period

During the upswing of the business cycle, the Loss Identification Period is longer due to easier refinancing policies and favorable economic conditions.

According to the formula, a longer Loss Identification Period will increase Incurred Losses during the upswing.

In this way, we reconcile the calculation of IFRS Generic Provisions with the countercyclical capital buffer required by Basel IV.

The Integrated Financial and Risk Architecture holistically assesses capital consumption for Credit Risk, both from a solvency perspective (Basel IV) and from an accounting perspective (IFRS-9).

In Bank Analyzer Credit Risk, we determine the Probability of Default, the Loss Given Default, and, of course, the Expected Loss for each exposure, dynamically applying collateral and guarantees.

Secondly, SAP Financials Product Subledger uses the results of the Basel IV Credit Risk calculation as input for the calculation of IFRS-9 provisions.

Applying the above method to a real bank's portfolio management requires an integrated accounting (IFRS) and risk management (Basel IV) system within a holistic data model. This is the foundation of Bank Analyzer's Integrated Financial and Risk Architecture and makes it the best system for measuring a bank's available and consumed capital.

The results of the Basel IV and IFRS-9 calculations are holistic and reconcilable for the common dimensions of the Result Data Area of the Integrated Financial and Risk Architecture. This is why this architecture offers us a reconcilable and holistic view of capital consumption for Credit Risk.

The capital consumption for Market Risk is still missing, as it is only available in the Results DataBase. This lack of integration can be partially resolved with the open architecture of the Integrated Financial and Risk Architecture, but this would be the subject of another article.

The next level is Capital Optimization, which requires the integration of Real Economy and Financial Economics processes. For the past 12 years, our team has worked on modeling all economic events and business flows represented in Real Economy SAP systems, in terms of capital and liquidity consumption and generation. With this information, our systems measure how to offer financial instruments to cover capital and liquidity gaps or invest excess capital and liquidity, thus optimizing the system's capital consumption and liquidity.

We are working to introduce our system to the market and are looking for business partners and investors. If you are interested, please do not hesitate to contact me.

ferran.frances@gmail.com

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

Join the SAP Banking Newsletter: Subscribe on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6893665983048081409

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

If you want to connect on linkedin send me an invitation and I will accept it.

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.  

Japanese bond market collapse, Capital scarcity and Capital Optimization with SAP Banking.

 Dear,

In recent weeks, long-term Japanese government bond rates have been rising due to investor concerns about inflation, government spending, and interest rate hikes by the Bank of Japan.

In recent years, the Bank of Japan's low interest rates, necessary to keep interest on Japan's high debt under control, created a yen carry trade, where investors borrowed in yen at low costs and purchased assets with stronger yields abroad.

This mechanism has financed investments in other markets, such as the US.

However, if Japanese debt yields rise, this carry trade mechanism will cease. Investors will have less incentive to finance assets outside of Japan, eventually liquidating US assets to obtain liquidity under the pressure of the rising interest burden on Japanese debt.

When we reach this point, and we will because the debt is growing unstoppably, the Japanese debt problem will spread to the United States and from there to the rest of the world. Let's not forget that Japan is the largest foreign holder of US debt.

As SAP consultants, none of us are in a position to stop the forces of the macroeconomic environment, and therefore our goal must be to act to guide our actions in helping our clients navigate the stormy seas of rising Capital Costs.

Ultimately, rising government debt yields will accentuate the strain on the financial system and make it difficult for companies to finance their investments.

For all of the above reasons, reducing Capital Costs, or in other words, Optimizing Capital, is becoming critical.

Let's look at what a Capital Optimization process looks like.

1) The first step in a Capital Optimization process is to accurately measure the capital consumed in each market segment to which the bank is exposed.

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

Bank Analyzer's Credit Risk module will calculate the Risk-Weighted Assets for each contract, each risk exposure in the bank's portfolio, and, consequently, the Regulatory Capital consumed.

Once the capital consumed by each contract/exposure is known, we can aggregate it according to the analytical dimensions defined in Bank Analyzer's results data layer, thus understanding the capital consumed in each market segment in which the bank operates.

Alternatively, SAP Bank Analyzer's Credit Portfolio also provides us with 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 allocation of collateral to exposures to reduce Risk-Weighted Assets and capital consumption.

The allocation of collateral to exposures is not always static. A 1-to-1 allocation of one collateral to one exposure is a trivial case, but it is common for several (n) exposures to be allocated to several (m) collaterals.

If (n) exposures are allocated to (m) collaterals, an optimal distribution of collateral portions across exposures occurs, reducing Risk-Weighted Assets and, consequently, capital consumption. This is the basis of dynamic collateral management, which we discussed in a previous blog post and will discuss again in a future one.

https://www.linkedin.com/pulse/dynamic-collateral-management-capital-optimization-sap-frances-gil/

Bank Analyzer's credit risk module has robust capabilities for optimal collateral allocation to exposures in Level 2 of the risk-weighted asset calculation. These capabilities analyze Probabilities of Default and Exposures at Default, as well as Collateral Values, efficiently adjusting the allocation of collateral portions to Exposures.

3) The third step in a Capital Optimization process is to maximize the bank's profit by reducing Capital Consumption. Each market segment has a potential expected profit, and each market segment has a potential expected loss and, consequently, potential capital consumption.

Capital Optimization involves identifying the market segments with the highest Expected Profit weighted by the market segment's Expected Capital Consumption.

This is the most complex element of a Capital Optimization process, as it requires a doubly synchronized simulation to find a solution that minimizes Risk-Weighted Assets and maximizes Expected Profit.

This optimization engine is not yet available, but Bank Analyzer's Integrated Financial and Risk Architecture has been designed to provide an integrated and reconcilable view of Risk and Accounting.

The IFRA is the technical basis for running the simulation cycles that capital managers must implement to achieve optimal bank portfolio planning, reducing RWA while maximizing expected profit.

Finally, the future will require automatic calculation and simulation of bank investments to propose optimal sales and execution planning. I have personally worked on some of these models, adapting the theory of constraints to portfolio management.

These simulations require very powerful computing capabilities, but that is the value that SAP HANA brings to solving the problem.

The last 12 years our team has worked in modeling all the economic events and business flows represented in the SAP systems of the Real Economy, in terms of Capital and Liquidity consumption and generation. With this information, our systems measure how to offer Financial Instruments for covering Capital and Liquidity gaps or investing Capital and Liquidity surpluses, optimizing the Capital and Liquidity consumption of the system.

We are working on presenting our system to the market, and looking for business partners and investors, if you are interested do not hesitate in contacting me at

ferran.frances@gmail.com

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

Join the SAP Banking Newsletter: Subscribe on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6893665983048081409

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

If you want to connect on linkedin send me an invitation and I will accept it.

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances-Gil.