Capital Optimization and Solvency and Accounting Planning with SAP Banking

Dear Colleagues,

As organizations often operate in multiple locations and industries, it is critical to establish a common language for communication with their counterparts. Financial planning, reporting, disclosure, and consolidation form the basis of this language and are crucial to a company's information systems.

In the past, companies created flat-structure financial statements with numerous general ledger (GL) accounts to represent both the economic nature of accounting events and the analytical position in which they occurred. However, as businesses became more complex and regulatory requirements more stringent, the increasing number of analytical dimensions and economic event types resulted in large charts of accounts with thousands of GL accounts. Additionally, the structure of financial statements often varied among affiliates within the same group, making consolidation a challenging task.

To address these issues, SAP introduced the Flexible General Ledger and Universal Journal of S4 HANA, which introduced the concept of a multi-dimensional ledger. In this system, the analytical positions are represented by combinations of dimensions in the coding block, while the economic nature of the accounting event is represented by the GL account. This technology facilitated the harmonization and simplification of charts of accounts among affiliates within a group, making it easier to produce homogenous financial statements and facilitating their reconciliation and consolidation.

SAP S/4HANA Finance for group reporting includes a complete set of financial consolidation capabilities, including currency translation, inter-unit eliminations, data validation, and real-time company and group scope analysis reports. It also features seamless integration with SAP Analytics Cloud for central reporting and visualization of consolidated and non-consolidated financial information.

However, SAP has not yet released a complete solution for solvency and fair value accounting planning, including collateral revaluation, commitments postings, and value at risk analysis. An alternative to this is to complement the planning capabilities of SAP S/4HANA Finance with the solvency calculation capabilities of the SAP Credit Risk Analyzer and the IFRS-9 accounting capabilities of SAP Financial Products Subledger, using planning data rather than actual data.

Integrating in the same Planning cycle the Accounting Valuation and the Capital consumption forecast allows us to identify the expected benefit by market segment and weighted by the capital consumption of that segment. Establishing the basic pillar to Optimize Capital.

These are the guidelines followed by our team in the construction of our Capital Optimization system, built on top of the Integrated Financial and Risk Architecture.

Our Capital Optimization system speaks with the business processes of our clients' SAP Systems translating them in terms of Capital and Liquidity generation and consumption. With this information the Capital Optimization system measures the deficits and surpluses of capital and liquidity of the business processes and proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com 

I look forward to reading your comments.

Kindest Regards,

Ferran Frances.

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  #sapfinance #saps4hana #sapbanking #sapanalyticscloud #capitaloptimization

Collateral Management and Capital Optimization with the SAP Integrated Financial and Risk Architecture.

Dear,

We are in a process of systemic transformation of the Financial System, from a model based on Volume to a model based on Capital Optimization.

The Integrated Financial and Risk Architecture of SAP Banking offers multiple functionalities to support a holistic Capital Optimization process, but today we will look at its capacity for the efficient management of bank's collateral management.

One of the main consequences of the 2008 Financial Crisis was the recognition that the Financial System was severely undercapitalized; the subject was approached with two complementary approaches.

Governments and central banks recapitalized the financial system with bailouts, distressed asset relief programs, and cycles of quantitative easing.

The regulators focus on increasing and making visible the Capital Requirements with new Solvency and Accounting standards (IFRS 9, IFRS 15, IFRS 16, IFRS 17, Basel III, Basel IV, etc.)

The recapitalization of the Financial System has been a temporary measure. The global debt has continued to grow and the weak economic growth has generated new capitalization tensions; more visible as the end of quantitative easing cycles in Europe is announced.

With the advent of Quantitative Tightening, non-performing assets will become illiquid, reducing their value and once again increasing capitalization problems.

In this scenario of scarcity of capital, all forms of capital must be managed efficiently, and guarantees are probably the form of capital with the least representation in the Bank's Information Systems.

Bank information systems are ledger-centric, and since collateral is not represented on the balance sheet, the bank's IT architects have not paid much attention to modeling it.

Like any other right or obligation of banks, collateral management has an Operational and an Analytical component.

Operational Collateral Management focuses on the technical details of the collateral and its contractual relationship with the asset, the risk of which is being hedged,

Analytical Collateral Management focuses on the sustainable value of collateral and its ability to reduce capital consumption, and limit the provision for impairment of the asset whose risk is being hedged.

In the SAP Integrated Financial and Risk Artchitecture collateral is modeled in two different objects.

- As SDL-Financial Transaction to represent the contractual relationship between the collateral and the asset.

- As an RDL entry that represents the effective capacity of the guarantee to reduce exposures to Credit Risk and limit provisions for impairment.

Although a guarantee has a Nominal Value, it can have several different Credit Risk mitigation capacities, according to the Solvency calculation approach that the bank is following; Simplified Standardized, Comprehensive Standardized, Basic IRB and Advanced IRB.

Many times a group of guarantees covers a group of exposures; Determining the most efficient distribution of collateral to exposures reduces the capital consumed, which is the basis of Dynamic Collateral Management, one of the main Capital Optimization techniques.

HANA's high-performance in-memory computing capabilities make it easy to create simulation scenarios and stress tests, but before banks can take advantage of them, they must improve the representation of collateral in their information systems.

The Integrated Financial and Risk Architecture of SAP Banking provides a centralized collateral repository, facilitating regulatory reporting, calculation of risk-weighted asset provisions and impairment, stress testing of collateral values and simulation scenarios for capital optimization.

These are the guidelines followed by our team in the construction of our Capital Optimization system, built on top of the Integrated Financial and Risk Architecture.

Our Capital Optimization system speaks with the business processes of our clients' SAP Systems translating them in terms of Capital and Liquidity generation and consumption. With this information the Capital Optimization system measures the deficits and surpluses of capital and liquidity of the business processes and proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com 

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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

#capitalcrisis #capitalscarcity #sapbanking #energycrisis #capitaloptimization

Capital Optimization with SAP Banking vs reporting with Central Data Hubs

 Dear,

Capital Optimization requires making visible the generation of value by processes and business segments, weighted by their capital consumption.

The General Ledger does not have the capacity to provide this analysis capacity and this is a big problem if we take into account that the General Ledger is at the center of the banking Information Systems.

Measuring the generation of value weighted by capital consumption makes it necessary to represent the organization's accounting, solvency and liquidity situation in an integrated manner, including off-balance sheet items such as commitments, derivative contracts or collateral agreements.

Integration requires the processing of large data tables and the management of large blocks of memory, because each transaction must read and update data records from other areas. This was an unapproachable challenge until a few years ago. For this reason, banking information systems were built as separate silos of information, communicated by interfaces and intermediate tables, with very little integration between them. 

Many banks are tackling this problem with the construction of Central Data Hubs with which they try to respond to the accounting and solvency regulatory reporting requirements, although in most cases with mediocre results.

Central Data Hubs receive data from all the operational, silo style, systems of the bank, homogenize the data, and finally store it in an standardized format. So it can be delivered from there to the other analytical and regulatory reporting systems of the banking landscape. 

I’ve seen several of these initiatives in the last years, and they all present common difficulties.

Project design follows an ad-hoc/on-demand approach. Data architects collect data requirements from the data consumer systems, and design the data repository according to these requirements. And then, define the interfaces for collecting data from the source systems and populating the data in the destination systems.

To some extent, this approach implies reinventing the wheel, according to the bank’s own experience, and limited integration capabilities of the bank’s information architecture.

SAP has proposed a revolutionary, holistic approach, to manage the analytical requirements of banks. This is the Finance and Risk Data Platform, which takes advantage of the SAP Integrated Financial and Risk Architecture.

The Finance and Risk Data Platform has been designed to fulfill present and future Accounting, Risk and Liquidity regulatory requirements, as an alternative to the ad-hoc/on-demand approach of the Central Data Hubs.

The Finance and Risk Data Platform combines:

- The accumulated knowledge in the design and development of the Integrated Financial and Risk Architecture of Bank Analyzer during the last 2 decades. The Primary Data Objects of the Bank Analyzer Source Data Layer as an standard template of the Operational Data, and the Result Types of the Results Data Layer as an standard template of Analytical Data. 

Data Architects take advantage of these standard templates as a basic reference, and enhance them for fulfilling the bank’s specific requirements, without breaking the integrity of the data-model.

- The high-performing capabilities of SAP HANA for storing and managing very-high volumes of data, without intermediate tables and assuring the referential integrity of the database.

- The Extract, Transformation and Loading capabilities of SAP Smart Data Integration in Premise and in the Cloud. 

- The Analytical Layers of SAP Bank Analyzer Risk Engines, Liquidity and Risk Management on HANA, Intraday Real-time Liquidity Management, etc. 

These are the guidelines followed by our team in the construction of our Capital Optimization system, built on top of the Integrated Financial and Risk Architecture.

Our Capital Optimization system speaks with the business processes of our clients' SAP Systems translating them in terms of Capital and Liquidity generation and consumption. With this information the Capital Optimization system measures the deficits and surpluses of capital and liquidity of the business processes and proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com 

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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

Capital Optimization and Capital Allocations with SAP Banking and Predictive Analytics

Dear,

We are in a new economic scenario, a scenario of scarcity of Capital due to the combined effect of two forces that harm the economy.

- Weak growth. The shortage of energy and other natural resources is weakening economic growth. Weak growth limits capital generation.

- Excess debt that overconsumes capital.

If capital is overconsumed and not regenerated at the same rate, capital becomes scarce and capital is the most important resource of the financial system.

Efficient management of a scarce resource requires Planning. The capital optimization process begins by planning your consumption and the expected return on the underlying investment. With this analysis we will weight the return on investment by its capital consumption, prioritizing those segments with the best performance weighted by their capital consumption.

You can find a small example in this video.

https://www.youtube.com/watch?v=GkcVF5CWVrU&t

The process continues with the monitoring of the deviations between the planning of Income and Capital Consumption with the actual results.

Portfolio Management must look to the future and future is full of uncertainty. Managing uncertainty is managing capital, taking corrective actions when reality deviates from planning above the tolerance threshold.

The tolerance level must be consistent with the assigned capital, the required guarantees and the hedging strategies. Only in this way will we be managing the portfolio holistically, as this new structural environment of capital scarcity demands.

This classical vision has acquired new potential with the development of analytical tools and machine learning.

Thanks to the integration capacity of SAP Predictive Analytics with the rest of the SAP Business Suite components, including SAP Banking, this potential is even greater, as I will try to show you in the following scenarios.

Time Series Forecast

A Time Series forecast identifies key trends that directly influence future performance. Time Series Forecasting is useful for estimating future values of a measure where we have a time dimension available to help us identify a trend. Time series predictions are always time dependent.

In a capital consumption weighted income planning process, Time Series Forecasting is very useful to estimate several critical elements such as the following:

- Future Cash-Flows.

- Default Probabilities.

- Loss Given Defaults.

- Future Collateral Values.

Depending on the magnitude to be estimated, we must select the relevant data series for the estimation. The values taken by the target variable in the past and its corresponding dates. This Time-Serie is called the signal which will be analyzed by the Time Series Forecasting process of SAP Predictive Analytics.

Data accuracy is a critical success factor and our main competitive advantage as we take advantage of the integration capabilities of SAP Bank Analyzer Credit Risk Analyzer and SAP Predictive Analytics Cloud (Source Data Layer, Data Sources, Ad Hoc Reporting, Historical Database and Open Hubs).

Classification

Classification is the process of separating data into classes. In this scenario, the target is discrete, and the goal is to separate data into groups in a meaningful way.

In Capital Optimization, classification is particularly useful for segmentation of my counterparties and financial exposures. Typically, a Bank’s portfolio is managed in a repository where each Financial Transaction and its Counterparty contains the Product, Address, Level of Studies, Industry, Collateral Type, Region, Age, etc.

Classification supports the process of separating the Financial Transactions of our Portfolio between Rating Levels and showing how particular data influencers like Industry, or Region change based on Rating Level.

In SAP Analytics Cloud Predictive Scenarios, the system analyzes data using a discrete binary variable while simultaneously considering other variables in the data set. These are known as Influencer Contributions, which show how influencers affect the ranking result.

The Credit Risk analyst can also view individual statistics for each influencer in SAP Analytics Cloud, and the software calculates all of these statistics immediately when training a ranking scenario. SAP Analytics Cloud also generates contribution graphs that visually show how each class contributes to the total data set.

This scenario is particularly useful for supporting the automatization of assigning assets to tranches in a Securitization process.

Regression

Regression Analysis is a way of sorting out which variables have the most impact in a dataset. The target is continuous in this method and is primarily used to show the relationship between two or more variables in a dataset. For example, a Credit Risk analyst would use regression analysis to determine whether there is a correlation between users’ Level of Studies and average Delinquency Level. Traditionally, this involves taking all the data, plotting it on a scatter plot for the two variables, and finding an average line if the data fits a particular trend. This would then be done for other variables that are not included in the initial regression in the traditional method. In SAP Analytics Cloud, the Credit Risk analyst would simply pick one variable and the software automatically generates regressions, complete with relevant statistical data, for all variables in the dataset and how they relate to the target variable.

Conclusion

The methodology is much more efficient when we combine the three families of algorithms and build models in which we establish the dimensions of study and those that have a more direct influence on them. For example.- The level of education has a direct influence on the level of income, and this, together with the volume of expenses, influences the Delinquency Level. This approach provides a more robust model than another in which we analyze how the level of education impacts the Delinquency Level, without taking into account the volume of expenses. 

In our case, we have dedicated the last 12 years to building Credit Risk models that take advantage of the information contained in the SAP Systems of the non-financial economy. 

These models, built on SAP Banking systems, are integrated with the business processes of our clients' SAP Systems to Plan, Segment and Monitor the Capital Consumption of their business processes.

Even more, our proposal measures the Capital and Liquidity consumed and generated by the processes of the real economy managed with SAP Systems, detecting the deficits and surpluses of capital and liquidity of the process. With this information, it proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com 

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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

Vendors Credit Risk and Capital Optimization with SAP Banking.

Dear,

As a consequence of energy scarcity and excess debt, the world is entering fully into a new systemic phase of capital scarcity.

Energy shortage → Weak growth/decrease

Excess Debt → Excessive Capital Consumption

If Capital is overconsumed due to excess debt and does not regenerate at the same speed due to lack of Growth, Capital becomes scarce. And Capital is the most important resource in the financial system, therefore the priority must be to optimize it.

The need to optimize capital brings new business processes and massively deploy business processes that until now had been a minority.

For example; The credit risk function has traditionally been limited to the exposure that suppliers had with their clients, but not the other way around.

The Credit Risk module, within the Financial Supply Chain Management area, made it possible to measure the Credit Risk exposure to customers and based on sophisticated rules, categorize customers and block the exit of merchandise, the creation of the delivery or the Order confirmation.

But credit risk management for supplier exposures presents special challenges. A confirmed purchase/sale order is technically a Forward contract and will be an Asset or a Liability depending on the difference between the Fair Value and the Strike Price of the purchase-sale contract and if the Purchase Order is an Asset (because the Fair Value is higher than the Strike Price), the client will be exposed to the Provider's Credit Risk.

SAP purchasing and sales modules do not have the ability to determine the Fair Value of a Contract and the potential credit risk exposure of a Purchase Order. Historically this has not been a serious problem and was resolved with penalty conditions for poor service, but the scarcity of Capital is changing this forever.

An undercapitalized system manifests itself with increasing volatility; The weak growth and excess debt is transferred to the price of the main commodities and energy, which are necessary components in production, increasing the volatility of the price of the products and services that require them.

This volatility increases the market risk of these products, in some cases reaching the Fair Value of the marketed product above the Strike Price, turning it into an Asset for the Client and exposing it to the Credit Risk of its Supplier.

Forward contracts manage this scenario with the help of collaterals that protect both parties against the potentially volatile Credit Risk, and with the determination of Margin Calls in case the collateral is insufficient.

The combination of the SAP Sales, Purchasing and Logistics Execution Modules, with the FSCM Credit Risk and SAP Banking Market Risk, Credit Risk and Collateral Management functionalities would respond to the requirements of this scenario, facilitating the efficient execution of the contract. Purchase/Sale and Capital Optimization.

During the last 12 years we have worked on this integration, developing the process that allows extracting the best of the functionalities of the Logistics and SAP Banking areas to satisfy the needs of the Purchase/Sale process in a complicated environment such as the current one.

More generically, our proposal measures the Capital and Liquidity consumed and generated by the processes of the real economy managed with SAP Systems, detecting the deficits and surpluses of capital and liquidity of the process. With this information, it proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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

Energy Crisis, Capital Crisis, Stock Management and Capital Optimization with Integrated Processes in SAP Banking.

Dear,

Bloomberg published an article indicating that 60% of British factories are at risk of going under as energy bills soar. 

https://www.business-standard.com/article/international/60-of-british-factories-at-risk-of-going-under-as-energy-bills-soar-122090300111_1.html

This is not a surprise, since the financial crisis of October 2008 the world has entered a new systemic phase of Capital scarcity. Just look at the evolution of the balance sheet of the Federal Reserve in this period and you will see it.

https://www.statista.com/statistics/1121448/fed-balance-sheet-timeline/

There are two main factors determining this new environment of capital scarcity.

The lack of growth, as a consequence of the shortage of energy (peak-oil) and the excess of debt (public and private debt).

The excess of debt over-consumes capital and the lack of growth prevents it from being generated. Both factors are structural and therefore determine the new economic environment.

But capital is the most important resource in the financial system, and if it has become scarce, the priority is to optimize it. 

The Second Law of Thermodynamics teaches us that to optimize a resource in a system it is necessary to reduce its entropy and that entropy is reduced with information. 

And information theory teaches us that the exchange of information requires a common language between sender and receiver.

The highest level of information exchange to reduce entropy is process integration, when the sender and receiver collaborate on the process and share the information needed to plan and execute it efficiently.

SAP has been since its foundation the leader in process integration. First integrating the processes of the departments of a company, then the information of the companies within a group and finally integrating processes between groups of companies until reaching 70% of the World GDP.

Financial services have remained isolated from this integration process, very few banks have transformed their processes to SAP and none have integrated their processes with those of their clients.

But the new economic environment of scarcity of capital has come with new challenges. Since the start of the COVID-19 pandemic, supply chains have suffered severe tensions and those tensions have been exacerbated by the war in Ukraine and the energy crisis.

For instance, when more than half of the companies in the United Kingdom announce that they have solvency problems, traditional credit analysis is insufficient.

SAP has excellent solutions for Credit Risk management in the area of Financial Supply Chain Management, but these solutions are limited to the analysis of the historical performance of counterparties and the volume of risk exposure.

In times of systemic change, history changes direction and historical default data is insufficient to estimate future credit risk. As an example, just look at the credit risk of online retail companies and physical stores in the last 3 years.

If looking at the historical performance of our counterparties is not enough, we will have to estimate their future.

SAP systems provide a lot of useful information to estimate the future result and performance of a company. It is about analyzing it in a systematic way to draw conclusions about its future performance.

For example, a company that produces and distributes perishable products will reduce waste and improve the level of service with efficient management of the shelf-life of its products. SAP offers us powerful tools for the efficient management of the shelf-life of perishable products. Available to Promise with Product Allocations functionalities, consensus based planning and forecasting, vendor-managed-inventory scenarios, etc. It seems reasonable to think that companies with the know-how and technology to carry out these processes improve their stock management, which puts them on the path to better future results.

But we will only reduce the risk by moving from intuitive to systematic analysis. The uncertainty of these difficult times requires moving from reactive to proactive management and only the integration of processes can take us to that level of efficient capital management.

Our proposal measures the Capital and Liquidity consumed and generated by the processes of the real economy managed with SAP Systems, detecting the deficits and surpluses of capital and liquidity of the process. With this information, it proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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

Disruption of the Supply Chains, Systems Dynamics, Theory of Constraints and Capital Optimization with SAP Banking.

 Dear,

Logistics chains have been under great pressure since the fall of 2020. When societies recovered activity after coming out of the COVID-19 confinements, and consumption recovered, including a certain rebound in demand, the goods began to to accumulate in the ports, freight prices skyrocketed and inventories began to drop.

Complex supply chains have a tendency to behave this way. The complexity of the supply chain increases its entropy, and when an unexpected event occurs, the disruption is transmitted through the system, multiplying its effects. This nonlinear behavior is called the bullwhip effect, also known as the Forrester effect, and was first described by MIT Professor Jay Forrester's, in his book Industrial Dynamics (1961).

In 1984, the Israeli Physicist Eliyahu M. Goldratt proposed the Theory of Constraints as a solution to the non-linear behavior of organizations, described by Systems Dynamics. According to this Theory of Management, Organizations can achieve their Objectives, managing a reduced number of magnitudes or restrictions. Dr. Goldratt published his proposal in the management-oriented novel The Goal (1984).

During the last 30 years, SAP has transformed organizations by establishing a common language that allows them to integrate their processes, manage their constraints holistically, reduce their entropy and improve efficiency.

First, integrating intracompany processes, then intercompany processes within and outside its group of companies.

In 1998 SAP released its Advanced Planner & Optimizer software, which following the proposals of the Theory of Constraints, has multiplied the efficiency of Supply Chains and reduced the number of their disruptions.

Unfortunately, the economic system is under a level of stress that is not comparable to any other in the last 30 years. The complexity of supply chains has grown exponentially as a result of globalization, and in the last 3 years they have suffered the impact of several events with great disruptive potential. It was first hit by the worst pandemic since the 1918 influenza pandemic, followed by rising raw material and energy prices, multiplied by Russia's military intervention in Ukraine.

In this stressed environment, not all organizations are experiencing the impact of disruption in the same way. Those that have invested efficiently in implementing the Technology and Processes proposed by the best logistics practices (SAP Best Practices), have a greater capacity to manage bottlenecks, proposing alternatives, prioritizing corrective actions, reducing costs and improving, within possible, the level of service.

By reducing costs and improving the level of service, more efficient companies are improving their competitive position against those that lack these capabilities, improving their results, market capitalization and future solvency.

Integrating the business processes between the supply chain partners allows them to detect and manage the bottlenecks with the greatest disruptive potential in the system as a whole. Reducing the stress of these bottlenecks improves the resilience of the entire system, something critical when we manage complex, non-linear, highly entropic systems that can experience chaotic behavior.

The financial system is also a complex, non-linear, highly entropic and potentially chaotic system. The destructive potential of periodic financial crises and recessions, and the less frequent but much more destructive depressions, are ample proof of this.

I have worked as a SAP Consultant for 30 years, first in Real Economy (SD, MM, PP, APO, BIW, etc.) and since 2007, also as a SAP Analytical Banking Consultant.

From my first day as a SAP Banking Analytics consultant, I was impressed by the lack of integration of banking processes and the destructive potential of its disruption, as we all experienced in 2008.

As befits the value proposition that the company has offered for half a century, SAP Banking has solid proposals for the integration of financial processes, with benefits analogous to those that this integration has brought to the real economy. However, and despite what many of us thought in 2009, after the financial crisis of the previous year, the transformation of processes in the Financial System is far from having taken place.

Moreover, in the same way that the integration of processes in the real economy began between departments of the same legal entity but grew to incorporate external partners, the Financial System should integrate the processes of the real economy and is far from achieving it.

This is serious because the stressful economic environment, in addition to debt levels unseen in the history of capitalism, are a powerful disruptive force in the financial system. This disruptive force has the potential to destabilize the system and cause non-linear effects and without integration we will be unable to manage the bottlenecks, as proposed by the Theory of Constraints.

I detected this risk in 2010 and started working on a process integration proposal based on SAP Best Practices for financial services and real economy industries, and on top of it, the principles described by System Dynamics and the Theory of Constraints. 

During these years I explained the proposal to other colleagues and we put together a team to integrate financial and non-financial processes supported by SAP technology.

Our proposal measures the Capital and Liquidity consumed and generated by the processes of the real economy, detecting the deficits and surpluses of capital and liquidity of the process. With this information, it proposes financial instruments to offset these deficits and surpluses, optimizing the consumption of capital and liquidity 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 to contact me at ferran.frances@capitency.com

Looking forward to reading your opinions.

Kindest Regards,

Ferran Frances.

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