If you explain what Source Data Aggregation of Bank Analyzer is, please do it right.

Dear, 
Last week I was talking to a customer who is considering implementing Source Data Aggregation in its Bank Analyzer - Accounting for Financial Instruments System. 

For those of you who are not familiar with Source Data Aggregation, let me give you a brief description of the functionality. 

Source Data Aggregation is a standard functionality of Bank Analyzer, fully available from release 7 which has the objective of reducing the size of the database in accounting calculations with no information lost. For doing that the system stores RDL related data aggregating the information of homogenous contracts. 

But reducing the size of a database with no information lost requires to follow some rules. 

1) We must identify the components which offer a better opportunity for reducing the database size. 
Simplifying, Bank Analyzer stores data in the Source Data Layer and the Results Data Layer. 
The Source Data Layer stores the Primary Objects (Master Data, Transactional Data and Market Data), while the Results Data Layer stores the interpretation of the Transactional Data from Accounting Principles (AFI calculations) and Basel III Credit-Risk Calculations. 

If you check the size of the Bank Analyzer database, you will see that the size of the tables storing Results Data Layer data is much bigger than Source Data Layer data. Consequently, we have a much better opportunity of reducing the database size by looking at the RDL instead of the SDL. 

2) We need to understand how can we reduce the size of the database and not loosing information in the process. 

The valuation of Financial Contracts follows two basic approaches; Nominal and Fair Value. Bank Analyzer supports both approaches. For some products, like Customer Accounts (Saving or Checking) the difference between both valuations is immaterial, for others like Mortgage Loans the difference between Nominal Accounting and Fair Value Accounting is very significant. 

On the other hand, calculations for determining the components of the Nominal Valuation of Financial Transactions are contained in the Transactional Banking System and consequently they´re also available in the Source Data Layer. 

Simplifying; we have an opportunity of reducing the size of the database by reducing the Results Data Layer related data, and not loosing information in the process by aggregating Nominal Accounting based products (like current or savings accounts). 

My customer was explained the above, but as my customer is an smart person he asked; how can I get the nominal accounting data by contract level (Current and Savings Accounts) if that data is not available by contract in the Results Data Layer? 

Unfortunately whoever explained him the Source Data Layer Aggregation functionality forgot to mention that this data can be obtained very easily from the Source Data Layer, that has not been aggregated, so he thought he was losing information by using Source Data Aggregation. 

This post is a simplification and it can never replace the proper analysis that must be performed before a Source Data Aggregation project is implemented. 

I just tried to make a point with it, SAP Bank Analyzer is an amazing product, but implementing it requires to follow some rules, and it´s important we explain those rules properly. 

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

Capital Optimization in Trading Activities with SAP Bank Analyzer.

Dear,

In the last post we look at the SAP Banking capabilities for Investment Management in an environment of Capital scarcity. 

https://www.linkedin.com/pulse/capital-optimization-investment-activities-sap-bank-analyzer-frances?trk=object-title  

After receiving some feed-back, I think there’s a little confusion with the concept of investment and SAP related functionalities, we’ll look at them in this post. In general, capital allocation activities are classified in two big groups; investing and trading. 

The goal of an investor is making profit by allocating capital over an extended period of time, comparable to the life-time of the asset in which he’s investing. For instance, an investor would buy a building for renting it and make profit. 

On the other hand, a trader goal is making profit by buying and selling assets in a short period of time.  

Looking at the previous example, a trader would buy a building for selling it after some months at a higher price. 

A couple of weeks ago, we saw how purely investment activities are managed with SAP Investment Management, and how can we integrate SAP Investment Management with SAP Bank Analyzer for managing efficiently the capital allocated to investment projects. 

This week, we’ll see how to manage trading activities efficiently, by combining the functionalities of Treasury and Risk Management with the functionalities of Bank Analyzer. 

The Treasury and Risk Management module has two sub-modules; Transaction Manager and Position Management. 

• Transaction Manager manages the trading contracts. 

• Position Management calculates the Accounting Values and Capital Consumed by the trading contracts.To some extend Position Management is an old version of Bank Analyzer (also called SEM-Banking). 

Transaction Manager offers all the necessary functionality for the operational management of the trading contracts.

• Business Parthers of the contracts. 

• Financial Conditions of the contracts. 

• Clearing Accounts for managing the payments and collections. • Cash-Flows generation. 

• Products Management for supporting most of the necessary trading contracts types (Forward Contracts, Options, Futures, Commercial Paper, Equities, Forex, Swaps, Bonds, etc.) 

On the other hand, Position Management (SEM-Banking) offers Accounting and Capital Management functionalities, but this solution is being replaced by Bank Analyzer, which comes with a more robust architecture. 

Fortunately, the integration between Transaction Manager and Bank Analyzer is quite simple.

Transaction Manager Data-model uses Financial Transactions and Business Transactions as Bank Analyzer does.

Transaction Manager also supports securities (called classes), that would be integrated in the Bank Analyzer Source Data Layer as Financial Instruments.

As you can see, integrating Transaction Manager as trade solution, with Bank Analyzer for covering the Accounting and Capital Management requirements is an excellent alternative for the management of trading contracts in an environment of capital scarcity. 

For instance, a real estate company promotes and manages the construction of a building, but it gets the necessary capital issuing bonds that will be acquired by investors. 

Traders could be interested on those bonds, as they expect its value to rise, and sell them when the market value has risen.

The capital allocation will be managed with a Transaction Manager contract, with the Holding Category “Held for Trading”. 

Position Management (SEM-Banking) could also manage the accounting and capital consumption effects of the trading contract, but as we said they’re old solutions meant to be replaced by Bank Analyzer. 

Finally, trading contracts can require the management of logistics operations, particularly when the trading partners have agreed on physical settlement of the contract. 

We’ll talk about this scenario in a future post. 

Looking forward to read your opinions.

K. Regards,

Ferran.

Capital Optimization in Investment Activities with SAP Bank Analyzer.

Dear,
The concept of Capital is deeply related to the concept of Risk. Risky activities consume more capital than safe ones. 

Investing is one of the most risky activities of the financial system. As difference to lending, where repayment cash-flows are determined by the contract conditions, investors’ returns depend on the profitability of the investment, which by nature are non-deterministic.

There’s the common misconception that SAP doesn’t have strong solutions for Investment Management, but this has more to do with lack of knowledge about the capabilities of the SAP business suite than with the reality.

Managing an Investment has two components; Operational and Analytical.

- The Operational Component includes the activities which assure the efficient execution of the Investment Project, including logistics requirements, milestones, control of costs and execution times, etc.

- The Analytical Component includes the budgeting and accounting activities of the Investment, including the Capital Management Activities.
SAP Enterprise Core Components has offered Investment Management functionalities for many years; including their seamless integration with the Projects System, Materials Management, Sales and Distribution and Plant Maintenance Modules.

I personally implemented the SAP Investment Management functionalities in several clients more than 10 years ago.

On the other hand, the SAP ECC modules lack in strong Capital Management functionalities of the Investment Projects, and this is a very important handicap in times of Capital scarcity.

Fortunately, this limitation can be easily solved by integrating the Investment Management functionalities of SAP ECC with the Capital Management functionalities of SAP Bank Analyzer.

Typically, the Investment Process starts with the definition of an Investment Program in SAP ECC, which is the hierarchical definition of the Investment Positions.

Every Investment Position is assigned to One or Several Investment Orders, Work Breakdown Structures or Appropriation Requests (which at the end will be Investment Orders or Work Breakdown Structures).

The Investment Orders and Work Breakdown Structures, represent containers of the Investment Program Cash-Flows.

And this is the key integration point between SAP ECC Investment Management and SAP Bank Analyzer.

In Bank Analyzer we also have a standard Primary Object for containing Cash-Flows, which is the Financial Transaction.

Replicating the Orders and Work Breakdown Structures, as Bank Analyzer Financial Transactions, will put the Bank Analyzer Capital Management functionalities at disposal of the Investment Program requirements.

Every Order, Work Breakdown Structures and Financial Transaction represents a collection of expected cash-flows, which have a probability of becoming actual cash-flows, according to the risks associated to the Investment Position.

Giving to Bank Analyzer the relevant probabilities of default and expected volatilities of the expected cash-flows, the Risk engines will provide the capital costs associated to the investment positions, and the Fair Value of the investment positions.

Although powerful market risk engines (including Value at Risk calculations) are still not available in the current versions of Bank Analyzer, it’s just a matter of time that they’re included in new releases.

During the execution of the Investment Project, actual flows will be posted in the Orders and Work Breakdown Structures, these flows will be transferred to Bank Analyzer as Business Transactions adjusting the Fair Value and Capital consumption of the correspondent Financial Transactions.

Efficient Capital management is the most critical activity of the new Financial System that will emerge of the current systemic crisis.

The SAP business suite can be a very important asset in this situation, but we need to improve the market recognition of its capabilities.

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