Sunday, June 21, 2015

Managing Conduct Risk with SAP Bank Analyzer.

Dear,

Last years, many scandals have come to light in the Financial Industry; scandals like Libor and Forex manipulations, Tax Evasion practices, etc. 

Coinciding with the imposition of fines to some of the biggest and most powerful banks for these compliance violations, we’ve seen a new concept called Conduct Risk, showing up in banking publications, speeches and forums. But what’s exactly the “Conduct Risk”?

We still don't have a regulatory definition of what’s Conduct Risk, but several approximations to the concept have been proposed by regulators in different jurisdictions.

Personally,  I like the description proposed by Daniel K. Tarullo, member of the Board of Governors of the Federal Reserve Board and chairman of the Federal Financial Institutions Examination Council. In his speech "Reforming Culture and Behavior in the Financial Services Industry" of October last year. He described it as the risk of malfunctioning controls and operations due to unethical practices. 

http://www.federalreserve.gov/newsevents/speech/tarullo20141020a.htm  

The Basel Committee on Banking Supervision is already aware of the necessity of building a regulatory framework addressed to Conduct Risk and recently issued the consultative document "Corporate governance principles for banks".

http://www.bis.org/publ/bcbs294.htm

Before that, on 2013, the British Financial Conduct Authority provided a very interesting guide for a company to asses Conduct Risk.

https://www.fca.org.uk/static/fca/documents/fca-risk-outlook-2013.pdf

Banks are responsible of building systems preventing Conduct Risk and unethical behavior. Considering that settlement costs of unethical related activities in recent years are more than 21.000 Million Euros, it looks like an interesting opportunity.

The broad scope of Conduct Risk makes difficult to describe a holistic architecture for managing it; from cases of banks being fined for selling products considered too complex for the risk profile of some of their customers; to banks receiving fines for money laundry or supporting tax evasion.

In my opinion, there’s no better candidate to fulfill the requirement than the Integrated Financial and Risk Architecture of Bank Analyzer. Let me explain you why.

In the same way banks are moving from silo-style to centralized holistic systems for the management of Credit, Market or Liquidity risk, the same rule applies for defining the architecture of a Conduct Risk System.

A holistic management of Conduct Risk requires an integrated vision of economic Facts and the interpretation of those Facts, and this is in the core values of the Integrated Financial and Risk Architecture of Bank Analyzer.

The Source Data Layer is a centralized container of Facts, mirroring economic events happening in the Transactional Banking System. But the Source Data Layer also requires that economic Facts have been homogenized in a single Data Model which makes feasible to track those economic Facts amongst individual processes.

For instance; while is a common issue that banks can have several operational systems with different versions of their account holders ratings, in Bank Analyzer we enjoy a unified vision of the Business Partner and all his attributes.

How can the bank claim that it has run a proper analysis of the Risk Profile of its customers if it’s unable of storing a Single Truth of their Rating?

We don’t have a Conduct Risk Analyzer in Bank Analyzer yet, but we can take advantage of the Open Architecture of the Integrated Financial and Risk Architecture for connecting with other systems fulfilling the specific functions.

For instance, many banks are building Anti-Money-Laundering systems tracking suspicious transactions in their silo-style, poorly integrated network of transactional systems. 

As we have all the Business Transactions in the Bank Analyzer Source Data Layer, it would be much more efficient to track suspicious Business Transactions in the centralized and homogenous repository that the Source Data Layer represents.

I’ve seen many customers thinking that Bank Analyzer is just a Sub-Ledger (Accounting System); this is a limited understanding of the Integrated Financial and Risk Architecture whose capabilities go far beyond that.

But this post has become too long; we’ll come back to this topic in a future one.

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

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

Monday, June 15, 2015

Efficient Management of Real Estate contracts with SAP Bank Analyzer.

Dear,
Managing Real Estate Properties has become an important activity for banks all over the world.

Since the burst of the US Real Estate bubble on 2007 and later in other countries, banks have covered their potential losses taking ownership of the Real Estate Collaterals of their failed Mortgage Loans.

Some of those Real Estate properties are activated by being rented to the market, becoming Financial Assets whose value must be determined according to the regulations of the International Financial Reporting Standards.

On May 2001, the International Accounting Standards Board (IASB) issued IFRS 13 (Fair Value measurement), as a single source of guidance for measuring the fair value of Financial Assets, including Real Estate Lease Out contracts.

http://www.ifrs.org/Documents/FairValueMeasurementFeedbackstatement_May2011.pdf

http://www.ifrs.org/Current-Projects/IASB-Projects/Fair-Value-Measurement/Pages/Fair-Value-Measurement.aspx

http://www.iasplus.com/en/standards/ifrs/ifrs13

According to IFRS 13, there are generally three approaches that can be used to derive fair value: the market approach, the income approach and the cost approach. To measure fair value, management should use valuation techniques consistent with one or more of these approaches.

Real estate assets are often unique and not traded on a regular basis, producing lack of observable input data for identical assets. For that reason, the income approach is the preferred method for real estate fair value measurement. Consequently, fair value measurements of real estate assets will require the following inputs.

- Cash flow forecast using the entity’s own data
- Yields based on the management estimation
- Yield adjustments based on management’s assumptions about uncertainty/risk
- Assumptions about future development of parameters (for example, vacancy, rent) that are not derived from the market

The Flexible Real Estate module of SAP Enterprise Core Components provides strong functionalities for the management of Real Estate Assets, including Cash-flow generation from the financial conditions of the Lease Out contracts, which can be the foundation for the cash-flow forecast required by IFRS 13.

On the other hand, Flexible Real Estate lacks on strong functionalities for Yields determination and adjustments based on potential counterparty or market events (Counterparty and Market Risk).

Fortunately, we have the option of taking advantage of the SAP Bank Analyzer capabilities for the generation and management of the required inputs and the subsequent valuation of the Lease Out Contracts according to the income approach, or what is the same, the discounted cash-flows valuation technique.

For doing that we need to follow some basic requirements for the integration of the Lease Out contracts on the Financial Database of SAP Bank Analyzer.

The first activity is modeling the Lease Out contracts as Financial Transactions on the Bank Analyzer Source Data Layer by creating a specific template.

Once the Financial Transactions are created in the Source Data Layer, we can transfer the cash-flows generated in SAP Flexible Real Estate module to the Bank Analyzer-Source Data Layer. Alternatively, we can transfer the Lease Out contract Financial Conditions and reproduce the cash-flows generation in the Bank Analyzer SDL.

For the transfer we can use SAP Services or the Extract and Transformation Layer of Bank Analyzer. Since release 8.0 Bank Analyzer has very powerful functionalities for transferring Financial Assets with SAP Services, and in my opinion is also the best option for integrating Real Estate contracts.

Additionally, we’ll have to create new Business Transaction classes and Types, and the correspondent Items, for modeling in the Source Data Layer the accounting events posted on the Lease Out contract.

Finally we’ll have to adjust the calculation procedures of the Processes and Methods Layer for supporting the new Business Transaction Types.

Planned and Actual Maintenance costs of the Real Estate properties are managed by the Plants Maintenance module of SAP ECC, and transferred to Bank Analyzer as expected and actual cash-flows, for generating the correspondent accounting entries in the Lease Out contract sub-ledger.

In conclusion, combining Flexible Real Estate and Bank Analyzer, SAP provides a holistic solution for the management of Real Estate contracts, according to the most recent regulation of the International Accounting Standard Board.

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

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

Monday, June 8, 2015

Omnichannel Architecture and SAP Bank Analyzer.

Dear,
The Digital Banking revolution is transforming the way in which customers interact with banks. Smart-phones, Computers, Phone Banking, Branches or even Social Networks offer multiple communication channels and bring the opportunity for a deeper relationship between the bank and their customers.

On the other hand, obsolete processes and legacy systems are far from being ready to be aligned with the new paradigm. Many, if not most, of the banks are incapable of managing holistically all their interaction channels.

For instance, different channels have different response times, presenting contradictory experiences and generating a distorted image of the bank to the customer and vice-versa.

The response to this challenge is the convergence of physical and virtual channels, putting the customer at the centre; this approach is normally called Omnichannel Architecture.

Personally, I don’t think the name Omnichannel is a fortunate one, digital banking is not only a technical revolution but also a social one. The context of the interaction is as important as the channel through which is happening.

For instance, when we access to a banking service in Facebook, what’s the interaction channel, Internet, PC, Smartphone, Tablet or Facebook?

On the other hand, the context of banking interaction in Facebook is potentially very different to a traditional Online Banking interaction, and they can be both Internet based.

What’s most relevant in this case, the context in which the transaction is requested and fulfilled, the channel in which the interaction occurred, or both analytical dimensions must be analyzed?

Determining the analytical dimensions of the bank’s portfolio will define the analytical business segments, and this is the most critical activity in a Bank Analyzer implementation.

Managing a bank requires analyzing the business segments in which the bank is investing and finding an answer to some important questions.

For instance:

- Expected return weighted by capital consumed in the business segment.

- Liquidity generation and consumption by business segment.

- Value at Risk by business segment.

Digital banking requires defining the business segments according to a multidimensional matrix of customer types, ratings, syndication agreements, origination channels, transaction contexts, etc.

Traditionally; business segments performance has been measured by a combination of manual calculations, spreadsheets and silo based reporting systems, with very limited integration with the accounting and capital management systems.

SAP Bank Analyzer – Integrated Financial and Risk Architecture offers a solution to the above issue with multidimensional capital management and performance measurement tools, fully reconcilable with the Accounting Systems.

There’re some rules to be followed in the definition of the Business segments

-Dimensions should cover, without overlapping, any present or future opportunity for capital allocation.

-Key Figures must be capable of representing, without overlapping, all the necessary performing indicators (fees, costs, capital, short-term receivables, etc.)

Suboptimal definitions of the business segments and performing indicators will limit the future system capabilities. And once the system has been initialized is challenging to modify the structure of the Financial Database, especially for generating historical data according to the new structure, so you better do it right at the first shot.

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

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