Bank Analyzer (FS-BA)  PurposeBank Analyzer supports risk and return management by calculating, measuring, and analyzing financial products. The structure of Bank Analyzer is based on the Integrated Finance and Risk Architecture (IFRA) and meets today's requirements (International Accounting Standards (IAS), Basel II, Risk Adjusted Performance Measurement, and Sarbanes-Oxley) for financial products.

Bank Analyzer is a family of products that consists of the following components

●      Data Load Layer

●      Source Data Layer

●      Processes and Methods

●      Results Data Layer

●      Analytics

●      Infrastructure

●      Tools

 Data Load Layer (FS-BA-DL)  PurposeThis component contains the functions for importing source data and results data from SAP NetWeaver Business Intelligence (BI) to the specific interfaces in the Source Data Layer (SDL) or Results Data Layer (RDL) in Bank Analyzer. This is part of the general extraction, transformation and loading process (ETL process) that you can use to transfer data from your own source systems to Bank Analyzer.

IntegrationThe following graphic shows the components that are part of the ETL process:

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1. Extraction

The system extracts data from operational systems (full load or delta load) and saves the extracted data in SAP NetWeaver BI. The data is stored in DataStore objects, which have the same structure as the data from the feeder system.

2. Transformation

In SAP NetWeaver BI, the system transforms the extracted operational data into an analytical format, and saves this as the result of the transformation process. The analytical format is largely the same as the format used in the inbound interfaces for the Source Data Layer and Results Data Layer.

3. Loading

The system loads the transformation results from SAP NetWeaver BI as InfoProviders into Bank Analyzer.

FeaturesThe load process

●      The Data Load Layer connects the transformed data within SAP NetWeaver BI and the storage locations in Bank Analyzer, and reads the data from the InfoProviders in SAP NetWeaver BI. It calls the relevant interfaces in the Source Data Layer and Results Data Layer.

●      Since the volume of data may be large, the data load process can be run as a parallel job.

●      Custom key figures and characteristics can be transformed flexibly during the data load process if appropriate Customizing settings are made.

Process control

●      Process control is part of the Data Load Layer and is also integrated in the SAP NetWeaver BI technology. This ensures that the complete ETL process is subject to a standard process control and monitoring.

●      The function is integrated into BI technology, which contains the new process chain category FS Data Load Function, which can be used in the definition of a BI process chain. The process is scheduled and monitored in BI.

●      The status of the process is written back to BI.

Tracking of changes

●      Each object that was changed during the transformation process in BI is included in the loading process. The changes are handled as change pointers in the Change Notification Service (CNS). This tool collects all the changes made to an object (in this case the Bank Analyzer primary object) in order to make the all the changes at once.

The change indicators, which are created in BI and stored in Bank Analyzer, are the starting point for the loading process. The loading process updates in Bank Analyzer all the objects that were changed in NetWeaver BI (the update BAPIs are called for the SDL objects, or the APIs are called for RDL data),

●      A log is created of all the primary objects that were changed.

Constraints●      The Data Load Layer does not contain data checks. The system sends data that

has been transformed and mapped directly to the inbound interface of the Bank Analyzer system.

●      Each load process can supply the last version of an object only. It is not possible to process more than one version for each business day.

●      The system does not load business partner data The only way that the system can load business partner data into the Bank Analyzer system is by means of an existing interface for business partners.

 

 

 

 Source Data Layer (FS-BA-SD)  PurposeYou use this component to manage original data for the Bank Analyzer system.

The system uses the Data Load Layer component to load original data from other operational systems or source systems into the Source Data Layer (SDL) by means of an extraction, transformation, and loading process (ETL process). The SDL saves, consolidates, and manages the original data. At the same time it provides interfaces to additional operational systems.

The primary objects of the Source Data Layer (SDL) and their scenario versions are a flexible way of saving master data and flow data. They also group this data into units that belong together logically from a business perspective. This ensures that the Bank Analyzer components that are linked to the SDL have a standard, consistent data source.

In addition to storing primary object data, the SDL provides the following primary objects functions for applications linked to it:

●      Access to Source Data

●      General Functions for Source Data Layer

●      Methods for Source Data

●      General Access to Corrections

●      Tools

IntegrationThe SDL provides both the central original data basis and a part of the underlying infrastructure for linked applications. It is therefore a key element in ensuring the consistency of data and results.

 

 

 Processes & Methods (FS-BA-PM)  PurposeYou can use this component to carry out all financial and risk calculations for Bank Analyzer. Unlike Methods, Processes combine the selection, checking, and processing of data into one step.

The system generates the calculation results using either original data from the Source Data Layer (SDL) or existing results data. Existing results data comes from either source systems or previous calculation steps. The system then stores data that has been completely valuated in the Results Data Layer (RDL).

General Calculation and Valuation Methods (FS-BA-PM-GM)

General calculation and valuation functions provide you with various methods for upstream processing.

 Various Bank Analyzer components can use the results data from this method.

Determination of Net Present Values and Calculation Bases (FS-BA-PM-EIC)

You use this process to calculate net present values and other key figures that you can use as input for calculating funding costs and standard costs. This component calculates funding results, standard cost rates and the effective capital over time, for instance.

Accounting for Financial Products (FS-BA-PM-AFP)

Accounting Processes

Accounting processes comprise business transaction processing and financial position management in Accounting for the subledger scenario.

Cost Accounting Processes

Cost Accounting Processes contain the functions for profitability analysis.

Hedge Processes (FS-BA-PM-HP)

Hedge processes provide various functions for IAS and Basel II. In particular, you can use these service functions for key date valuations and hedge accounting.

Credit Risk (FS-BA-PM-CR)

Credit risk provides up-to-date control instruments for the simulation, planning, and analysis of the overall bank with its different levels. Risk management reflects the reporting obligations imposed by the banking supervisory authorities.

 

 Results Data Layer (FS-BA-RD)  PurposeYou can use this component to store, display, and edit results data. This results data is based on accounting-related or risk-related analyses of financial transactions or financial instruments in Bank Analyzer (Basel II, IAS Financial Reporting), or on analyses using other analysis tools. Results data is stored in the Results Data Layer (RDL) in results data areas in the form of result types.

The RDL is part of the Integrated Finance and Risk Architecture (IFRA). By means of common dimensions (for example, financial transaction ID, financial instrument ID, or legal entities) that are shared by results within a results data area, the RDL provides a basis for the integration of results data. It stores data in an infrastructure that is semantically and technically standardized, which enables standardized usage for existing and future applications that are integrated in the system.

The RDL provides the following functions:

●     Storage of results in results data areas

●     Aggregation 

●     Versioning

●     Archiving

●     External interfaces

●     User Interfaces

 Analytics (FS-BA-AN)  PurposeThis component contains analytical applications that call results data for Processes and Methods from the Results Data Layer (RDL) and, if necessary, continue to process this data.

The Regulatory Reporting Interface, for example, gets data from the RDL and transfers this to the reporting functions in SAP Net Weaver Business Intelligence (BI). The Historical Database gets data from the Source Data Layer (SDL) and processes it as part of data storage based on a time series in accordance with Basel II.

FeaturesComponents Relevant for Accounting

General Ledger Connector (FS-BA-AN-GL)

If you use the sub ledger scenario, the eneral Ledger Connector reads the subledger documents from the RDL and transfers results data to a connected general ledger.

Financial Statement Preparation (FS-BA-AN-FSP)

Financial statement preparation includes Balance Object Manager, Balance Processing, and Aggregated Transactions. In Balance Object Manager you create balance objects (BO) that define the processing level for processes in Balance Processing, in particular the object that is to be included in reporting. Balance Processing loads results data from the RDL and prepares the period-end processing for financial products, such as the balance sheet and income statement including notes to the financial statements.

Merge Scenario (FS-BA-BA)

The merge scenario processes only those financial instruments and transactions whose IAS valuation differs from its valuation according to local GAAP. The merge component converts local GAAP data to IAS data. The system creates a complete IAS balance sheet, including an income statement and notes to the financial statements.

The merge scenario stores the results data not in the RDL but in the Result Database (RDB).

Components Relevant for Basel II

Historical Database (FS-BA-AN-HDB)

The Historical Database is a time-based data store and meets the Basel II requirements for managing historical data. The system can provide the HDB with data from the Source Data Layer (SDL), RDL, or another source system.

Disclosure and Reporting (FS-BA-AN-DR)

The Disclosure and Reporting component provides utilities for selecting and extracting reporting data and meets Basel II requirements of the Capital Accord. The Disclosure and Reporting component supports external disclosure and internal reporting, and provides support for supervisory investigations and stress test reports.

Regulatory Reporting Interface (FS-BA-RR)

The Regulatory Reporting Interface ensures connection to external reporting tools in accordance with Basel II. It loads data from the SDL and RDL, converts it into a fixed format, and provides reporting tools.

Additional Components

Limit Manager (FS-BA-AN-LM)

Limit Manager provides support when determining, analyzing, and limiting counterparty/issuer risks, country risks, or Basel II-specific key figures. Banks set different maximum risk amounts in order to limit the potential harm caused by the insolvency of a business partner. Limit Manager also provides operational functions and supports both internal and external reporting.

Profit Analyzer (FS-BA-AN-PA)

Profit Analyzer ensures that costs and revenues are assigned to the single bank transactions, customers, or other segments that gave rise to them. During the profitability analysis, the system updates results as single items and evaluates them in terms of various criteria. You can use Profit Analyzer to carry out sales planning based on custom characteristics.

Strategy Analyzer (FS-BA-AN-STA)

Strategy Analyzer provides a net present value analysis and a gap analysis for market risk management. The net present value analysis shows the value of a portfolio on a key date. You can use the gap analysis to examine your portfolio with regard to interest rate risks by creating incoming and outgoing payments, liquidity, and net interest income for a longer period of time, for example.

 

Infrastructure (FS-BA-IF)  

You can use this component to call functions that provide central services to the various Bank Analyzer components.

Infrastructure contains the following functions:

Data Load Layer (FS-BA-DL)

Communication and Work list Services

Calculation and Valuation Process Management

Extraction and Reporting Services

Correction Services

General Scenario Management

Settings for XI Services

 Tools (FS-BA-TO)   Purpose You can use this component to call functions that are used in various places in

Customizing for Bank Analyzer. In addition, the following tools are available:

●     Garbage Collector ●     Schedule Manager ●     Segmentation Service

Features Derivation Tool (FS-BA-TO-DE)

The derivation tool enables you to control how the system derives characteristics and key figures from other characteristics and key figures, and how it derives the fixed fields of a field catalog. In Bank Analyzer the system calls derivations from the coding or by using a secondary data source. You can create this secondary data source with the module editor in Customizing for Bank Analyzer.

You can state the derivation environment for deriving the validity of a hedging relationship, for example, in Customizing for Bank Analyzer by choosing Processes and Methods  Hedge Processes  Portfolio Fair Value Hedge Configuration  Derivation of Validity. You use this derivation process in the secondary data source in order to use the characteristics of a transaction to derive whether the transaction is one of the qualified positions or unqualified positions in hedge accounting.

Module Editor (FS-BA-TO-ME)

The module editor generates modules that contain a sequence of processing steps. The modules are used to enrich user-defined information and provide the system with secondary data sources.

An application makes entries into the fields of an input structure and calls the module. The system applies each processing step of the module in the sequence defined in Customizing. The system can call function modules, derivations, or primary data sources within the module. The system then makes entries into fields of the output structure.

Modules can have various functions. The selection module of the Strategy Analyzer, for example, selects data using the Primary Data Source processing step. The calculation module of Profit Analyzer carries out complex calculations for the processing steps formula, derivation, and function module.

You can find the settings for the module editor, for example, in Customizing for Bank Analyzer by choosing Bank Analyzer  Analytics  Profit Analyzer  Profit Engine  Calculation  Edit Modular Costing.

Result Database (FS-BA-TO-RDB)

The Result Database (RDB) is a database in which the system saves results data permanently. Results are then available for further processing, by reporting, for example, or for additional calculation runs.

The RDB and the Results Data Layer (RDL) are two different results databases in

which the system can store results data. Each database is based on different principles. The RDB is found in a variety of forms in Bank Analyzer. These forms depend on the various areas (Financial Accounting, Basel II). The RDL is a standardized results data store for accounting and risk-based analyses of financial transactions or financial instruments.

For the long-term we recommend that you use the central RDL to store results data in a standardized way. In Customizing for Bank Analyzer you can choose whether the system is to store Basel II-specific results data in the RDB or the RDL.

Processing Framework (FS-BA-TO-PFW)

The Processing Framework supplies the processing rules with data from various data source categories. The calculation and allocation processing rules are available in Profit Analyzer, for example. The system uses suitable selection conditions to create a worklist. The system can also add further information using a secondary data source. The result records generated by the processing rules are forwarded to the temporary buffer, The system provides verification lists which you can use to check whether the result records are plausible from a business perspective. The result records are then updated in data drains.

You can also start the processing steps manually. In a typical scenario, you include the processing steps in the Schedule Manager which then carries out an automatic month-end processing on the basis of this.

Run Administration (FS-BA-TO-RUN)

Run administration provides you with various processing functions for the runs in the individual Bank Analyzer applications. Run administration therefore enables standard, general run administration.

Aggregation Tool (FS-BA-TO-AGT)

The aggregation tool is used to aggregate data from primary and secondary data sources, BAPIs, and the Data Processing Framework. The aggregation type is determined using granularities such as the branch or the business partner. Possible aggregation functions are determining minima, maxima, totals, or the number of occurrences of a certain value.

You can find the settings for aggregation, for example, in Customizing for Bank Analyzer by choosing Analytics  Historical Database  General Settings for the Historical Database  General Settings for Data Selection  Settings for Aggregation Processes. You can use the Aggregation Business Add-In (BAdI) to override the results from the aggregation process you defined in the IMG activity Edit Aggregation. This enables you to change individual results.

Data Processing Framework (FS-BA-TO-DPF)

The Data Processing Framework provides selection processes for processing data to the Historical Database, the Limit Manager and Bank Analyzer-wide to generic BI data extraction and generic ad hoc reporting For example, you determine the

selection settings in Customizing for the -Historical Database in the Edit Basic Settings for Data Sources section. Every selection is assigned to a fixed context (application of the Data Processing Framework) which is, in turn, assigned to a certain application of the module editor. Data processing that is either triggered by a report or by generic data extraction, for example, can contain both selection BAdIs as well as aggregations and general selection criteria.

Configuration (FS-BA-TO-CON)

The configuration shows characteristics and key figures and generates customer-specific database tables and field structures for further processing. The system calls these processes "generation". The system currently uses only both Bank Analyzer accounting scenarios for generation. For more information, see the documentation about Generation.

 

The division of the components ensures that data is stored in an integrated and consistent way. The system loads original data from operational systems or source systems into the Source Data Layer (SDL). The SDL is the original data basis for the processes and methods of Bank Analyzer. The valuation results of processes and methods are stored in the Results Data Layer (RDL). This structure ensures that original data, methods, and valuation results are clearly separated. The open, modular structure of Bank Analyzer supports a gradual implementation into existing system landscapes.

Bank Analyzer provides a consistent view of a bank's operational data and enables you to process data promptly so that you are always in a position to provide current financial and risk information. Results data is therefore always available for decision-making and for day-to-day business.

The figure below shows the structure of Bank Analyzer:

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1.        1.      The SDL manages the basic data for the measurement of financial products. This data is loaded from the operational source systems by means of extraction, transformation, and loading (ETL) processes.

The SDL is the source for semantically integrated data for all valuation processes that are based on financial products, and is also a central consolidated source for analyses.

The SDL is not used to store data that has already been analyzed completely. Instead, this data is stored in the RDL.

2.        2.      The RDL manages consistent and reusable financial and risk data from various calculation and valuation processes for financial instruments and financial transactions.

3.        3.      Reporting and Analytics read results data from the RDL. The Analytics layer contains analytical applications that call results from the RDL and process them as required. This means that results data is analyzed specifically for each application.

4.        4.      Infrastructure and Tools provide central services and utilities for the various Bank Analyzer components.

In addition to the RDL, Bank Analyzer also has a Result Database (RDB). RDL and RDB are two different results databases where the system can store results data. The RDB is found in a variety of forms in Bank Analyzer. These forms depend on the various areas (Financial Accounting, Basel II). The RDL is a standardized results data store for accounting and risk-based analyses of financial transactions or financial instruments.

IntegrationThe integrated data store for product-based source and results data is based on SAP NetWeaver Business Intelligence technology. SAP Net Weaver is the basis for integrating Bank Analyzer in various IT environments and internal bank solutions.

FeaturesBank Analyzer contains the following solutions:

SAP Financial Database

The SAP Financial Database solution offers an extensive database infrastructure for analytical data and accompanying data processing systems. It is technically compatible with other SAP applications and with third-party applications.

SAP Financial Database uses the following Bank Analyzer components:

●      SDL (FS-BA-SD)

●      RDL (FS-BA-RD)

●      ash Flow Generation (FS-BA-PM-GM-CFG)

●      Correction Server (FS-BA-IF-CS)

The system uses ETL processes to load original data from other systems or source systems into the SDL in the form of primary objects. Primary objects are a flexible way of storing master data and flow data in entities that belong together logically from a business perspective.

Results data from financial calculations and valuations are stored in the RDL in results data areas in the form of result types. The SAP Financial Database uses the SDL and RDL to support the extensive versioning and authorization concept. In the SDL it provides functions to support the principle of dual control. This means that you can define special release rules to protect certain processes.

Cash flow generation generates cash flows that are made up of a number of flows (for example, disbursement, interest, payment).

The correction server enables data flow management and records corrections to find and display any inconsistencies. The correction server records corrections and can find and

display any entities belonging to these corrections, provided the relevant system settings are made.

SAP Basel II

The SAP Basel II solution supports the Basel II regulations for risk and capital adequacy management as well as new supervisory review and disclosure processes. The solution integrates both internal and external credit risk management on a central platform. Bank Analyzer supports all methods for calculating credit risk, from the standardized approach to the IRB advanced approach.

In addition, the software covers the local requirements for the EU Directive and the German Solvency Regulation. You can use Customizing settings to define whether the calculation is for Basel II, the EU Directive, or the German Solvency Regulation.

The system runs the calculation not only for real data, but also for stress data (for example, changes in the ratings of sovereigns or business partners).

The SAP Basel II solution uses the following Bank Analyzer components:

●      Account Pooling (FS-BA-PM-GM-AP)

●      Free Line (FS-BA-PM-GM-FL)

●      Determination of Default (FS-BA-PM-GM-DD)

●      Credit Exposure (FS-BA-PM-CR-CE)

●      Historical Database (FS-BA-HDB)

●      Disclosure and Reporting (FS-BA-DR)

●      Regulatory Reporting Interface (FS-BA-RR)

SAP Accounting and Financial Instruments

The SAP Accounting and Financial Instruments solution supports compliance with the International Financial Reporting Standards (IFRS) and local accounting standards.

Sub ledger scenario

In this scenario you use Bank Analyzer as a subledger for the accounting of financial instruments. You transfer financial instrument data to the Bank Analyzer system here. You can then post and price the related business transactions, aggregate documents, and transfer them to the general ledger. You can also create the financial statements for the end of the period. You can link the hedging relationships between financial instruments, test the effectiveness of the hedging relationships as per the accounting rules, and create accounting documents for the hedged items.

In addition to the SDL and the RDL, the subledger scenario uses the following components:

●      Accounting Processes

●      Hedge Processes (FS-BA-PM-HP)

●      General Ledger Connector (FS-BA-AN-GL)

●      Financial Statement Preparation (FS-BA-AN-FSP)

SAP Accounting for Financial Instruments is released for volumes of up to 1 million financial transactions only. If the volume of your business exceeds 1 million transactions, a fit/gap analysis is required. For more information, contact your SAP account executive, or create an OSS message under component FS-BA.

Merge scenario

You can use this scenario to process financial instruments in accordance with IFRS, determine financial reporting data, consolidate data from individual companies, and

create company reports. The system merges the calculated IFRS data with the local GAAP (Generally Accepted Accounting Principles) data and calculates the required financial statement items. You can link the fair value hedging relationships between financial instruments, test the effectiveness of the hedging relationships as per the accounting rules, and create accounting documents for the hedged items. You can display the results in reporting.

The merge scenario stores results data in the RDB.

SAP Hedge Management

The SAP Hedge Management solution handles all hedging activities in line with IAS 39. Bank Analyzer covers fair value hedges, cash flow hedges, and portfolio fair value hedges. The system identifies hedged objects and hedging instruments, and maps these as hedging relationships in line with IFRS. Bank Analyzer provides prospective and retrospective effectiveness tests, and extensive functions for hedge accounting.

SAP Profitability & Management Accounting

This solution comprises scenarios for profitability analysis. Profitability analysis measures the indirect costs and income generated by each transaction in the bank's retail business. These include cash-flow-based financial transactions such as loans and accounts that can be measured on the basis of periodic volume information. The indirect costs and income to be measured are funding costs, funding revenue, and the standard costs for the following components: process costs, risk costs, and the cost of equity.

●      Profitability analysis with accounting function (integrated accounting for financial products)

You can use this scenario in conjunction with the subledger scenario for financial products only. It allows you to integrate financial accounting and management accounting. The integrated accounting scenario allows you to create income statements and balance sheets for organizational units such as business units or profit centers.

●      Profitability analysis without accounting function

In this scenario, you supply direct costs from source systems and use the profitability analysis functions without the Bank Analyzer component for accounting processes.

SAP Profitability Analysis & Management Accounting and SAP Limit Manager are released only for volumes not exceeding 300 000 transactions. If the volume of your business exceeds this, a fit/gap analysis is required. For more information, contact your SAP account executive, or create an OSS message under component FS-BA.

Additional Components

●      Limit Manager (FS-BA-AN-LM)

See the note under SAP Profitability Analysis & Management Accounting.

●      Strategy Analyzer (FS-BA-AN-STA)

●      Profit Analyzer (FS-BA-AN-PA)

●      Counterparty Risk

●      Country Risk

 

Limit Manager (FS-BA-AN-LM) PurposeTo meet the requirements of risk management regulations and business considerations, Bank Analyzer contains functions for measuring, limiting, and analyzing default risks.

Banks set different maximum risk amounts in order to limit the potential harm caused by the insolvency of a business partner.

This function helps you manage defaults by means of limits and the online monitoring of these limits. These functions can be used to produce comprehensive reports for management purposes and for external purposes.

IntegrationLimit Manager is part of Bank Analyzer. It uses the attributable amounts calculated from Credit Exposure, for example, and allocates them to the limits you define. You can display the results of the limit utilization runs using the SAP List Viewer (ALV) or SAP NetWeaver Business Intelligence (BI).

For more information, see Architecture of Limit Manager.

FeaturesYou use Limit Manager to manage risks by defining limits and monitoring them continuously to ensure that these limits are observed. Limits can be managed flexibly, since the limit characteristics that are available can be combined in any way.

Limit Manager enables you to define different levels for the limitation of default risks. The limit area represents the highest level, and is used to separate different areas that are logically independent. There are different limit types for each limit area. You assign defined limit characteristics, such as an organizational unit, a business partner, or currency, to the limit types. Within a limit, you define specific limit amounts that are related to the characteristic values of a limit type.

You can create a limit for each combination of limit characteristics and limit characteristic values. The limit is a maximum amount for limit utilizations that is defined in relation to certain values of the limit characteristics of a limit type.

 

Architecture of Strategy Analyzer IntegrationStrategy Analyzer is one of the Bank Analyzer applications. As is the case with the other applications, Strategy Analyzer is also provided with data from the Source Data Layer (SDL). Reporting functions are provided by SAP NetWeaver Business Intelligence (BI) or directly in Bank Analyzer by the SAP List Viewer (ALV)

SAP provides fixed key figures for NPV analysis and gap analysis in Strategy Analyzer; you cannot change these key figures. SAP provides pricing models for the valuation of financial transactions and instruments. You can add your own pricing models in Customizing, and you can also connect external price calculators.

Strategy Analyzer uses the General Calculation and Valuation Methods component in Bank Analyzer, which contains cash flow refinement methods , derivation strategies for preparing selected transaction data, and the price calculator for pricing transactions and positions.

 

Data FlowsStrategy Analyzer uses the same architecture for the net present value analysis and the gap analysis. For this reason, Strategy Analyzer is divided into two runs: the valuation run and the aggregation run. The valuation run prices transactions, and the aggregation run consolidates cash flows and net present values across a maturity band. In net present value analysis, you start the valuation run only. For gap analysis, however, you start both the valuation run and the aggregation run, except for the aggregation of single records in gap analysis, in which the results of a valuation run are displayed without being consolidated.

NPV and gap analyses can be started online or as batch jobs. We recommend you start them in online mode only if the volume of data is small. In batch processing, Strategy Analyzer uses the Result Database (RDB) for interim results (IntR-RDB) and final results (FinR-RDB):

In online processing, only the main memory is used and not the RDB. Moreover, reporting can only be carried out in the SAP List Viewer (ALV).

You can write the results of the valuation runs to a file. You make this setting in Customizing for Strategy Analyzer for each valuation run type. If you select File as the data drain, the system writes the results of the valuation run to the application server in the form of a file. This file is then also available to other systems, as well as Bank Analyzer. The administrator of the application server has to ensure that only authorized users can access the data. We also recommend that you encrypt the data.

DependenciesNot all valuation run results can be saved in file form on the application server. This is possible for split cash flows only.

 

Valuation Run

Valuation runs are started for net present value analyses and gap analyses. In order to improve performance, a valuation run is usually divided into subvaluation runs

that are started separately and that are processed in parallel. Each subvaluation run involves the following steps:

●      Creation of a worklist

The system uses InfoSets and selection characteristics to select the object IDs of the transactions and positions that are to be analyzed from the SDL.

You can use selection criteria to restrict the worklist of a valuation run or its subvaluations. You might need to do this if, for example, you assign a valuation run multiple subvaluations that are provided by the same InfoSet but that you want to process in different worklists. The selection criteria must not overlap, but they must make up the entire valuation run worklist.

●      Selection of transactions and positions

The transactions and positions are selected in the secondary data source.

●      Formatting of cash flows

In the secondary data source, the system calls up the Cash Flow Engine. The Cash Flow Engine contains multiple cash flow refinement methods that the system uses to change the valuation structure of transactions and positions in order to prepare the data for the analysis.

●      Measurement of transactions and positions

The system calculates the key figures of the selected key figure family (net present value or gap).

●      Summarization of the segments

In order to improve performance and reduce the volume of data, the system summarizes the results before it writes them to the Result Database and displays them there. Summarization is carried out for the segments defined in Customizing for Strategy Analyzer.

Aggregation Runs

The aggregation run is started for gap analysis only, and involves the following steps:

●      Maturity band summarization

The system summarizes the interim results along the maturity band.

●      Calculation of the net interest income

●      Segment hierarchy summarization

The system summarizes the interim results across the specified segment hierarchy along the maturity band.

●      Currency translation

The system translates the results into the display currency.

●      Interpretation

The system formats the aggregated gap analysis results and the net interest income in such a way that a complete result is available for each maturity band date. The system carries out this step for all the reporting settings that were determined in Customizing for the aggregation run.

 

 

 

 Net Present Value (NPV) Analysis 

PurposeTo obtain an objective view of the financial and risk position of a bank, it has to be possible to value all financial assets by the sales price realizable on the market, and all financial liabilities by the redemption price demanded by the market. The net present value analysis in Strategy Analyzer is used for this purpose. This analysis enables the mark-to-market values of individual items or of a portfolio, for example, to be calculated.

In addition to the mark-to-market valuation, financial transactions and financial instruments can also be valued at theoretical prices. This is particularly useful if you are unable to carry out a mark-to-market valuation of the items or cannot because market data is missing.

In the net present value analysis, you can enter any horizon you want so that the system can carry out evaluations for the current date and for future dates. You can also specify market data scenarios that the system is to use. This results in the following options for carrying out the net present value analysis:

●     Evaluation today based on current market data

All future cash flows are priced using the specified current market data, and the net present value is discounted to the horizon.

●     Evaluation using scenario data

All future cash flows are priced using the specified market data scenarios, and the net present value is discounted to the horizon date.

●     Evaluation in the future using forward rates

Transactions and positions are priced for a horizon in the future. Here the system calculates forward rates for the horizon from the current market data or market data scenarios on the evaluation date. It uses these forward rates to price all cash flows after the horizon date by discounting the net present values for the horizon date.

 

You can also carry out the net present value analysis for historical dates. In this analysis, the system also uses the market data that is valid on the evaluation date (here, the historical market data).

The transactions are selected from the Source Data Layer (SDL) by using selection characteristics, which you can define as required. A large number of settings are provided for the NPV analysis. These settings can be used to define how the net present values are displayed in reporting and include cash flow splitting and cash flow view settings.

 

The relevant bid/ask spreads quoted on the market can be used for the financial positions in the NPV analysis. The system also prices transactions that are traded in different markets (German federal bonds or mortgage bonds) using yield curves that are specific to these markets. Likewise, the system uses different volatility curves to calculate the prices of standard options and exotic options.

 

Process FlowDepending on the volume of the data that is to be analyzed, you should either start the NPV analysis immediately (online processing) or schedule it for a later point in time (batch job).

Online analysis

The analysis is called immediately, and the report is generated straight away. This type of analysis is suitable for small volumes of data only.

Batch evaluation

The NPV analysis and the reporting of the results of the analysis are scheduled to start at a later point in time. This method is recommended for large volumes of data.

You can display the results of the NPV analysis in reporting.

 

 Net Present Value (NPV) Analysis PurposeTo obtain an objective view of the financial and risk position of a bank, it has to be possible to value all financial assets by the sales price realizable on the market, and all financial liabilities by the redemption price demanded by the market. The net present value analysis in Strategy Analyzer is used for this purpose. This analysis enables the mark-to-market values of individual items or of a portfolio, for example, to be calculated.

In addition to the mark-to-market valuation, financial transactions and financial instruments can also be valued at theoretical prices. This is particularly useful if you are unable to carry out a mark-to-market valuation of the items or cannot because market data is missing.

In the net present value analysis, you can enter any horizon you want so that the system can carry out evaluations for the current date and for future dates. You can also specify market data scenarios that the system is to use. This results in the following options for carrying out the net present value analysis:

●     Evaluation today based on current market data

All future cash flows are priced using the specified current market data, and the net present value is discounted to the horizon.

●     Evaluation using scenario data

All future cash flows are priced using the specified market data scenarios, and the net present value is discounted to the horizon date.

●     Evaluation in the future using forward rates

Transactions and positions are priced for a horizon in the future. Here the system calculates forward rates for the horizon from the current market data or market data scenarios on the evaluation date. It uses these forward rates to price all cash flows after the horizon date by discounting the net present values for the horizon date.

 

You can also carry out the net present value analysis for historical dates. In this analysis, the system also uses the market data that is valid on the evaluation date (here, the historical market data).

The transactions are selected from the Source Data Layer (SDL) by using selection characteristics, which you can define as required. A large number of settings are provided for the NPV analysis. These settings can be used to define how the net present values are displayed in reporting and include cash flow splitting and cash flow view settings.

 

The relevant bid/ask spreads quoted on the market can be used for the financial positions in the NPV analysis. The system also prices transactions that are traded in different markets (German federal bonds or mortgage bonds) using yield curves that are specific to these markets. Likewise, the system uses different volatility curves to calculate the prices of standard options and exotic options.

 

Process FlowDepending on the volume of the data that is to be analyzed, you should either start the NPV analysis immediately (online processing) or schedule it for a later point in time (batch job).

Online analysis

The analysis is called immediately, and the report is generated straight away. This type of analysis is suitable for small volumes of data only.

Batch evaluation

The NPV analysis and the reporting of the results of the analysis are scheduled to start at a later point in time. This method is recommended for large volumes of data.

You can display the results of the NPV analysis in reporting.

 

 Gap Analysis PurposeGap analysis enables banks to monitor and manage interest rate risks from transactions so they can make strategic decisions with regard to gap positions for defined points in time. Liquidity analysis and the cash flow evaluation enable banks to manage their liquidity requirements and NPV risks.

In contrast to NPV analysis, where risks are recorded using NPVs and future values, in gap analysis, position and maturity volumes as well as cash flows and liquidities are displayed on key dates or for periods. The gap positions, interest rate risk, currency risk, and liquidity risk that are disclosed in this way are then displayed.

You can carry out gap analysis for single transactions or for user-defined segments in a segment hierarchy. In reporting, you can switch between different segment hierarchy levels and display the results by different cash flow views, market data scenarios, and currencies.

The Strategy Analyzer gap analysis includes the following evaluations:

Position evaluation

The system compares the development of lending and borrowing positions from both the balance sheet and off-balance-sheet areas. You can carry out both a key date position evaluation and an average position evaluation.

Maturity evaluation

The system shows the NPV interest rate risk by using; the fixed-rate cash flows. You can restrict the evaluation to particular currencies.

Cash flow evaluation

The system displays the NPV interest rate risk; the cash flows cash flows are displayed only up to the time point at which the interest rate was fixed. You can restrict the evaluation to particular currencies.

Liquidity evaluation

The system depicts the incoming and outgoing payments for the capital tie-up. In contrast to the cash flow evaluation, only incoming and outgoing payments that are expected to be realized are displayed.

NPV evaluation

The system displays the NPVs of a portfolio or the associated cash flows in the maturity band. You can also use market data scenarios in the analysis. You can calculate full scenarios and delta scenarios.

Net interest income evaluation

The system calculates the potential net interest income for each maturity band. The capital tie-up is used as the basis for this. For variable items, the interest revenue or the interest expenses that has not been determined is calculated using the forward interest rate.

If the default setting is used, the system does this in all evaluations. In gap analysis, you can specify that the system does this for certain evaluations only in order not to impair system performance. For more information, see Creating Valuation Runs.

You can use gap analysis as follows:

●     To display the interest rate risk as a potential negative deviation in the net interest income per period from the expected net interest income per period

●     To display position volumes for key dates and for periods and maturity volumes for key dates and periods in terms of their fixed interest rates and capital tie-up, and to display fixed-rate cash flows and incoming and outgoing liquidity

●     To display gap positions as a comparison of the volume of lending and borrowing positions, and maturity volumes, as well as incoming and outgoing cash flows or liquidity flows

●     To analyze positions, maturity, and cash flows from fixed-rate items for any subportfolio on a daily basis

●     To display the net interest income for old business whilst using scenarios

●     To include variable items without a fixed-interest period by means of due date scenarios (demand deposits and savings deposits) and forwards (for example, floaters, the variable side of swaps and forward rate agreements) in the analyses

●     To include non-interest-bearing items without a fixed-interest period by using due date scenarios (for example, equity, provisions, land, and buildings) in the analyses

●     To include optional interest rate instruments and their underlyings or delta-weighted underlyings (for example, forward swaps for swaptions, (fictitious) bonds for OTC interest rate options, options on futures) in the analyses

●     To display the results distributed over maturity bands, which can be subdivided into any time period, for example, day, month, quarter, half-year, and year

 

ExampleAn interest rate risk exists, for example, if a fixed interest rate gap exists in the lending positions for a particular currency. The diagram below illustrates this:

In the closed fixed interest rate block area, there is no risk because the product interest rates of the assets and liabilities are not affected by the market interest rates. The net interest income is therefore not affected by changes in the market interest rate. In the closed variable-rate block, it is assumed that the changes in the market interest rates are reflected in both the asset-side and the liability-side items, meaning that the final net interest income is unchanged in this block too.

Therefore, the actual risk is seen in the area of the fixed interest rate gap; in the area under “Assets” in this example. If, for example, the interest calculated for the variable-rate liabilities increases as a result of increases in the market interest rate, then you expect a decrease in the net interest income.

 

PrerequisitesSettings have to be made for the gap analysis in Customizing for the General Calculation and Valuation Methods and for Strategy Analyzer. For information about this, see Strategy Analyzer Architecture.

 

Process FlowDepending on the volume of the data you want to analyze, you should either start the gap analysis immediately (online processing) or schedule it for a later date (batch processing).

Online evaluation

The analysis is called immediately, and the report is generated straight away. This type of analysis is suitable for small volumes of data only.

Aggregation of valuation runs

The aggregation run is called immediately on the basis of a valuation run that has already been carried out. The results are displayed straight away.

Batch evaluation

The gap analysis and the reports are scheduled to run at a later point in time. This method is recommended for large volumes of data.

 

The system stores the results of the gap analysis in the Results Database (RDB). Reporting is carried out in SAP NetWeaver Intelligence (BI) or the SAP List Viewer (ALV).

 

Run Administration  DefinitionRun administration includes the following functions:

●     Execute or create run

●     Display an overview of runs

●     Display application log

●     Edit run

●     Manage run

●     Replace run

●     Select run for archiving

●     Delete run

●     Log of deletion function

The above functions are not all available for each application. For more information, see the application-specific documentation.

UseThe following table lists the runs available for each application:

Application Run

General Methods in Bank Analyzer Account Pooling  

Facility Distribution

Determination of the Free Line

Collateral Distribution

Determination of Default

Stress tests:

Stress test for account pooling

Stress test for facility distribution

Stress test for the determination of the free line

Stress test for collateral distribution

Stress test for default determination

Credit Risk Credit Exposure Run

Country Risk Run

Stress test:

Stress Test in Credit Exposure

Historical Database Version management:

Historization Run for Data Layers 

Historization Run for Bank’s In-House Models

Uploading of Files

Calculation functions:

Determining Default Rates 

Determining Average Default Rates 

Determining Default Figures 

Calculation of Migration Matrices 

Data retrieval:

Exporting Data to In-House Models

Downloading of Files

Stress runs:

Stress Run for Supplying Models with Data

Generation of Scenario Data in the Source Data Layer

Generic BI Data Extraction Testing the BI Extractor

BI Extraction Run

Extraction runs are created and executed in SAP NetWeaver Business Intelligence (BI).

The system displays information about extraction runs in run

administration of Bank Analyzer.

Regulatory Reporting Interface Data Extraction Runs

Limit Manager Limit Utilization Run

Strategy Analyzer Valuation Run

Subvaluation Run

Aggregation Run

Fair Value Effectiveness Test for Hedging Relationships

Fair Value Effectiveness Test Run

Cash Flow Hedge Analysis Creating Valuation Runs

Subvaluation run

Creating Aggregation Runs

Portfolio Fair Value Hedge Initial Generation Run

Portfolio Item Run

 

For some of the Bank Analyzer components, you can use the Schedule Manager to schedule and control jobs. If you use multiple applications, you can define the sequence in which the runs are to be carried out. For more information, see Schedule Manager.

See also: Status Overview for Run Administration

 

 Tools 

In order to provide an overview of the evaluation bases while the system is in operation, you can display the individual Customizing settings. You have the following options:

        Displaying Field Instances

        Editing Secondary Data Sources

 

 

Current Settings You can change the following Customizing settings in your operational system:

●      Create Maturity Band

●      Edit Due Date Scenario

●      Edit Scenarios and Scenario Progressions

To set up scenarios, on the SAP Easy Access screen choose Bank Analyzer  Processes and Methods  Hedge Processes  Cash Flow Hedge

Analysis Current Settings  Edit Scenarios or Bank Analyzer  Analytics  Strategy Analyzer  Current Settings  Edit Market Data Scenarios.

To set up scenario progressions, on the SAP Easy Access screen choose Bank Analyzer  Processes and Methods  Hedge Processes  Cash Flow Hedge Analysis  Current Settings  Edit Scenario Progressions or Bank Analyzer  Analytics Strategy Analyzer  Current Settings  Edit Scenario Progressions.

For information about other functions, see the document Market Data Scenarios in the Source Data Layer (SDL) documentation.

The Strategy Analyzer contains the function Edit Filter.

 

 Tools 

In order to provide an overview of the evaluation bases while the system is in operation, you can display the individual Customizing settings. You have the following options:

        Displaying Field Instances

        Editing Secondary Data Sources

 

 

 Profit Analyzer (FS-BA-PA) Purpose

This component provides a costing and allocation system that allows costs and revenues to be assigned to individual bank transactions, customers, profit centers, or other definable segments in a way that reflects their true cause.

The results are updated as line items as part of a profitability analysis and can be evaluated in accordance with various user-defined criteria. The results can be evaluated on the basis of market segments, such as products, customers, regions, or organizational units, for example, a profit center. In this way, Profit Analyzer allows you to cost, for example, a product, a customer, or a profit center.

Profit Analyzer can also be used to plan sales on the basis of user-definable characteristics and key figures.

Features

Profit Analyzer is divided into the following components:

...

5.        1.      Profit Engine6.        2.      Profitability Analysis7.        3.      Profitability Planning

 

...

8.        1.      Profit Engine

In the Profit Engine, individual contracts, or any other segments, are costed by means of modular costing. A variety of valuation functions that can be combined are provided for this purpose. The allocation module carries out allocations between individual segments. The processing framework provides data, manages and logs processing, and updates the results.

9.        2.      Profitability Analysis

All the results determined by the Profit Engine are consolidated in Profitability Analysis. In terms of processes, Profitability Analysis is responsible for the following subprocesses:

         Depicting completed periodic contribution margin accounting and Profitability Analysis.

         Structuring and updating line items

         Providing data at any aggregation level

         Providing results data for internal and external access

         Data flow and controlling through Profitability Analysis

Complete profitability analysis means period-specific contribution margin calculation after all allocations have been carried out.

Profitability Analysis is part of Business Accounting (B-Accounting). For more information, see the relevant documentation.

10.        3.      Profitability Planning

Profitability Planning in Profit Analyzer supports the overall process of sales planning of instrumental reporting for financial institutions. User-defined key figures are planned. They are classified by user-defined characteristics.

In order to carry out operative sales planning, Profit Analyzer uses the SAP SEM-BPS application. This application is shipped separately and is not integrated in Profit Analyzer. For more information, see the documentation on the SEM-BPS application.

 

 Profitability Management  DefinitionBusiness Accounting is both the most important data drain and a Profit Analyzer data source. To enable Profit Analyzer to use Business Accounting, you have to make specific settings for Profit Analyzer (Profitability Management) in addition to the basic accounting settings.

These settings concern in particular:

(Profitability management view) variant

Line items

Realignment

Special key figures

UseSet Up a Variant

A profitability management view is a variant of a set of basic data (the data basis). The data basis is the highest entity in Business Accounting. The accounting systems are provided with the key figures and characteristics of the data basis. The variant contains the key figures and characteristics of a data basis that are relevant for Profit Analyzer and comprises a consistent analysis of profitability (calculation/contribution margin accounting) in Profitability Management (not to be confused with the “entry variant” for line items).

Only one variant can be active for each data basis. The active variant is the central data store for Profit Analyzer. You use the variant to first store the Profit Analyzer data as line items in Business Accounting, and then as totals records (aggregated line items) in an InfoCube in SAP NetWeaver Business Intelligence (BI). From this InfoCube, Analyzers can

request the data via a primary or secondary data source; see also: Data Storage for Accounting Views.

Line Items

You can create line items manually if data was not supplied from the source systems on time or correctly.

This is a delta correction, in which missing values (such as key figures) are added, and existing documents are not overwritten.

Example:

The nominal volume of a transaction has been incorrectly entered as 1 million instead

of 1.2 million. You have to create a new line item with the same characteristic values

and a nominal volume of 0.2 million.

If you need to change the characteristic values of a posted document, you first have to cancel the original document and then create a new document that contains the correct characteristic values.

Example:

A business transaction was assigned to the wrong organizational unit. You have to

cancel the original document and then post a new document that contains the correct

organizational unit.

The posting date of the new document can be either in the past or in the future. The system displays all the characteristics and key figures of this data basis variant. You use the entry variant to determine whether fields can be maintained or whether they are predefined. Note that when you enter a currency, the key figure currency of all the key figures that refer to this currency field contains the new currency.

Realignments

Realignment is the process in which you change the structure of a company, template hierarchy, or organization, for example. During this process, postings that have already been made are adjusted retroactively. Two InfoCubes are available for this purpose: The first InfoCube (As Posted view) contains the data originally posted. The other InfoCube (By Current Structure view) contains the changed data as if the new structure had always existed in this form.

Special Key Figures

You use BI technology to calculate key figures at runtime. These calculated key figures (special key figures) are to be used in addition to the updated key figures, and can be defined in Profitability Management. You can define your own aggregation processes in addition to using the BI logic for aggregating values.

Activities...

11.        1.      Set Up a Variant

To set up a variant, in Customizing for Bank Analyzer choose Analytics  Profit Analyzer  Profitability Management  Set Up Variant.

When you set up a variant, you have to consider the following issues:

○       Which basis key figures, calculated key figures, and characteristics you want to use for costing/contribution margin accounting.

○       Are any realignments planned? If so, which characteristics are affected? ○       The more characteristics and characteristic values you include in the

variant/InfoCube, the more time the system requires for the analyses.

12.        2.       Line Items

In order to enter line items later, you first have to create an entry variant.  To do so, in Customizing for Bank Analyzer choose Analytics  Profit Analyzer Profitability Management  Line Items  Characteristic and Key Figure Groups/Entry Variants.

An entry variant is the form that you use to update line items for corrections, for example, in Profitability Management. Entry variants are therefore a selection of characteristics, characteristic values, and key figures that define the part of the variant of the data basis that you want to correct. You can create any number of entry variants.

When you create an entry variant, you have to consider the following issues:

○       Which characteristics and key figures are to be entered? ○       Which fields should be required entry fields? ○       Which fields should contain default values? If required entry fields

contain default values, can these default values be overwritten? ○       Whether the calculation module can be used to fill additional fields that

are locked for entry.

To enter line items, you can use an authorization concept based on characteristics or apply a calculation module to the data that was entered to check whether the data is plausible, or for calculation purposes, for instance.

To assign a calculation module and a characteristic profile to an entry variant, in Customizing for Bank Analyzer choose Analytics  Profit Analyzer Profitability Management  Line Items  Assign Costing Module and Characteristic Profile to a Screen Variant.  You can determine whether a calculation module is to be used and if so, which one. If no calculation module is run, the data is forwarded directly to the data store in order to be updated.

To enter a line item, on the SAP Easy Access screen choose Bank Analyzer  Analytics  Profit Analyzer  Profitability Management  Line Item Entry for Corrections.

To use the document you have just posted as a template, choose Transfer Template. You can change this template.

Two additional options are also provided for filling a new document

(you can choose New Line Item to empty the fields):

         To use an existing document as a template, choose Environment  Line Item Entered Manually. You can select a document and choose the appropriate pushbutton to use it as a template.

         To display and cancel the source document, choose Environment  Line Item Entered Manually  Source Document.

To call a calculation module and to carry out a valuation, choose Valuation. The result of the valuation is displayed, but not updated. You must have already set up the calculation module and assigned it to an entry variant.

You can also choose Simulation to carry out a valuation. In this case, however, the documents are also displayed in the form in which they would appear if they were posted in Business Accounting.

To post the documents, choose Save. When you post the documents, the system checks the authorization in accordance with the characteristic profile that you have assigned to the entry variant.

The valuation is also carried out when you post the documents. Once you have posted the documents, the system automatically notifies the orrection server.

Two IMG activities are required for this purpose:

         In Customizing under Bank Analyzer  Infrastructure  Communication and Worklist Services  Data Sources  Primary Data Sources  Edit Primary Data Sources.

         In Customizing under Bank Analyzer  Infrastructure  Correction Services  Edit Correction Components.

See also: Entry of Line Items.

13.        3.      RealignmentTo define a realignment, on the SAP Easy Access screen choose Bank Analyzer  Analytics Profit Analyzer  Profitability Management  Edit Realignments.

Create a realignment request. When you do so, the data affected by the realignment is selected for a data basis. The actual realignment is executed in the realignment run.

To execute a realignment, on the SAP Easy Access screen choose Bank Analyzer  Analytics  Profit Analyzer  Profitability Management  Execute Realignments.

You use a derivation strategy or an externally defined method to execute the realignment. You can define how the data is realigned for each characteristic.

For more information, see Realignment in the Business Accounting documentation. You can define that the realignment process is to be subject to user authorization checks based on characteristics....

14.        4.      Assign Calculated Key Figures

InfoObjects are usually used for the communication of the data for characteristics and key figures between individual Analyzers and the Source Data Layer.

However, there are no Info Objects for calculated key figures. This means that you have to assign each calculated key figure to a key figure in the environment catalog (SDL).

To do so, in Customizing for Bank Analyzer choose Analytics  Profit Analyzer  Profitability Management  Special Key Figures  Assign Calculated Key Figures.

15.        5.      Assign Special Aggregation

Special logic (average calculation, last value) is assigned to the key figures. This involves enhancing the logic that is already available in BÍ. You can use this logic for primary or secondary data sources of the “Profit Analyzer” category.

Example:

The system contains an entry for the months January to March. No income was obtained for the months April to November in this area. You want to calculate the average for the calendar year at the start of December, including November. The total income is divided by 11, using the “AVG” aggregation category.

“LAS” delivers the last value. In this example, the last value is not the last posted value (revenue from March). The last value is the value for November, which is zero.

In Customizing for Bank Analyzer choose Analytics  Profit Analyzer  Profitability Management  Special Key Figures  Assign Special Aggregation.

 

 Profit Engine (FS-BA-PA-PE) PurposeYou use this component to calculate bank-specific costs and revenue, in particular the revenue components of the asset, liability, and service transactions in banks, as well as the standard unit costs incurred at different levels.

The results components of the costed transactions can be neutralized at different hierarchy levels or distributed to various items. This enables a previously costed bonus or premium that was allocated to one customer service representative to be removed (neutralized) at overall bank level, for example. If a results component is distributed, a revenue component is assigned to two customer service representatives in a particular ratio, for example.

The results data records are forwarded to Profitability Analysis, where line items are generated from the data records and consolidated in a user-definedcontribution margin scheme.

FeaturesThe Profit Engine component is divided into the following subcomponents:...

16.       1.      Processing framework17.       2.      Modular costing18.       3.      Allocation19.       4.      Value determination20.       5.      Derivation21.       6.      Verification lists

Processing framework

The processing framework reads data from a data source and provides it for costing or allocation purposes. The data records generated are transferred to Profitability Analysis for the purpose of line item generation. The data records can also be transferred to a file or table. Status management for the costing or allocation processes is carried out within the processing framework.

Modular costing

Modular costing generates new costing components by carrying out various valuation and retrieval functions. Modular costing consists of elementary functions that can be combined for particular processes.

Value determination

In modular costing, it must be possible to derive currency amounts, percentages, or quantities on the basis of characteristics:

       The values are determined depending on any combination of characteristic values.

       These currency amounts, percentages, and quantities are determined using a multi-step access logic. The system first searches for a particular customer group and product combination, for example, a percentage. If this is not available, the system searches for a valid percentage first at product group level and then at organizational area level.

The value determination tool determines the above values for modular costing.

Allocations

Allocations are:

       The distribution of profitability values

       The neutralization of imputed results figures at aggregated level

Distribution:Distribution is a transfer of profitability values (in particular costs or revenues) from one or more senders to one or more receivers.Neutralization:Costing results are determined in both real (for example, actual costs) and imputed results figures (for example, bonus/premium, standard unit costs). These imputed results figures are identified on lower levels (single transaction, for example) but have to be taken out of the figures at higher levels (overall bank, for example) so that the overall bank result is correct.

New data records are generated during the allocation process.

Derivation

In the derivation tool, additional, logically dependent characteristics are determined on the basis of particular characteristics. The derivation can be carried out in several steps.

 

The characteristic branch is determined on the basis of the characteristic branch office and the characteristic business area is then determined on the basis of the branch.

Verification lists

You can display the results of modular costing and of the allocations in verification lists before the data records are updated in Profitability Analysis. In Profitability Analysis, the data records that have been processed without errors can be checked for business accuracy. To enable comparisons to be made between the result records and the results from previous periods, the data records can be extracted from the verification lists to the Business Information Warehouse (BW).

 

 

 Profitability Planning PurposeProfitability Planning in Profit Analyzer supports the overall process of sales planning of instrumental reporting for financial institutions. User-defined key figures are planned. They are classified by user-defined characteristics.

In order to carry out operative sales planning, Profit Analyzer uses the SAP SEM-BPS (Business Planning and Simulation) application. This application is shipped separately and is not integrated in Profit Analyzer. For more information, see the documentation on the SEM-BPS application.

IntegrationSales planning is based on actual values, from which plan values are generated during the planning process, as well as data that is loaded from Profitability Analysis or non-SAP systems, for example.

Data from the individual systems is merged within planning using SAP NetWeaver Business Intelligence (BI), which BPS uses for data storage purposes. Note that the granularity level at which planning is to be carried out can be generated when data is extracted to BI by means of simply aggregating the actual data records. If several Cubes are to be merged, all characteristics must be identical and filled.

Sales planning is carried out at branch office level and profitability analysis data is available at account level. The data records in Profitability Analysis also contain the branch office characteristic, which enables the single records to be aggregated at account level.

 

 

 Counterparty Risk DefinitionThe risk of an unexpected loss in the value of a receivable in a contract due to a worsening of the credit standing of a business partner.

UseCounterparty Risk identifies risks and provides key figures to measure and control credit risk as part of the bank management process.

StructureCounterparty risk is calculated as follows:...

22.        1.      The input data is selected that is needed to calculate the counterparty/issuer risk (see Selection Management in the Source Data Layer). The main types of input data are:

         Business partner data

         Contract data

         Collateral data

23.        2.      Counterparty risk is calculated at business partner level, or for a group of business partners and their contracts. It is calculated as follows:

The balances of contracts are netted off against one another on the basis of legal or economic aspects (see Account Pooling).Business partner data is aggregated on the basis of legal or economic aspects, or as required for specific models, or for system performance reasons (see Summarization Schema).Summarized business partner data is transferred to a credit risk model (such as CreditMetrics, or CreditRisk+), which returns the calculated risk key figures (see Interface to Portfolio Models).

a.       Risk key figures are saved along with their characteristics, and made available to other business applications and processes.

Since risk key figures cannot usually be returned at contract level, some business processes have to redistribute the key figures back to the individual contracts (see Redistribution).

 

 

IntegrationCounterparty risk, or credit risk, is by far the greatest risk borne by banks. It is a risk they have borne since their conception. Yet new developments on the capital market and advanced methods for measuring and controlling credit risks present banks with new requirements in terms of business processes and technical systems for assessing credit risk. These requirements are increased by prospective changes to the banking supervisory regulations aimed at limiting bank’s default risk. Bank Analyzer aims to provide suitable solutions to meet the changing requirements of banks for processes and methods to measure and manage counterparty risk.

 

 

 Portfolio Credit Risk PurposeThis component enables you to measure, analyze, and control default risks. Default risk is the potential loss incurred from a financial transaction in the event of the business partner being unable to meet contractual obligations due to specific economic or political causes. Default risks are classified as follows:

Counterparty risk describes the danger of a loss in the value of a receivable due to a worsening of the creditworthiness of the business partner. Country

risk describes the risk of a loss in value due to a worsening of the credit standing of the country risk country. This is the country whose situation affects the business payments.

Portfolio Credit Risk contains functions for counterparty risk only.

 

 Counterparty Risk DefinitionThe risk of an unexpected loss in the value of a receivable in a contract due to a worsening of the credit standing of a business partner.

UseCounterparty Risk identifies risks and provides key figures to measure and control credit risk as part of the bank management process.

StructureCounterparty risk is calculated as follows:...

24.        1.      The input data is selected that is needed to calculate the counterparty/issuer risk (see Selection Management in the Source Data Layer). The main types of input data are:

         Business partner data

         Contract data

         Collateral data

25.        2.      Counterparty risk is calculated at business partner level, or for a group of business partners and their contracts. It is calculated as follows:

The balances of contracts are netted off against one another on the basis of legal or economic aspects (see Account Pooling).Business partner data is aggregated on the basis of legal or economic aspects, or as required for specific models, or for system performance reasons (see Summarization Schema).Summarized business partner data is transferred to a credit risk model (such as CreditMetrics, or CreditRisk+), which returns the calculated risk key figures (see Interface to Portfolio Models).

a.       Risk key figures are saved along with their characteristics, and made available to other business applications and processes.

Since risk key figures cannot usually be returned at contract level, some business processes have to redistribute the key figures back to the individual contracts (see Redistribution).

 

 

IntegrationCounterparty risk, or credit risk, is by far the greatest risk borne by banks. It is a risk they have borne since their conception. Yet new developments on the capital market and advanced methods for measuring and controlling credit risks present banks with new requirements in terms of business processes and technical systems for assessing credit

risk. These requirements are increased by prospective changes to the banking supervisory regulations aimed at limiting bank’s default risk. Bank Analyzer aims to provide suitable solutions to meet the changing requirements of banks for processes and methods to measure and manage counterparty risk.

 

 

 Risk Calculation Counterparty credit risks can be calculated externally (see also External Calculation of Risk  or internally (see also Internal Calculation of Risk Calculation). When risks are calculated externally, the basic data is selected from the Source Data Layer (SDL) and transferred to an external counterparty risk processor, where the risk is then calculated. The data is transferred to the administration of counterparty/issuer risk runs, and then to the Result Database (RDB). At present, the interface for external risk calculation is provided only for external counterparty/issuer risk processors of the pilot customer.

Internal risk calculation takes place almost exclusively within the SAP system. If required, certain counterparty/issuer risk key figures can be calculated in an external portfolio model. However, internal risk calculation can currently be used as a prototype function only.

 

 

 Country Risk  PurposeThis component provides an infrastructure for calculations and can be defined by the customer as required. Calculations are primarily used to determine attributable amounts for individual transactions.

 

IntegrationCountry Risk is part of Bank Analyzer. In Country Risk, you can use the results generated by the upstream General Calculation and Valuation Methods. You can process the attributable amounts calculated in Country Risk in Limit Manager.

For more information, see the following documents:

Architecture of Country Risk

Interaction Between Country Risk and Limit Manager

 

FeaturesSince in practice a large number of methods are used to determine the exposure to default risk, a flexible and customizable interface is provided in Country Risk for the analysis of financial transactions such as loans and facilities. For each transaction entered in the system, the system calculates attributable amounts that disclose the risk content of each transaction. Formulas are assigned for each combination of determination procedure and default risk rule defined in Customizing. The formulas are stored in each transaction.

 

 

RETAIL BANKING

Retail banks provide basic banking services to the general public, including:

Checking and savings accounts CDs Safe deposit boxes Mortgages and second mortgages Auto loans Unsecured and revolving loans such as credit cards

The significance is that retail bank deals with customers directly.

The real time effectiveness makes the scenario is more current which in turn makes the customers and the employees happy.

Labour cost is at its all time high and speculation read that they will keep increasing over the coming years.

Banks with well defined systems and procedures would emerge as leaders in Retail Credit.

Using the right financial technology is paramount in transforming the customer experience. The results speak for themselves. Customer centric technology solutions ensure higher customer acceptance than traditional direct marketing practices – generating an excess of 40% positive responses to offers (as opposed to 1%)!

Definition

Retail banks offer a range of services to individual customers and small businesses, rather than to large companies and other banks. The services can include current accounts, savings accounts, investment advice and broking, and loans and mortgages. Retail banks perform two crucial

functions for customers: firstly, they enable customers to bank their money securely, access it easily, and conduct transactions; and secondly, they provide access to additional money to fund large purchases, such as buying a home. In return for holding customers’ funds, which they can then invest, banks pay customers interest.

Traditionally, retail banks have provided these services directly to the customer via branches. While many still do this, retail banks now offer their services by telephone and the internet as well. Some operate solely via the internet and do not have facilities to serve customers at physical outlets. Other organizations, such as supermarkets, have now entered the banking sector and also offer a wide range of banking services.

It has become more difficult to identify the traditional retail bank—a bank that funds itself through customer deposits and lending—because retail banks now often combine retail and wholesale banking. It is therefore more relevant to today’s banking structure to regard retail banking as a series of processes rather than as an institution.

The intermediation services offered by retail banks (such as looking after customers’ money and making loans) and the payment services (allowing customers to make transactions using debit cards, checks, etc.) mean that they have to make funds available to customers at very short or immediate notice. This inevitably means that a retail bank has to manage the risk that more money will be requested by customers than it has available and of customers defaulting on loans. Banks do this by holding stocks of liquid assets, maintaining a cushion of capital, lending to different types of borrower, adjusting interest rates, and screening potential borrowers (credit scoring).

Evolution of the Indian Banking Industry:

The Indian banking industry has its foundations in the 18th century, and has had a varied evolutionary experience since then. The initial banks in India were primarily traders’ banks engaged only in financing activities. Banking industry in the pre-independence era developed with the Presidency Banks, which were transformed into the Imperial Bank of India and subsequently into the State Bank of India. The initial days of the industry saw a majority private ownership and a highly volatile work environment. Major strides towards public ownership and accountability were made with nationalization in 1969 and 1980 which transformed the face of banking in India. The industry in recent times has recognized the importance of private and foreign players in a competitive scenario and has moved towards greater liberalization.

Fund management

Payments and payment systems are important to banks because they are the ‘life blood’ of the customer relationship. Transfers of value are the principal reason customers have banking relationships. Too often this basic need is overlooked by both the bank and the customer. In some markets, payments may be priced as a loss leader,

underpinning a customer relationship which allows cross-selling of other products and services. Payments also provide a stable revenue base for banks. When so many other sources of revenue are uncertain or reducing, banks are welcoming the continued flow of income from payments.

This report offers an overview of current issues and trends in payments, ranging from efficiencies in payment systems to new technology, systemic risk and evolving business models. One of the key features to emerge is that there has been a reversal of priorities for payments businesses over the last year. Only a year ago payments were seen as unexciting and low-margin.

Financial regulators paid little attention to payments. Governments were driving forward a social agenda, fighting banks to reduce prices and introduce new, universal-service products. Banks were focusing on innovation and exploring new partnerships with non-banks to enable them to reach new customer segments and achieve a higher share of customers’ spending.

Key areas of concern:

Funds transfer pricing Multiple rate scenarios Roll/on and roll/off balance sheets Product, customer and line of business profitability Branch profitability Determining RAROC Driver based cost allocations Compliance reporting Risk management

Checklist Description

This checklist describes the structure and function of retail banks, what services they provide, and the factors to be considered when selecting one. In the United Kingdom retail banks are also known as high street banks.

Current Structure

Currently the Indian banking industry has a diverse structure. The present structure of the Indian banking industry has been analyzed on the basis of its organized status, business as well as product segmentation.

Organizational Structure

The entire organized banking system comprises of scheduled and non-scheduled banks. Largely, this segment comprises of the scheduled banks, with the unscheduled ones forming a very small component. Banking needs of the financially excluded population is catered to by other unorganized entities distinct from banks, such as, moneylenders, pawnbrokers and indigenous bankers.

Business Segmentation

The entire range of banking operations are segmented into four broad heads- retail banking businesses, wholesale banking businesses, treasury operations and other banking activities. Banks have dedicated business units and branches for retail banking, wholesale banking (divided again into large corporate, mid corporate) etc.

Retail banking includes exposures to individuals or small businesses. Retail banking activities are identified based on four criteria of orientation, granularity, product criterion and low value of individual exposures. In essence, these qualifiers imply that retail exposures should be to individuals or small businesses (whose annual turnover is limited to Rs. 0.50 billion) and could take any form of credit like cash credit, overdrafts etc. Retail banking exposures to one entity is limited to the extent of 0.2% of the total retail portfolio of the bank or the absolute limit of Rs. 50 million. Retail banking products on the liability side includes all types of deposit accounts and mortgages and loans (personal, housing, educational etc) on the assets side of banks. It also includes other ancillary products and services like credit cards, demat accounts etc.

Other Banking Businesses

This is considered as a residual category which includes all those businesses of banks that do not fall under any of the aforesaid categories. This category includes para banking activities like hire purchase activities, leasing business, merchant banking, factoring activities etc.

Products of the Banking Industry

The products of the banking industry broadly include deposit products, credit products and customized banking services. Most banks offer the same kind of products with minor variations. The basic differentiation is attained through quality of service and the delivery channels that are adopted. Apart from the generic products like deposits (demand deposits – current, savings and term deposits), loans and advances (short term and long term loans) and services, there have been innovations in terms and products such as the flexible term deposit, convertible savings deposit (wherein idle cash in savings account can be transferred to a fixed deposit), etc. Innovations have been increasingly directed towards the delivery channels used, with the focus shifting towards ATM transactions, phone and internet banking. Product differentiating services have been attached to most products, such as debit/ATM cards, credit cards, nomination and demat services.

Other banking products include fee-based services that provide non-interest income to the banks. Corporate fee-based services offered by banks include treasury products; cash management services; letter of credit and bank guarantee; bill discounting; factoring and forfeiting services; foreign exchange services; merchant banking; leasing; credit rating; underwriting and custodial services. Retail fee-based services include remittances and payment facilities, wealth management, trading facilities and other value added services.

Advantages

Your money is much more secure than in a box under your bed and you can buy goods, be paid, and sell things without cash changing hands.

The bank you are familiar with and which knows you can also offer you a wide range of other services, such as mortgages and insurance. Your bank may be able to offer you competitive deals in return for your loyalty as a customer.

Retail banks offer a variety of ways you can access your account and manage your money, most notably via internet banking. This means that you can keep a close eye on your finances and avert many potential problems.

Disadvantages

Banks are a business, and they need to make money from looking after yours. If the bank decides to apply charges to your account (within the terms of the account), you may only find out about it afterwards—for example if you accidentally go overdrawn without permission. If you disagree with a charge, you will need to contest it to recover the money.

Action Checklist

Think carefully about what you want from a bank account and what is important to you. For example, if you are not concerned about having face-to-face contact with your bank, an internet-only bank may suit you.

When choosing an account, check the interest rate offered and how quickly and by what methods you can access your money.

When looking for a current or checking account, find out what extra services the bank can offer you, such as a debit card, overdraft facility, free or cheap insurance policies, etc.

Does the bank have local branches, or is it internet only? Are you comfortable with the ways in which you can communicate with the bank?

Most importantly, find out what charges apply to various transactions and events, such as going overdrawn without the bank’s approval.

Dos and Don’ts

Do

Compare different banks and their products and services.

Look for added value, such as free insurance.

Challenge charges you feel are unfair or wrongly applied to your account.

Regularly review your savings accounts to make sure you continue to get the best interest rates available.

Don’t

Don’t let financial problems get out of control, and don’t put off talking to your bank about them if they do.

Don’t be afraid to move to a new bank if you are not happy with your current one and if, via sound research, you have found something better. The bank you want to move to will be happy to take on the transfer arrangements for you.

 

Features

Collateral Management covers a comprehensive list of functions required for collateral administration, maintenance and monitoring. Some of these features include:

 

●     Centralized Master Data Maintenance

You can maintain detailed descriptions for collateral entities that can be used for executing collateral processes in Collateral Management. The master data is also available for reporting in external reporting systems.

 ●     Collateral Terms

The collateral terms represent the terms and conditions for collateralizing receivables using collateral agreements. The declaration of purpose is a special feature that can be used to determine the scope of collateralization.

 ●     Collateral Calculations

You can determine a range of coverage values for receivables assigned to collateral agreements. The standard system considers the business requirements of collateral entities for performing a range of intermediary calculations for each of them.

 ●     Collateral Processes

You can execute processes relevant for collaterals such as liquidation of collateral objects or determining the value of charges on collateral objects. It is also possible to extract collateral data for use in analysis and reporting in external systems. The standard system provides the framework for extraction and uploading of collateral data to SAP Netweaver Business Intelligence and SAP Bank Analyzer (for use in Basel II-specific reporting).

 ●     Configuration Framework for Collateral Processes

The process control framework allows you to define controls and use these controls to define processes. You define processes using business activities. Basic controls include managing statuses, configuring user interface specific to the business of collateral entities and additional business checks for processes. Other controls include the authorization and change management features.

 ●     Collateral Monitoring

The collateral monitoring reports such as the collateral overview, collateral sheet and the report for batch collateral coverage monitoring (BCM) have been provided for administration and monitoring of collaterals. You can also display an overview of the status of collaterals for a specific business partner using the Overview of Business Partner Collaterals.

 ●     Correspondence for Business Partners

You can send outbound correspondences to the business partners using the correspondence function.

 ●     Navigation Workbench

Easy navigation in the Collateral Management workbench between collateral entities. You can maintain all the collateral entities using the workbench. You can also run the business partner collateral overview report from the workbench. Further you can search for collateral entities, create new entities and copy entities using the workbench. Organizational settings must be defined in the workbench for a user.

POST DATED CHEQUE

Postdated check is a check delivered now with a written date in the future, so that it cannot be cashed until that date. The danger to the recipient is that such a check is legally only a promissory note due at the later date, and if the account is closed or short when the check is presented at the bank, the payee has no rights to demand payment by the bank or claim that the delivery of a bad check was criminal.

PDC forms a major mode of repayment of installments of any loan/ mortgage payments in India, where end customer prefers to issue cheques for the installment amounts payable on future due dates. These instruments require being stored in a safe and effective manner given that it is a negotiable instrument and forms part of receivables.

On one hand, the companies and banks find it hard to keep track of the ever increasing volumes of cheques being received from customers and on the other coping with the pressure of

meeting sales targets and keeping competition down. Invariably, Organizations start losing control over efficient back office management. The primary concern being efficient tracking, secure storage, accurate retrieval and timely presentation of these cheques. Post Dated Cheque management is a serious problem for both Banks & NBFC’s (Non-Banking Financial Corporations).

Today, PDC and Document management has grown to be a high transaction volume business. A lost cheque, late cheque presentations, customer dissatisfaction, loss of revenue. These are the worst nightmare of any bank & financial institution dealing with disbursement of loans, typically companies dealing in retail loans.

This is where the important of proper post dated cheque management systems come in to picture. Post dated cheque management enable fast turnaround time on foreclosure recovery by improving process efficiency by managing dishonored cheques and repeat entries. It was logical that the banks had to manage a huge number of PDCs towards repayment of loans and had to manage varied types of documents in relation to loans/ credit cards/ mortgages. In this scenario, we have to maintain a efficient procedure to manage the PDCs in a professional manner thereby enabling the banks to focus on their core business processes so as to emerge successful in this competitive environment. We have to solve the issues coming in the check transfers, which is taking place in the daily banking scenario.

FEATURES OF POST DATED CHEQUE MANAGEMENT

Cheque Received Entry

Maintains received cheque details such as cheque receive date, present date, amount, bank and customer together with relevant invoice no’s.

Cheque Present Entry

When a date is entered all unpresented cheques are shown and the user can tick opposite the cheque number to deposit it in a specific bank.

Cheque Realized Entry

When date of the realized cheque is entered into the system, the cheque will be automatically realized.

Cheque Dishonored Entry

When dishonored data is entered for a cheque that is not realized, it automatically reverses the debtor balance and the relevant invoices.

Cheque re-deposit Entry

When a cheque is dishonored due to some reason and can be deposited again this transaction is entered.

After a cheque is realized it cannot be dishonored. After realizing, the debtor's statement shows the invoice amount with the allocation.

Before the cheque is realized the user can dishonor the cheque. All dishonored cheques are shown in the debtor's statement. Once a cheque is dishonored the invoice balance is automatically reversed.

Only dishonored cheques can be re-deposited. When re-depositing, one cheque can be allocated to many invoices.

Facility to obtain age analysis of unrealized cheques (according to user defined aging periods).

One cheque number can be allocated to multiple invoices. However a cheque no. for one customer bank cannot be repeated.

Daily “to be banked cheques" listing facility. Cheque purchasing facility. Cheque presenting dates amendment facility. Realized cheques are monitored daily.

Allocates cheque advance payments against invoices or debit notes.

This all are the issues which we have to solve in an efficient and effective way while implementing it in banks or any other Non-banking institutions. In sap we can make it simpler and time saving rather than any other software tools which is available in the market.