Bank Analyzer (FS-BA) 

 
Purpose
Bank 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)  

Purpose
This 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.

Integration
The following graphic shows the components that are part of the ETL process:
 ...

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.

Features
The 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)  

Purpose
You 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

Integration
The 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)  

Purpose
You 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)  

Purpose
You 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)  
Purpose
This 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.

Features
Components 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:

...
...

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.

Integration
The 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.

Features
Bank 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) 

Purpose
To 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.

Integration
Limit 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.

Features
You 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 

Integration
Strategy 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 Flows
Strategy 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.

Dependencies
Not 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 

Purpose
To 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 Flow
Depending 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 

Purpose
To 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 Flow
Depending 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 
Purpose
Gap 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
 

Example
An 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.
 

Prerequisites
Settings 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 Flow
Depending 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  
Definition
Run 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.

Use
The 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 Fair Value Effectiveness Test Run
Hedging Relationships

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 Engine
6.        2.      Profitability Analysis
7.        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  
Definition
Business 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

Use
Set 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.      Realignment
To 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) 

Purpose
You 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.

Features
The Profit Engine component is divided into the following subcomponents:
...

16.       1.      Processing framework

17.       2.      Modular costing
18.       3.      Allocation
19.       4.      Value determination
20.       5.      Derivation
21.       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 
Purpose
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 (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.

Integration
Sales 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 
Definition
The 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.

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

Structure
Counterparty 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).
 

Integration
Counterparty 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 

Purpose
This 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 
Definition
The 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.

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

Structure
Counterparty 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).
 

Integration
Counterparty 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  
Purpose
This 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.
 

Integration
Country 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
 

Features
Since 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.