Status
Owner	Prasad Naidu
Stakeholders	The business stakeholders involved in making, reviewing, and endorsing this decision. Type @ to mention people by name

Purpose

The purpose of this document is to define the approach, scope, and rules for the conversion of Bank Master Data from legacy systems into SAP S/4HANA. The Bank Master includes information about House Banks and Bank Directory (External Banks) required for processing payment transactions such as vendor payments, customer refunds, and bank reconciliations.

This conversion ensures that all bank-related master data is available and consistent in the S/4HANA system to support business-critical financial operations post go-live. The data migration encompasses both:

·        External Banks (from tables like BNKA): Used for storing details of banks globally (e.g., SWIFT, bank address, bank key).

·        House Banks: Internal company banks used for executing payments and receiving cash (e.g., bank account number, account ID, GL account linkage).

The migration process includes the cleansing, transformation, mapping, and loading of this data in alignment with SAP's Business Partner and Financial Supply Chain Management framework, while adhering to data quality and audit requirements.

Conversion Scope

The scope of this conversion covers the migration of all relevant Bank Master Data from the legacy SAP ECC system to the SAP S/4HANA system. This includes both External Bank Directory data and House Bank configurations, ensuring continuity in banking operations such as payments, collections, and bank reconciliations.

The data from legacy system includes:

1. Bank Key
2. Bank Country
3. Bank Name
4. Bank Address
5. SWIFT/BIC Code
6. Bank Number / Routing Code

The data from legacy system excludes:

1. Bank configuration for treasury or cash management tools not in active use
2. Bank Communication Management (BCM) configurations unless separately scoped

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2	Bank Master
WP2	Bank Master
PI2	Bank Master

Additional Information

Multi-language Requirement

Summarize Multi-language Requirement/s, if any

Document Management

Summarize Document Management requirement, if any

Legal Requirement

Summarize Legal Requirement/s, if any

Special Requirements

Specify any special requirements or considerations that may impact the data conversion process based on specific locations, regulatory compliance or system limitations. Clearly outline any regional or localization requirements such as country-specific data formats, legal reporting obligations or industry standards that must be adhered to (e.g., localization rules for countries like China).

If the data conversion involves third-party systems or external data sources, such as Icertis, describe any additional requirements related to data mapping, transformation logic, validation rules or security measures that must be followed.

Target Design

With Functional input, document the technical design of the target fields that are in the scope of this document.

The technical design of the target for this conversion approach.

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
BNKA	BANKS	BANKS	Bank Country Key	CHAR	3	Required
BNKA	BANKL	BANKL	Bank Key	CHAR	15	Required
BNKA	BANKA	BANKA	Bank Name	CHAR	60	Optional
BNKA	BANKN	BANKN	Bank Account Number	CHAR	35	Optional
BNKA	BANKL_OLD	BANKL_OLD	Old Bank Key	CHAR	15	Optional
BNKA	BRNCH	BRNCH	Branch Number	CHAR	15	Optional
BNKA	SWIFT	SWIFT	SWIFT Code	CHAR	11	Optional
BNKA	CITY	ORT01	Bank City	CHAR	35	Optional
BNKA	STREET	STRAS	Street	CHAR	60	Optional
BNKA	COUNTRY	LAND1	Country	CHAR	3	Optional
BNKA	REGIO	REGIO	Region (State, Province, County)	CHAR	3	Optional
BNKA	BANKT	BANKT	Bank Type	CHAR	1	Optional
BNKA	MCOD1	MCOD1	Search Term	CHAR	25	Optional
BNKA	DATLZ	DATLZ	Date of Last Change	DATS	8	Optional
BNKA	TIMEZ	TIMEZ	Time of Last Change	TIMS	6	Optional

Data Cleansing

All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.

If data cleansing is managed outside of the source system (e.g. Syniti Migrate, 3rd Party Vendor, DCT), the necessary documentation must be produced and appended to this deliverable for sign-off.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
1	High	Bank key not unique within country	BANKS + BANKL must be unique	Flag as duplicate; reject or merge records	PF2,WP2,PI2
2	High	Missing or invalid SWIFT/BIC code	SWIFT field must be 8 or 11 alphanumeric characters	Flag and request update from valid bank directory	PF2,WP2,PI2
3	Medium	Bank name contains special characters or inconsistent casing	BANKA field should follow naming conventions and avoid special characters	Normalize or correct bank name formatting	PF2,WP2,PI2
4	High	Obsolete bank record not linked to any business partner	Check if BANKL is not referenced in any related table (e.g., LFBK, KNBK)	Mark for archival or deletion after verification	PF2,WP2,PI2
7	High	Duplicate bank key entries detected	BANKL must be unique per BANKS; fuzzy match for duplicates	Flag duplicates; consolidate or clean up	PF2,WP2,PI2
10	High	Bank key format invalid per country-specific rules	BANKL format must match country-specific structure rules (e.g., DE = 8 digits)	Flag and correct according to rulebook or SAP note	PF2,WP2,PI11

Conversion Process

The high-level process is represented by the diagram below:

Data Privacy and Sensitivity

Summarize Data Privacy and Sensitivity Requirements, if any

Extraction

Extract data from a source into Syniti Migrate. There are 2 possibilities:

1. The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
   1. Perform full data extraction from relevant tables in the source system(s).
   2. Perform extraction through the application layer.
   3. Only if Syniti Migrate; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
2. The data does not exist (or cannot be converted from its current state). The data is manually collected by the business directly in Syniti Migrate. This is to be conducted using DCT (Data Collection Template) in Syniti Migrate

The agreed Relevancy criteria is applied to the extracted records to identify the records that are applicable for the Target loads

Extraction Run Sheet

Req #	Requirement Description	Team Responsible

Selection Screen

If applicable, this section will give the details on any selection screen parameters, including the parameter type, that are required to be entered to ensure consistent data extracts.

Selection Ref Screen	Parameter Name	Selection Type	Requirement	Value to be entered/set

Data Collection Template (DCT)

Target Ready Data Collection Template will be created for Data Object data with exception of some fields which require transformation as mentioned in the transformation rule.

<Object> DCT Rules

Field Name	Field Description	Rule

Extraction Dependencies

List the steps that need to occur before extraction can commence

Item #	Step Description	Team Responsible

Transformation

The Target fields are mapped to the applicable Legacy field that will be its source, this is a 3-way activity involving the Business, Functional team and Data team. This identifies the transformation activity required to allow Syniti Migrate to make the data Target ready:

1. Perform value mapping and data transformation rules.
   1. Legacy values are mapped to the to-be values (this could include a default value)
   2. Values are transformed according to the rules defined in Syniti Migrate
2. Prepare target-ready data in the structure and format that is required for loading via prescribed Load Tool. This step also produces the load data ready for business to perform Pre-load Data Validation

Transformation Run Sheet

Item #	Step Description	Team Responsible

Transformation Rules

Rule#	Source  System	Source Table	Source Field	Source Description	Target System	Target Table	Target Field	Target Description	Transformation Logic
1	ECC	BNKA	BANKS	Bank Country Key	S/4 HANA	BNKA	BANKS	Bank Country Key	Copy as-is
2	ECC	BNKA	BANKL	Bank Key	S/4 HANA	BNKA	BANKL	Bank Key	Copy as-is
3	ECC	BNKA	BANKA	Bank Name	S/4 HANA	BNKA	BANKA	Bank Name	Copy as-is
4	ECC	BNKA	BANKN	Bank Account Number	S/4 HANA	BNKA	BANKN	Bank Account Number	Copy as-is
5	ECC	BNKA	BANKL_OLD	Old Bank Key	S/4 HANA	BNKA	BANKL_OLD	Old Bank Key	Copy as-is
6	ECC	BNKA	BRNCH	Branch Number	S/4 HANA	BNKA	BRNCH	Branch Number	Copy as-is
7	ECC	BNKA	SWIFT	SWIFT Code	S/4 HANA	BNKA	SWIFT	SWIFT Code	Copy as-is
8	ECC	BNKA	CITY	Bank City	S/4 HANA	BNKA	CITY	Bank City	Copy as-is
9	ECC	BNKA	STREET	Street	S/4 HANA	BNKA	STREET	Street	Copy as-is
10	ECC	BNKA	COUNTRY	Country	S/4 HANA	BNKA	COUNTRY	Country	Copy as-is
11	ECC	BNKA	REGIO	Region (State, Province, County)	S/4 HANA	BNKA	REGIO	Region (State, Province, County)	Copy as-is
12	ECC	BNKA	BANKT	Bank Type	S/4 HANA	BNKA	BANKT	Bank Type	Copy as-is
13	ECC	BNKA	MCOD1	Search Term	S/4 HANA	BNKA	MCOD1	Search Term	Copy as-is
14	ECC	BNKA	DATLZ	Date of Last Change	S/4 HANA	BNKA	DATLZ	Date of Last Change	Copy as-is
15	ECC	BNKA	TIMEZ	Time of Last Change	S/4 HANA	BNKA	TIMEZ	Time of Last Change	Copy as-is

Transformation Mapping

Use the exact name and reference this section in the “Transformation rules” above

Mapping Table Name	Mapping Table Description

Transformation Dependencies

List the steps that need to occur before transformation can commence

Item #	Step Description	Team Responsible

Pre-Load Validation

Project Team

The following pre-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following pre-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Load

The load process includes:

1. Execute the automated data load into target system using load tool or product the load file if the load must be done manually
2. Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation

Load Run Sheet

Item #	Step Description	Team Responsible

Load Phase and Dependencies

Identify the phase as to “when” the load for this object will occur. <Pre-Cutover, Cutover, Post Cutover> and list the steps that need to occur before the load can commence

Configuration

List the Configurations required before loading can commence

Item #	Configuration Item

Conversion Objects

Object #	Preceding Object Conversion Approach
	list the exact title of the conversion object of only the immediate predecessor – this will then confirm the DDD (Data Dependency Diagram)

Error Handling

The table below depicts some possible system errors for this data object during data load. All data load error is to be logged as defect and managed within the Defect Management

Error Type	Error Description	Action Taken

Post-Load Validation

Project Team

The following post-load validations will be performed by the Project Team.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Business

The following post-load validations will be performed by the business.

Completeness

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Accuracy

Task	Action
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Data Object is in scope based on data design and any exception requested by business.

Any additional key assumptions.

See also

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log

Workflow history