KOR provides an intuitive, no-code solution to normalize and map attributes to our KOR Data Model (KDM), ensuring rigour in reporting to regulators.
First, you will create a new rule in the Configurations tab.
In this guide, we will go through common mapping rules on KOR and provide best practices on how users can easily create as well as edit their own mapping, transformation, and normalization rules.
We will run through different examples using source data in nested XML/JSON formats as well as flat files such as CSV to show how extracting values from different formats work.
Simple Straight-through Mapping of a Source Field to KDM
In this example, we will map a field from a JSON source file to a KOR Data Model field called “executionTimestamp”.
Default Value Mapping to KDM
In this example, we will automatically populate the KOR Data Model field called “customBasketIndicator” with the value “False”. Any static value can be mapped using Default Value Mapping.
Concatenation of Multiple Source Fields to Map to KDM
In this example, we will map and concatenate two fields from a CSV source file to a KOR Data Model field called “clientMessageIdentifier”. Namely, we shall combine a field called “Msg ID” with a field called “Action Code”. Note that KOR provides a flexible solution for creating as well as editing mapping configurations and so there may be different ways to achieve the same result in KOR.
Extraction of Date from Source Field for Mapping to KDM
In this example, we will extract a custom date and timestamp format within the “Trd DateTime” header in a submitted CSV file and convert the values into a date in the required reporting yyyy-MM-dd format for the “effectiveDate” KDM field.
Transformation of Field Content Using Mapping Tables for each Regulatory Regime (CFTC & EMIR)
In this example, we will map Asset Class information from a JSON file and convert the content from this field into acceptable values for regulatory reporting under CFTC and EMIR using a mapping table or reference data tables.