The Smart Splitter can help you to reduce the size of large grouped transactions, which is useful when your data contains transactions comprised of a large number of related entries. These transactions can limit MindBridge's ability to accurately assess and score risk at a transactional level because unrelated entries are being grouped together.
Learn more about which control points trigger at a transactional level in our Knowledge Base.
The Smart Splitter identifies double-entry transactions within large batched transactions by looking at commonalities in the defined transaction ID column data in addition to matching debit and credit amounts. Each double-entry transaction identified is extracted from the large batched transaction and assigned a new unique transaction ID, as illustrated below.
Note: if you are familiar with the data and expect to see some large transactions using the smart splitter can compromise the integrity of the data. There is a risk of unrelated entries being matched to create new transactions if there are repeated debit, credit, and transaction ID column data values throughout a large batch transaction.
Any remaining entries left unmatched within the large batched transaction are grouped together to form a separate transaction with a unique Transaction ID assigned to it.
How To Use
The Smart Splitter can be used during the Review Data stage of the data ingestion process.
Use the Select transaction identifier drop-down menu to select the transaction ID to split. MindBridge will recommend a transaction ID based on your data, but you can select your own combination if desired.
When satisfied, run the Smart Splitter using the Yes, run Smart Splitter button.
The graph on the right container will update to reflect the changes made with the Smart Splitter.
Custom running total
The data may lack a unique transaction ID to link account entries, but restructuring the data may help recognize transactions by the order in which entries are recorded.
A custom running total involves sorting the data in the order that would place like-entries next to each other. For example, successive reference numbers may have been assigned to every new entry recorded in the general ledger, with related entries being recorded sequentially.
When a custom running total by reference number is applied as a transaction ID, the data will be sorted by increasing reference number. MindBridge will calculate the running total on the sorted entry amounts and assign unique transaction IDs to groups of entries that sum to zero, as illustrated below.
To select a custom running total transaction ID, use the Select transaction identifier drop-down menu. You can then select the columns you wish you sort your data on.
If the custom running total on the selected data columns is a suitable transaction ID, you will see improvements in your transaction graph, and more of your data integrity checks will pass.
Learn more about the transaction graph and data integrity checks in our Knowledge Base.