Questions? We have answers.

Find and apply a client's transaction ID

  • Updated

Summary

MindBridge relies on transaction IDs to accurately score monetary flows for risk. 

If a transaction ID column does not exist in the dataset, learn how to identify which of your clients' columns best reflect the transaction ID, and how to apply them to MindBridge general ledger analyses.


How do I know what my client uses for their transaction ID?

The transaction ID will vary depending on the accounting system and bookkeeping procedures. In double-entry accounting, transactions should balance and should not span multiple dates.

The most effective method of identifying which column reflects the transaction ID is to filter the data and check the resultant amount balance, with unique transaction ID values yielding a net of zero.

Transaction_ID_recording_-_use__1_.gif

Common terms for transaction ID

Transaction IDs may be referred to differently depending on the software. Some common alternatives include:

  • Document number
  • Journal number
  • Transaction
  • Reference / Reference number / Ref / Ref number
  • ID 

Common challenges

  • Entries may not be recorded in the form of transactions (i.e., records are in monthly batches)
  • Some systems do not readily provide a transaction identifier
  • Transactions are sometimes recorded as large batches when imported from one system to another

Transaction ID and data integrity

When dealing with large batch transactions, it is important to understand the batches so you can determine if they can and should be broken down further. 

Some batches do not need to be broken down (for example, in payroll, Debits to Credits form a one-to-many or many-to-one relationship [or a few-to-many or many-to-few relationship]), whereas other batches may need to be (for example, a batch of 1000 entries consisting of 500, double entry, matching pairs).

Ask yourself the following questions:

  1. Is it appropriate to break the transactions down further?
  2. Could the transactions be broken down with a custom column combination?
  3. Could the transactions be broken down with a custom running total approach?
  4. If not, could the data be broken down by a particular sort order?
  5. If not, is it appropriate to use the Smart splitter?
     

I've identified the transaction ID in the data, what next?

Now that you have determined which column(s) you want to use to identify transactions, you can import the data into MindBridge. The transaction ID is applied during the Review Data step of the data import process.

Note: Mapping the transaction ID during the Map Columns step does not apply the transaction ID to your data. By mapping this column you are making it available to filter on in the analysis.

Apply the transaction ID

On the Review Data step, MindBridge will attempt to create logical groupings based on the available data, and a provide a recommendation on what it considers the strongest grouping.

To change the columns used to identify the transaction ID:

  1. Open the Select transaction identifier menu to select which data column(s) to use as the transaction ID.
    As you make selections, the graph on the right will automatically generate a visualization of the transactional structure using each ID.
  2. If your desired transaction ID column is not listed, select Custom combination.
  3. Use the Select Column menu to select the column(s) you want to use to group the transactions in the ledger.
    For example, grouping entries with the same transaction number and transaction date. Combining multiple ID components helps break down larger transactions and creates a more accurate representation of the individual transactions that took place.
  4. Use the + icon to add a column.
    Use the icon to remove a column.
  5. Select Generate Preview to update the graph on the right.
  6. When you are satisfied, select Next to go to the next step of the import process.

Gif_showing_example_transaction_ID_selection_process.gif

Transaction length summary graph

The bars in this graph represent the number of entries each transaction contains under the applied conditions (i.e., the applied transaction ID). The number of entries indicates the selected transaction ID's level of granularity, whether it represents smaller, more accurate transaction structures, or larger, less accurate batch transaction structures.

It is recommended to try to achieve a high level of granularity and reduce the number of very large batch transactions. Therefore, most transactions should be made up of 2-4 entries, and single entry transactions should be avoided.

Data integrity checks

The data integrity checks displayed below the transaction graph can help you validate whether the correct transaction ID has been applied. These checks indicate the presence of any single entry transactions, transactional imbalances, multiple posted dates, and more. They also highlight any overall imbalances or missing information in the dataset, which will impact your analysis.

Select a transaction ID that yields green checkmarks for all 6 data integrity checks:

  • Your ledger has balanced debits and credits
  • Your ledger does not contain single entry transactions
  • Your ledger does not contain any unbalanced multi-entry transactions
  • Your ledger does not contain any very large transactions
  • No transactions span more than one effective date
  • Your ledger has all mandatory information for all records


Anything else on your mind? Chat with us or submit a request for further assistance.


Related articles

Was this article helpful?