To configure abnormal activity monitoring patterns or groups via Tool #101 Abnormal Activity Monitoring Config, you will first need to determine your credit union's thresholds for normal and abnormal activity. You may start from scratch or base patterns on previous cases of fraud.


Basing Patterns on Past Fraud
You can reverse engineer patterns based on fraud you’ve experienced in the past. Configure the pattern to monitor the same type of transaction and base the threshold numbers around the experienced fraud to ensure it will be flagged.

After configuring your pattern, run a test for the date you experienced the fraud and see how many accounts, along with the original account with fraudulent activity, appear. Fine tune your configuration and run another test; repeat as necessary until you are satisfied with the resulting accounts.


Starting from Scratch
If you a data analyst on staff, you may ask them to build custom queries on member transaction activity for specific origin codes or transaction types for all members or designated member groups. You may reach out to Asterisk Intelligence to build custom queries for you as well. The data within these queries will give you a good starting point for determining abnormal/normal transaction ranges.

To find a starting point for your configurations without using query, launch Tool #775 Sample Transactions by Delivery Channel. Select the Go! button next to the analysis method you are interested in monitoring (e.g., ACH Processing). The dashboard will display the number of transactions each account performed for that delivery channel over the past month end.

This information alone can give you an idea of the average number of transactions, but you will need to dig a little deeper to learn more about transaction amount. Note the account number of the member with the highest number of transactions.

Search this account in member inquiry. Select the Participation/Products tab and select Transaction Activity.



The dashboard shows the member's activity over the past three months. Select Compare to All Members. The All Mbrs Average Totals column displays each origin's average amount/number of transactions for all memberships. 



You can use these numbers as a starting point to determine the abnormal threshold.

After configuring a transaction pattern, select Run a test to view the accounts that populate the dashboard. Edit your pattern configuration and run tests until you are comfortable that you have a reasonable review population.