Potential Fraud Detection in JobPts

Assisting customers with tailored abuse pattern detection and fraud alert systems.

JobPts facilitates point gifting and redemption among employees, ensuring fairness and preventing misuse through robust fraud detection mechanisms. This includes real-time monitoring of transactions and redemptions to promptly identify and address any suspicious activities, maintaining a secure and trustworthy rewards ecosystem for all users.

Here are the key areas of potential fraud detection in JobPts:

Cycles Detection

This feature analyzes the flow of monetary awards between users, identifying patterns where transactions form closed loops or cycles among a group of users.

Our algorithm goes beyond simple detection by considering factors such as the value and time frame of points exchanged within these cycles. For instance, if the transferred points in all transactions within a cycle are of very similar value, it may indicate potential fraudulent activity.

Redemption Monitoring

Our system detects unusual instances of employees redeeming their points and uses machine learning techniques to model typical redemption behaviors based on historical data. This enables us to identify anomalies that may indicate fraudulent activity.

The analysis includes factors such as redemption values, frequency, detecting anomalies and deviations that could signify potential fraudulent behavior. Additionally, the algorithm flags potentially fraudulent card redemptions, such as when a user purchases a virtual card with their own funds to acquire additional benefits. In these cases, they bypass spending points for the transaction.

Image: JobPts application - Fraud Detection

Favoritism Detection

This feature uncovers favoritism or discrimination demonstrated by managers during transaction authorizations and budget allocations. It identifies cases of preferential treatment or bias towards certain individuals across various teams, examining factors such as time durations between transactions and approvals, adjustments in award point values before approval, and variations in approval patterns among managers.

This helps ensure fairness and transparency in the allocation of rewards and approvals within the JobPts platform."

If this article left your questions unanswered, please submit a Support Form, and we can clarify this topic.