At a Glance: This article will help you understand how to track, monitor, and analyze fraudulent activities happening on the platform, specifically around installs and in-app events.
Introduction
Ad fraud is a major concern in the performance marketing ecosystem, leading to revenue loss and skewed campaign data. The Fraud Report feature in the platform allows you to track and review fraudulent installs and in-app events. It provides both real-time blocking of fraud and post-attribution analysis to ensure better decision-making and budget protection.
Video to watch
Fraud Report for Installs
Real-Time Fraud Detection
This section shows fraudulent installs that were blocked immediately.
Fraud detection happens before attribution. If an install is identified as coming from a fraudulent media source, it is blocked and not counted as a valid install.
This protects your data accuracy and prevents fake installs from impacting your campaigns.
Post-Analysis Fraud Detection
Once installs are processed, a post-analysis is performed to double-check fraud status.
If any wrongly flagged installs are found genuine during the backend review, the system updates the fraud count.
The number displayed here reflects the latest validated fraud count.
Similarly, Fraudulent Costs indicate the potential spend saved by blocking these installs.
Post-Attribution Fraud
Some fraudulent activities are detected after attribution is done. This is referred to as post-attribution fraud.
It can be identified within the install day and up to 7 days afterward (8 days in total).
Since installs cannot be deleted after being attributed, these cases are flagged and monitored separately.
Trends and Graphs
Visual graphs display trends in both real-time and post-attribution fraud detection.
Helps you track fraud patterns over time and take corrective action.
Common Fraud Triggers
The system uses multiple fraud detection logics, and the following triggers are commonly flagged:
Fake Device: Installs generated from simulated or fake devices.
App Version Mismatch: When the app version during the install request doesn't match the actual installed version.
SDK Spoofing: Fraudulent attempts to simulate valid SDK signals without actual app installs.
Untrusted Device: Installs coming from suspicious devices, possibly using anonymous IPs or invalid SDK signatures.
Understanding these triggers helps you detect the source of fraud and safeguard your campaigns.
Fraud Report
This section displays detailed daily data on rejected installs and rejected costs for your selected date range.
Helps in tracking how much potential loss was prevented.
Fraud Report for In-App Events
Similar to installs, in-app events are also monitored for fraudulent activities.
The same filters and detection logic are applied to ensure that your event data is clean and trustworthy.
Helps prevent manipulation of event-driven metrics or revenue reporting.
Filters
You can filter out the data of the report based on geolocation, agency, partner, and campaign and can have additional attributes for grouping data.
In case you want to set the time period for post-analysis of fraud data yourself, you can do that as well by going to the app settings page.
We are delighted to have assembled a world-class team of experienced professionals who are ready to take care of your queries and answer any questions you may have.
Feel free to reach out to us at any time by emailing us at support@apptrove.com or by using the in-platform chat feature. We'd love to hear from you!
