Rewarded advertising has become a powerful growth channel for mobile apps and advertisers.
However, with this growth, another issue emerged: fraud.
Fraudsters are now using device farms, multi-accounting, and purchase abuse to hack the system and get rewarded.
To address these challenges, MAF recently hosted the webinar “To Catch a Thief: How the Rewarded Advertising Ecosystem Stops Fraud,” bringing together industry leaders from Scrambly, Verisoul, Singular, and MAF.
The discussion explored how fraud impacts every layer of rewarded advertising and why collaboration is crucial when it comes to fraud prevention.
In this blog post, we recap the most important insights from the conversation.
Understanding the Rewarded Advertising Ecosystem
When you think of rewarded advertising, you need to think of a multi-layered ecosystem.
Each layer plays an important role in delivering value to both users and advertisers.
- Fraud prevention specialists, like Verisoul, perform a first check to assess whether the user is a real or a fake account.
- Rewarded discovery platforms, like Scrambly, bring the users into the advertisers’ funnels.
- Rewarded networks, like MAF, manage the end-to-end rewarded journey, ensuring users complete real actions and receive rewards.
- MMPs, like Singular, act as a neutral third-party, analyzing the data from various advertising networks to provide a unified view of app marketing campaigns.
One of the key points emphasized during the webinar is that fraud in rewarded advertising doesn’t impact a single player alone.
As Henry LeGard from Verisoul shared, the digital advertising industry is expected to lose over $172 billion to fraud by 2028.
With stakes so high, every agent involved must understand how fraud today works and how to prevent it.
How Fraud Has Evolved in Rewarded Advertising
In the early days, fraud was quite straightforward. It often involved a few sources that were easy to identify and block.
Today, however, fraudsters act in a more subtle way, making detection more complex.
For example, a user generating $12 in rewards may seem legitimate, but when these rewards are illegitimate and repeated across multiple channels, they can add up fast.
How the Rewarded Advertising Ecosystem Stops Fraud
Now, let’s get to the main topic of the discussion and see how the rewarded advertising industry stops fraud at each level.
Step 1: Verification
The first step of fraud prevention is verification. Fraud prevention specialists, like Verisoul, focus on identifying fraud that can multiply on a large scale.
For example, a few common tactics used by fraudsters that Verisoul sees daily are:
| Multiple accounts from the same device | Fraudsters often reuse devices, emulators, and device farms. One way to limit this is to enforce a one-account-per-device policy, which would then increase the cost of fraud. |
| Account abuse and identity manipulation | Rather than creating new accounts from scratch, fraudsters buy aged or pre-verified accounts (such as Gmail accounts) to appear legitimate. These accounts are then controlled by bots or automated agents that complete rewarded actions, including playing games. |
| Geographic spoofing | A significant portion of rewarded fraud originates from known geographic hubs. Because rewards are often higher in certain countries, fraudsters attempt to appear as users from high-value regions while operating elsewhere. So they rely on VPNs, proxies, emulators, and server-based devices to mask their true location and bypass geographic restrictions. |
| Click farms and phone farms | Despite technological advances, manual phone farms remain common. Large groups of low-paid workers use physical devices to complete rewarded tasks at scale, making the activity look more human and harder to detect. |
To stop these types of fraud, fraud prevention specialists are able to detect:
- VPNs and proxies
- Device spoofing and emulators
- Multi-accounts
- Impossible travel patterns
- IP and carrier inconsistencies
Step 2: User Acquisition
Rewarded discovery platforms like Scrambly sit at the first touchpoint, where traffic quality has an impact on the entire rewarded advertising chain.
As Illia Frantsevskyi from Scrambly highlighted, they focus on behavioral fraud detection. In other words, on all those behaviors that appear unnatural.
For example, a few indicators of fraud might be:
- A short time between installs, events and purchases.
- A user missing steps in the funnel.
- An abnormally fast progression.
- An unrealistic purchase behavior (e.g., large purchases minutes after install).
By analyzing these signals, rewarded discovery platforms can prevent low-quality or automated traffic from even entering advertising funnels.
Step 3: Rewarded Platforms
Monitoring users’ behavior also plays a crucial role for rewarded networks, like MAF.
These platforms keep track of different behaviors – like progression, session patterns, earning and more – against standard metrics.
Users who show unnatural patterns get blocked at the early stages.
However, fraudsters can slip through the cracks, because they can act legitimately at the beginning and then exploit the system later.
That’s why it’s important to keep an eye on other suspicious behaviors, especially during withdrawals and payouts.
Step 4: Measurement
Finally, mobile measurement partners like Singular act as the ecosystem’s source of truth.
Their job is to make sure that installs, clicks, and purchases actually come from real users, and that the right partners get credit for them.
Because MMPs see traffic from all sources, not just rewarded ads, they know what normal user behavior looks like.
This makes it easier to spot activity that doesn’t add up, such as installs that never engage, purchases that happen unrealistically fast, or huge volumes of clicks that don’t turn into real users.
Another key role of MMPs in fraud prevention is detecting attribution-based fraud.
For example, some fraudsters use techniques such as click flooding, postback hijacking, and fake installs to claim attribution.
MMPs can detect these patterns and block them.
Balancing Fraud Prevention and User Trust
Another key point was raised during the webinar.
While preventing fraud is critical, overly aggressive detection methods can be just as damaging as fraud itself.
There are cases where legitimate users are incorrectly flagged as fraudsters, and this can undermine user trust.
So what’s the solution here?
The panel highlighted that fraud prevention should not rely only on immediate bans.
Today, many platforms are shifting toward risk-based approaches.
Suspicious activity is flagged and monitored over time before an actual ban is issued.
This approach reduces the chances of error but still allows the system to respond quickly if fraud is confirmed.
The Big Takeaway: Collaboration Is the Only Way Forward
One message resonated consistently throughout the webinar: fraud prevention in rewarded advertising cannot succeed if there isn’t cooperation.
Fraudsters collaborate, share tools, and adapt quickly to new defenses. To keep pace, the ecosystem must do the same.
A collective approach increases the cost of fraud and reduces its scalability, making the ecosystem less attractive to bad actors over time.
By working together, the rewarded advertising industry can protect performance, preserve user trust, and ensure that rewarded advertising remains an effective growth channel.
Conclusion
To hear the full conversation and dive deeper into these insights, you can watch the recording of the webinar directly on LinkedIn.
If you’re interested in learning more about how MAF approaches fraud prevention, feel free to get in touch with us.
