Clean traffic is no longer optional, it’s a competitive advantage. That’s why Swaarm has partnered with ClearTrust, a leading fraud prevention and traffic quality platform, to help advertisers, publishers, and arbitrage teams protect performance at every stage of the user journey. In today’s performance-driven advertising ecosystem, protecting clean traffic across paid media, native, search arbitrage, and CTV is critical for sustainable performance.
By combining Swaarm’s advanced tracking, attribution, and traffic routing capabilities with ClearTrust’s real-time fraud detection and adaptive threat modeling, the partnership enables teams to identify, score, and act on traffic quality signals before revenue is impacted. From pre-lander filtering to post-click analysis, the Swaarm × ClearTrust integration ensures that every click has the best possible chance to convert, without fraud slipping through the cracks.
To dive deeper into the evolving ad fraud landscape and best practices for staying ahead, we sat down with Manish Gadhe, a seasoned ad fraud and traffic quality expert at ClearTrust. With hands-on experience across performance marketing, native, search arbitrage, and CTV, Manish shares practical insights into how fraud is changing and what advertisers and publishers should be doing now to stay protected.
How does ClearTrust differentiate between invalid traffic and legitimate (clean traffic) but unusual users (e.g. VPN users or privacy-conscious users)?
At ClearTrust, we believe fraud detection should be smart, not trigger-happy.
Our platform runs on a multi-layered scoring and filtering engine with 200+ customizable filters, each designed to identify a specific threat pattern across the advertising ecosystem. These filters analyze device behavior, referrer authenticity, environmental anomalies, viewability signals, and engagement patterns in real time.
Instead of relying on static indicators like IP addresses or user agents alone, we focus on behavior over time and full session context. This approach allows us to accurately separate malicious automation from real, privacy-conscious users such as VPN users.
The result: fraud gets blocked, while genuine users stay welcome. That balance is critical for sustainable performance marketing.
From ClearTrust’s perspective, what fraud types are most prevalent today across the industry?
Fraud today is smarter, faster, and far more convincing, largely thanks to AI.
We’re seeing advanced bot activity that mimics real users, including AI-generated user agents, realistic browsing flows, simulated scrolling, session depth, and time-on-page, all engineered to bypass traditional detection.
On the CTV side, fraud has evolved into dynamic spoofing, with device IDs, bundle IDs, and app signatures rotating intelligently. In lead generation, synthetic identity fraud is surging, with bots submitting data that looks valid but is fabricated or stolen.
That’s why ClearTrust focuses on adaptive threat modeling, not static rules. Modern fraud isn’t just about bad clicks, it’s about intent and consistency across the entire funnel.
When partnering with a tracking platform like Swaarm, what are the key integration best practices for optimal fraud prevention?
Speed and collaboration are everything. Once the initial integration is done correctly, scoring, filtering, and optimization follow naturally. This is where working with a technically agile partner like Swaarm really shines.
Winning technical setup:
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API integration for real-time, server-side filtering
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JavaScript for behavioral and browser-level intelligence
Best practices we recommend:
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Pass macros: IP, user agent, referrer, device ID, click ID
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Use custom filter profiles per traffic source
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Enable dynamic scoring responses (allow, block, redirect)
In short: move fast, filter smart, stay flexible.
Can you share a real-world example where ClearTrust significantly reduced fraud and improved performance?
One standout case involved a US-based advertiser running search arbitrage campaigns on native traffic. They faced heavy deductions due to bots, spoofed referrers, and proxy traffic.
By integrating ClearTrust’s SafePixel on the pre-lander, the advertiser gained real-time visibility into traffic quality before users reached the search feed. Invalid traffic was blocked instantly, stabilizing margins and protecting monetization.
Key takeaway: early-stage traffic filtering can make or break arbitrage profitability, and placing fraud protection at the right point in the funnel delivers immediate, measurable ROI.
What shift in ad fraud has surprised you most?
Without question: AI-powered CTV and mobile fraud.
High CPMs and complex ecosystems make these channels prime targets. Fraudsters now deploy spoofed device IDs, fake apps, and fabricated app store URLs that appear legitimate on the surface. What’s truly alarming is how AI-driven fraud adapts in real time, adjusting behavior, engagement, and viewability signals dynamically to avoid detection.
The real differentiator today isn’t having filters, it’s how fast those filters adapt. Our biggest wins come from deploying real-time, custom filter profiles, sometimes down to the sub-publisher level. Speed and precision are everything to achieving clean traffic and marekting goals.
Which industry events do you find most valuable for staying ahead of fraud trends?
A few consistently stand out:
These events bring together advertisers, publishers, adtech platforms, and fraud specialists, making them invaluable for staying ahead of emerging threats.
One piece of advice for advertisers and publishers who want to stay ahead of fraud in 2026
Treat traffic quality as a core KPI, not an afterthought. Teams that prioritize clean traffic as a core KPI consistently outperform those that treat fraud prevention as an afterthought.
Choose a fraud prevention partner with a proactive mindset, validate traffic in real time, especially at the click or pre-lander stage, and test new sources carefully. Build strong feedback loops between your data, your tracking platform, and your partners.
In 2026, performance without protection is a short-term win with long-term consequences.
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