MarTech Interview with Mathew Ratty, CEO of TrafficGuard

Mathew Ratty shares his insights on ad fraud and attribution fraud in this MarTech interview

Welcome to MarTech Cube, Mathew. We’re delighted to have you. To begin, could you share a bit about your professional journey and what led you to your role as CEO of TrafficGuard?

Thanks for having me. My background is in venture capital and high-growth businesses, so I’ve always been wired to look at problems through a commercial lens, where is value being lost, and how do you fix it?
What’s interesting about TrafficGuard is that it didn’t start out as a fraud prevention company. TrafficGuard was developed when the business previously operated as a digital marketing company called Tech Mpire, we were running ad campaigns, managing performance marketing, and operating as a network connecting advertisers with traffic sources. It was through running that digital marketing business that we accumulated proprietary data across trillions of mobile app advertising campaign data points, and it was in that data that we kept seeing the same troubling patterns.

Ad fraud was quietly inflating costs and distorting metrics from the inside. The invisibility of it is the real danger, as these losses build up as small inefficiencies that compound into lasting damage before anyone notices. Because we were operating inside the ad ecosystem ourselves, we had a front-row seat to just how widespread it was.

So rather than continuing to operate as a network and live with that problem, we made the call to pivot. In August 2018, the company pivoted to a global B2B SaaS model and sold its digital marketing business, channelling everything into building a dedicated fraud prevention platform. That pivot, from performance marketing to ad fraud detection and prevention, became the foundation for the TrafficGuard technology that’s now protecting ad spend for major businesses around the world. Our goal is simple: ensure every click drives real value.

Affiliate marketing remains a major growth channel for brands. How significant is the issue of attribution theft and hijacked clicks within affiliate programs today?

Brands are fighting an uphill battle against advertising fraud, as advertisers are unintentionally funding bad actors manipulating the affiliate system. Attribution theft is negatively impacting ROI as fraudulent affiliates are stealing credit from legitimate partners without delivering value or measurable results. This may be written off as insignificant, but if this issue is allowed to grow unchecked, brands face decreased budgets and loss of consumer trust.

Attribution is assigned to whoever gets the last click, and fraudulent affiliates can exploit this by hijacking the final click before a purchase, taking credit from the rightful partner. Not only do brands end up paying for redundant traffic, but their future campaigns also suffer as they unintentionally optimise towards fraudulent sources, delivering invalid results. This stops growth in its tracks, as budgets are rapidly drained away by fraudsters without detection.

Running traffic from restricted geographies or accidental promotion of misleading ads breaks compliance laws, places customers at risk, and severely damages reputations.

Many affiliate managers rely on surface-level reporting. Why does attribution fraud often go unnoticed within the attribution layer?

Attribution theft works by exploiting the main vulnerability of affiliate marketing, and that is last click attribution. Click injection is a common tactic where fraudsters inject a fake click just before a conversion event, such as a purchase or sign-up, to hijack the commission that should belong to a legitimate partner. This tactic can be deployed across campaigns at scale, allowing fraudsters to siphon commissions globally.

This goes undetected as it doesn’t impact the user’s experience or flag issues. From the advertiser’s perspective, the conversion still happened and results appear to be coming in, so there’s no reason to dig deeper into the source.

Meanwhile, fraudsters tactics are becoming increasingly sophisticated, with fake clicks inserted silently into the conversion path without disrupting the transaction. The measurement platforms used to track performance aren’t equipped to detect fraud. This leaves invalid, fraudulent data to be reported as legitimate.

Attribution fraud evolved into a very real threat for advertisers. AI has given fraudsters the ability to steal attribution from behind the scenes with ease, driving up costs with redundant traffic and fabricated results. Advertisers can’t afford to ignore the issue as it creates unreliable data that misleads future campaigns. The companies that win will be the ones utilise AI to beat fraudsters at their own game, and inform themselves with clean data they can trust.

How are fraudulent partners able to claim commissions without delivering real value to advertisers?

Fraudulent partners are skilled at manipulating affiliate programs to appear like they are delivering tangible value, when in reality, they’re depleting budgets. These tactics are purpose-built to steal credit from legitimate partners quietly, and without detection.

An example is cookie stuffing, which involves the bad actor secretly attaching multiple irrelevant third-party cookies to a consumer after they visit another affiliate’s website or click a link. When the consumer visits the target site and purchases something, the affiliate program will wrongly credit the fraudster rather than the legitimate partner who actually drove the sale.

Fraudsters can also falsify attribution by URL hijacking.This involves registering a domain name that closely mimics a retailer’s, capitalising on typos and misspellings to intercept organic traffic. A consumer who slightly misspells the retailer’s name lands on the fraudulent site, which instantly redirects them to the legitimate one before they notice anything is wrong. The fraudster then claims the commission, collecting a payout for traffic that was never theirs to begin with, and that the brand would have received organically anyway.

AI has made it easier for fraudsters to generate invalid traffic and manipulate campaigns. What new risks does this create for marketers?

Originally, to carry out large-scale affiliate fraud, fraudsters would need considerable resources and technical skill. However, developments in AI have drastically increased the accessibility of sophisticated tools for fraudsters. They no longer need assets like multiple smartphones or workers in a click farm. AI lets them run repeated, scalable attacks at a fraction of the cost.

One of the biggest risks facing advertisers is how difficult it is becoming to identify fraudulent attribution. AI has made it possible for fraudsters to hijack credit for conversions they played no genuine role in driving, all while going undetected among authentic user journeys.

This can be seen in the growing sophistication of AI-powered bots designed specifically for attribution theft. Where bots could once only carry out basic tasks, AI now enables them to perform complex sequences that mimic genuine purchase paths, replicating scroll depth, cursor jitter, and dwell time to appear human. They can inject last-click touches through cookie stuffing, and fake referral chains, making it look as though a fraudulent affiliate legitimately influenced the sale. They can also set up fake accounts to bypass simple captchas, then repeat the cycle continuously, siphoning attribution credit away from legitimate partners and causing sustained, compounding losses to advertiser budgets.

Bots powered by AI are increasingly used to scale fraudulent activity. How do these automated attacks impact affiliate campaign performance and budgets

Bots aren’t just generating noise in affiliate programs, they’re being deployed by bad-faith affiliates to systematically steal attribution. Rather than driving genuine traffic, fraudulent partners use automated scripts to insert themselves into the conversion journey at the last possible moment, claiming commission for sales they had no part in influencing.

The most common method is click injection, where a bot fires a fake click just before a legitimate conversion is recorded, hijacking last-click attribution from the affiliate that actually drove the customer. Malicious browser extensions and adware take this further, dropping affiliate cookies in the background at the exact moment a user browses, regardless of whether they ever interacted with an affiliate link.

The result is that legitimate affiliates lose the commission they earned, budgets flow to partners gaming the system, and advertisers are left with distorted reporting that makes fraudulent affiliates appear to be high performers, leading to misallocated spend and underfunding of genuinely valuable partners.

Can AI also play a role in defending against these threats? How can it help detect abnormal behavior and filter invalid traffic?

Relying on manual checks alone to identify attribution fraud is no longer sustainable. With such large volumes of fraudulent clicks and falsified conversions, advertisers are stretched to the limit. AI can take the pressure off, allowing teams to focus on driving genuine growth.

One of the most effective approaches is using AI to validate the full conversion journey, from impression through to click and conversion event. Rather than looking at isolated data points, AI can audit the entire path, flagging cases where a click appears suspiciously close to a conversion with no prior impression or engagement history. This is precisely how last-minute click injection and brand bidding are exposed. A legitimate conversion journey leaves a traceable, consistent footprint, while an injected click appears out of nowhere with no supporting touchpoints.

As bad actors exploit AI to evolve their tactics, defenders can use the same technology to fight back. Machine learning algorithms can capture and analyse vast amounts of data in real-time, monitoring behavioural signals across the conversion funnel and comparing them against legitimate baselines. Anomalies like an affiliate suddenly receiving attribution credit for conversions with implausibly short click-to-conversion times, traffic from mismatched geographies, or spikes that don’t align with any promotional activity are automatically flagged before payouts are made.

ML models can also evolve alongside fraud tactics, identifying new patterns as they emerge. The result is advertising data that can actually be trusted, giving advertisers the confidence to base strategic decisions on authentic performance metrics and block fraud before it impacts budgets or legitimate affiliate relationships.

What steps should brands and affiliate managers take to better protect their campaigns and budgets from attribution fraud?

Affiliate fraud is rapidly growing in sophistication, so it’s crucial that advertisers take action to safeguard operations, consumers and reputations. Transparency and detailed reporting are key to identifying potential fraud before it damages profits. Signs of click injection, such as suspiciously short click-to-conversion times or conversions being claimed by affiliates with no plausible role in the customer journey, are red flags that warrant investigation. Frequent audits of traffic allow advertisers to trace suspicious activity back to its source and ensure fraudulent partners aren’t manipulating attribution.

Determining whether or not a conversion is correctly attributed is crucial. Advertisers can do this with a platform that analyses conversion data across hundreds of parameters to fully validate if a conversion is legitimate. By examining the full picture of what happened before and after a conversion event, it can identify when a fraudulent affiliate has manipulated the attribution path, ensuring commissions are paid to partners who delivered real value, not those who gamed the last click.

Advertisers should also consider ad fraud detection tools that integrate directly with affiliate management platforms. This degree of conversion-level visibility gives advertisers the confidence to optimise toward authentic performance data and protect budgets from being eroded by misattributed commissions.

On a personal level, what leadership strategy has helped you guide TrafficGuard in addressing complex challenges in digital advertising?

For me it comes down to never looking away from an uncomfortable truth just because fixing it is hard. The invisibility of ad fraud is what makes it so dangerous. Losses don’t announce themselves. They build quietly as small inefficiencies that compound into lasting damage before most businesses notice anything is wrong.

That shapes how I lead. When the challenge is complex, the instinct is often to add layers of complexity to the solution. I’ve always pushed back against that. Clarity of purpose is what keeps a team focused and moving in the right direction, especially in a space where the threat landscape is constantly shifting.

And ultimately it comes back to the commercial reality of the problem we’re solving. Ad fraud costs businesses real money and erodes trust in channels that should be delivering growth. Keeping that front of mind, at every level of the business, is what drives the right decisions. Our goal has never changed: ensure every click drives real value.

What advice would you give to marketers navigating affiliate fraud today, and what final thoughts would you like to share with our readers about the future of ad fraud prevention?

The first thing I’d say to marketers is don’t be lulled into a false sense of security because you’re paying on conversion. That’s the trap many affiliate programs fall into. The assumption is that if you’re only paying when a sale happens, your risk is low. But the real issue isn’t whether a conversion occurred, it’s whether your affiliate actually drove it.

The damage in affiliate fraud isn’t always about fake traffic. It’s about rewarding the wrong partners. Commissions are flowing to affiliates who injected a click at the last second, stuffed a cookie, or simply intercepted a customer who was already on their way to convert organically. That customer was coming to you anyway. The affiliate added no value, but your budget treated them as if they did.

That misattribution compounds over time. Budgets shift toward partners who appear to be performing but aren’t, while genuinely valuable affiliates are underfunded based on data that has been quietly corrupted. The decisions you make tomorrow are only as good as the data you trust today.

My advice is to look beyond conversion volume and scrutinise the full journey. Understand which partners are genuinely influencing new customers and which are simply positioning themselves to claim credit at the last moment. Vet partners rigorously and monitor for warning signs like suspiciously short click-to-conversion times or traffic that doesn’t align with any real promotional activity.

That visibility also gives you something equally valuable on the other side: confidence to grow. When you can cross-check every partner’s activity against the full conversion journey, onboarding new affiliates stops being a leap of faith. You can scale your program, test new partners, and expand into new channels knowing that any fraudulent behaviour will surface quickly before it causes lasting damage.

The future of affiliate fraud prevention will be defined by incrementality. The question can’t just be did this convert, it has to be would this have converted without the affiliate. Programs that build around that question will protect their budgets and build partner ecosystems they can actually trust.

Mathew Ratty, CEO of TrafficGuard

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