The true cost of ad fraud in 2024: Strategies to outmanoeuvre the fraudsters - Part 1

‘Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.’

These words, commonly attributed to either American retailer John Wanamaker or UK industrialist Lord Leverhulme, are frequently cited in discussions about the effectiveness of advertising.

Indeed, it wasn’t about advertising fraud, our topic of discussion in this two-part series. However, the contemporary landscape is fraught with the inevitable threat of ad fraud, which has emerged as an omnipresent menace, actively diverting funds away from marketers.

Fraudsters are akin to chameleons, adapting and evolving with their street-smart guile. As we approach 2024, the question on everyone’s mind is: How will ad fraud tactics evolve, and what measures can advertisers employ to outmanoeuvre the ever-adapting strategies of fraudsters? Equally important is the need for them to collaborate to create a more resilient advertising ecosystem.

The evolving pace

The constant and evolving pace of digital advertising continues to make the digital landscape more complex and bring new challenges with malicious bots designed to commit ad fraud, points out Laura Quigley, SVP, APAC, Integral Ad Science.

“Juniper Research stated that $84 billion of ad spending will be lost due to ad fraud in 2023, which is expected to reach $172 billion by 2028. Leading into 2024, a few anticipated ad fraud tactics marketers are likely to encounter include device spoofing, site and app spoofing, hidden ads, ad stacking, and pixel stuffing. As technology advances, so do fraudsters,” she says.

Quigley cites Generative AI as a great example. AI-generated content is very difficult to detect and classify. According to Juniper Research, fraudsters are investing in AI to not only mask their illegal behaviours but also detect opportunities where they can spoof valid traffic. It's important to note that SIVT (Sophisticated Invalid Traffic) uses AI to intentionally avoid detection from AI-based fraud mitigation frameworks, creating an antagonistic game resulting in low returns for advertisers. However, not all AI-generated content is bad. Some AI-generated content may be useful, but people and advertisers deserve to know the source to make informed decisions based on their preferences and campaign objectives. That is why IAS continues to leverage machine learning and advanced web/ in-app technologies, both powered by intensive intelligence gathering, to detect non-human traffic of any kind. “While most solutions rely solely on an automated check to detect any invalid traffic, IAS’s unique, three-pillar approach is powered by unmatched scale and machine learning, providing the most accurate detection and prevention,” she says.

In today’s ad-fraud environment, we have begun to see fraudsters increasingly exploit vulnerabilities within targeted systems, points out Andreas Naumann, Anti-Fraud Evangelist at AppsFlyer. Consequently, he adds, the evolution of countermeasures must be tailored to these specific systems and their adaptive changes.

He stresses that the most effective defense for advertisers lies in possessing comprehensive knowledge and expertise in the field. Despite utilizing anti-fraud tools, they should maintain an internal resource capable of verifying whether the chosen tool is suitable for its intended purpose and effectively safeguards the unique campaigns run by the advertiser.

Fraudsters are always trying to stay ahead of the industry and exploit any systems possible to commit fraud, ultimately siphoning money away from legitimate media owners, opines Nick Frizzell, VP, Marketplace Quality, Magnite.

“Bad actors target all formats, with a particular focus on emerging formats such as Out-of-Home (OOH), audio, Connected TV (CTV), and others. One simple way to stay ahead of the curve and reduce the risk of ad fraud is to work with known and trusted media owners. A lot of fraud comes from lesser-known players in the industry, so understanding the supply chain and only working with reputable publisher and sell-side partners is a simple way to protect your media spend from bad actors,” he adds.

To identify and prioritize ad fraud threats in 2024, stakeholders should focus on comprehensive data analysis, employ AI-driven anomaly detection, and collaborate with industry peers to share insights on prevalent fraud tactics, says Sharath Madhavan, Lead - Performance Marketing, TheSmallBigIdea. According to him, continuous monitoring and adapting detection strategies will be crucial in staying ahead of evolving threats.

According to Tej Naidu Kota, Business Head, PAD, the industry can expect the following types of ad frauds:

AI-powered bots: Multi-device attacks - Fraudsters will leverage coordinated attacks across desktops and mobile devices, making attribution difficult.
Deepfakes:Utilizing synthetic media to create realistic fake clicks and impressions.
Emerging channel:Fraudsters will exploit new advertising platforms and formats like voice-activated ads.

In the realm of digital advertising, ad fraud is a persistent challenge, says Rakesh Mittapelly, Media Head, BCWeb Wise. As we look ahead to 2024, it's expected that those perpetrating ad fraud will likely adapt their tactics to evade detection and exploit new vulnerabilities. He gives a clearer breakdown of how ad fraud might evolve and what advertisers can do:

Sophisticated tactics:

Fraudsters may employ more sophisticated methods, such as using artificial intelligence to mimic human behavior or targeting newer advertising platforms that might have weaker security measures.

Prevention measures

As we approach 2024, the industry needs to explore technologies or strategies that are pivotal in combating the growing threat of ad fraud.

When it comes to advertisers protecting their digital campaigns against ad fraud, a combination of various measures can help them mitigate the risk, says Laura Quigley.

For example, she adds, using sophisticated AI-powered ad fraud detection solutions can help to identify and prevent ad fraud. AI algorithms can identify fraudulent activities like click fraud, bot traffic, and ad stacking.

“Second, working with trusted verification partners who have a good track record of preventing ad fraud can help advertisers understand how their digital campaigns are susceptible to ad fraud, thus implementing strategies that fight it. Third, by monitoring their digital campaigns closely, advertisers can spot suspicious activity and crack down on it. Finally, advertisers need to follow industry best practices to ensure their digital campaigns are protected against ad fraud,” she says.

She points out that since ad fraud is not restricted to mobile, desktop, or CTV platforms, the onus to prevent ad fraud lies with the entire ad tech industry. Certainly, she adds, advertisers and publishers working together to resolve trust and transparency challenges with more informative conversations about ad fraud in order to mitigate the risk within campaigns is a step in the right direction.

The crucial element for fraud protection, prevention, and detection in the ad ecosystem is the standardization of ad engagements, points out Andreas Naumann. According to him, it is imperative that measuring parties within the ecosystem can accurately assess real-world occurrences of fraud. “The transparency of user and data flow, detailing the specific sequence of events and identifying the parties involved in the value chain, is paramount. Ad fraud is most potent in environments characterized by opacity and inaccuracies, making transparency a key defense against this threat. Of course, this transparency cannot come at the cost of user privacy and must be offered within the strict privacy-oriented frameworks and policies.” says Naumann.

Rakesh Mittapelly lists out some tools and real-time techniques that advertisers can employ:

Tools:

Fraud prevention platforms:

White Ops:Offers sophisticated solutions using AI and machine learning to detect and prevent ad fraud.
Double Verify:Provides comprehensive verification services to ensure ad quality and authenticity.
Anura:Uses real-time analysis to detect and block fraudulent traffic.

Blockchain integration:

AdChain:Leverages blockchain technology to create a transparent and secure ecosystem for digital advertising.
Lucidity:Uses blockchain to provide transparent ad data, ensuring the authenticity of ad impressions and engagements.

Verification services:

IAS (Integral Ad Science):Offers verification tools to ensure ads are delivered to real humans in suitable environments.
MOAT:Provides analytics and measurement tools to verify ad viewability and prevent invalid traffic.

Real-time techniques:

AI-powered fraud detection:

Utilize AI and machine learning algorithms to analyze traffic patterns, detect anomalies, and identify fraudulent activities in real time.

Behavioral analysis:

Monitor user behaviour to detect unusual patterns that might indicate fraudulent bot activity, such as rapid clicks or unrealistic engagement rates.

IP and device analysis:

Track and analyze IP addresses and device characteristics to identify and block suspicious or non-human traffic.

Constant monitoring:

Regularly monitor campaign performance and engagement metrics to spot any sudden deviations or irregularities in real time.

Collaborative efforts:

Engage in industry collaborations and share information about emerging fraud tactics to collectively stay ahead of fraudsters.

User authentication:

Implement measures like CAPTCHA or two-factor authentication to ensure that interactions are with real users rather than automated bots.

Employing these tools and techniques in real-time allows advertisers to proactively detect and prevent ad fraud, safeguarding their ad campaigns and marketing budgets from malicious activities.

According to Tej Naidu Kota, the preventative measures include:

Multi-layered defense - Combine human expertise with AI-driven solutions for comprehensive protection.
Real-time monitoring - Continuously analyze campaign data for suspicious patterns and anomalies.
Device verification - Implement robust measures to identify and block fraudulent traffic sources.
Partner with trusted platforms - Choose ad networks with strong fraud prevention measures.
Advanced detection tools - Advertisers should invest in advanced tools that use AI and machine learning to detect irregularities in ad performance and user behaviour.
Stringent verification - Implement rigorous verification processes for traffic sources and consider third-party verification services to ensure ad placements and audiences are legitimate.
Blockchain technology - Exploring blockchain can add an extra layer of transparency and security, making it harder for fraudulent activities to go undetected.
Constant monitoring - Regularly monitor ad campaigns, analyzing metrics to spot any unusual patterns that might indicate fraudulent activities.
Industry collaboration - Collaboration within the industry helps share insights and best practices, strengthening the collective defense against ad fraud.
Education and tools - Educating teams about the latest fraud techniques and providing them with specialized tools and training ensures everyone is vigilant and equipped to tackle evolving threats.

“By combining these strategies – using advanced technology, staying vigilant, collaborating within the industry, and continuously educating teams – advertisers can proactively safeguard their campaigns against the ever-evolving landscape of ad fraud, ensuring their investments are protected and their campaigns maintain integrity,” Tej Naidu Kota adds.

(Tomorrow: How can marketers leverage emerging solutions, such as monitoring invalid clicks and geolocation tracking, and the importance of standardised industry certifications.)