HomeInterviewsInterview: CEO Amit Relan On mFilterIt Approach to Ad Fraud Prevention

Interview: CEO Amit Relan On mFilterIt Approach to Ad Fraud Prevention



During the interview with TechGraph, Amit Relan, Co-Founder and CEO, mFilterIt outlined the overview of how the ad fraud prevention market has evolved over the years and how it is using cutting-edge technologies like machine learning and artificial intelligence (AI) to prevent and detect fraudulent activities in real-time.

Read the complete interview:

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TechGraph: Can you tell us more about mFilterIt’s role in ads fraud prevention? How do your technology and services help prevent ad fraud?

Amit Relan: mFilterIt is one of the pioneers for ad traffic validation. We have helped some of the big names across various industries eliminate invalid sources from ad campaigns and achieve maximum efficiency with clean traffic.

Our solution is capable of detecting sophisticated fraud techniques across the user acquisition journey. This ensures that the sophisticated bots are not able to seep through the funnel and manipulate it. With full-funnel analysis, the advertisers get transparency of their ad traffic across the funnel and eliminate them proactively.

TechGraph: Ad fraud is a growing concern in digital advertising. In your opinion, what are some of the main challenges advertisers face when detecting and preventing ad fraud?

Amit Relan: When it comes to detecting and preventing ad fraud, advertisers encounter several challenges. Here are some of the main obstacles they face:

Sophisticated fraud techniques: Fraudsters are constantly evolving their techniques to bypass the ad fraud detection mechanisms. Earlier, the fraud techniques were easy to identify due to fixed patterns. However, with advanced techniques, these patterns are more human-like and hard to detect. Therefore, advertisers fail to identify sophisticated fraud behavior with early fraud detection methods.

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Data Quality and Accuracy: Advertisers heavily rely on data analytics and metrics to assess the performance of their ad campaigns. However, fraudulent activities can distort these metrics, leading to inaccurate insights. Ad fraud can artificially inflate impression counts, click-through rates (CTRs), and conversions, misleading advertisers into believing their campaigns are more effective than they are. This makes it difficult to make informed decisions and allocate advertising budgets appropriately.

Ad Verification and Measurement: Verifying the legitimacy of ad impressions, clicks, and conversions poses a significant challenge. Advertisers must rely on third-party verification tools and services to assess the quality of their ad placements. However, fraudsters often employ tactics to bypass these verification systems, making it harder to detect fraudulent activities accurately. Additionally, measuring the true impact and ROI of ad campaigns becomes complicated when fraudulent actions are involved.

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Amit Relan: The ad fraud prevention market has undergone significant evolution as it strives to keep pace with the ever-evolving tactics employed by fraudsters.

Here is a detailed overview of how the ad fraud prevention market has evolved:

Increased Awareness: As ad fraud became more prevalent and its impact on digital advertising became apparent, awareness among advertisers and industry stakeholders grew significantly. Advertisers began recognizing the need to protect their investments and sought solutions to combat fraud. This increased awareness has been a driving force behind the growth of the ad fraud prevention market.

Technological Advancements: With the advancement of technology, new tools and techniques have emerged to detect and prevent ad fraud. Machine learning, artificial intelligence, and data analytics have played a crucial role in developing sophisticated fraud detection algorithms. These technologies enable real-time monitoring, pattern recognition, and anomaly detection, enhancing the ability to identify and mitigate fraudulent activities.

Collaboration and Industry Initiatives: Ad fraud prevention has become a collaborative effort among advertisers, publishers, ad exchanges, and technology providers. Industry organizations, such as the Trustworthy Accountability Group (TAG) and the Interactive Advertising Bureau (IAB), have initiated programs and guidelines to combat ad fraud. Collaboration among stakeholders has led to the development of industry standards, best practices, and certification programs, fostering a more fraud-resistant ecosystem.

Enhanced Measurement and Verification: Advertisers now have access to more robust ad verification and measurement solutions. Third-party verification companies offer services that help advertisers assess the quality and legitimacy of ad impressions, clicks, and conversions. These solutions provide transparency, improve data accuracy, and help identify fraudulent activities, enabling advertisers to make informed decisions and optimize their ad campaigns effectively.

Continuous Innovation: Fraudsters continuously adapt their tactics to bypass detection systems, prompting the ad fraud prevention market to constantly innovate. Ad fraud prevention solutions have evolved from rule-based systems to more advanced machine-learning models that can detect sophisticated fraud patterns.

Cross-Device and Cross-Channel Protection: With the proliferation of mobile devices and the expansion of digital advertising across various channels, fraud prevention has extended beyond traditional web-based ad campaigns. The market has evolved to address fraud in mobile apps, connected TVs, over-the-top (OTT) platforms, and other emerging channels. Cross-device tracking and attribution solutions have emerged to combat ad fraud across multiple touchpoints.

Focus on User Experience: Advertisers and industry stakeholders have recognized the importance of maintaining a positive user experience while preventing ad fraud. Ad formats that are prone to fraud, such as intrusive pop-ups or misleading ad placements, have been discouraged. Advertisers are increasingly adopting measures to ensure their ads reach genuine human audiences and are viewable in a non-disruptive manner, striking a balance between fraud prevention and user satisfaction.

The fraud prevention market is continuously evolving to stay ahead of sophisticated fraud techniques employed by fraudsters. Several new trends and techniques have emerged in the ad fraud prevention market. Here are some of the notable ones:

Machine Learning and Artificial Intelligence: Machine learning (ML) and artificial intelligence (AI) have revolutionized fraud prevention. ML algorithms can analyze vast amounts of data to detect patterns, anomalies, and fraudulent activities in real-time. AI-powered systems can continuously learn from new fraud patterns and adapt to emerging threats, making them highly effective in detecting and preventing ad fraud.

Behavioral Analytics: Behavioral analytics is gaining traction in fraud prevention. By analyzing user behavior patterns, such as mouse movements, click patterns, and navigation paths, it becomes possible to distinguish between human users and fraudulent activities generated by bots or automated scripts.

Cross-Device Tracking and Attribution: As users engage with digital content across multiple devices, cross-device tracking and attribution have become crucial in detecting and preventing fraud. By linking user activities across devices, fraud prevention systems can identify suspicious patterns and discrepancies that may indicate fraudulent behavior.

Real-Time Monitoring and Response: Real-time monitoring has become a key focus in fraud prevention. By continuously monitoring ad impressions, clicks, and conversions in real time, advertisers can quickly detect and respond to fraudulent activities. Real-time response mechanisms, such as blocking suspicious traffic or invalid clicks, can mitigate the impact of fraud and protect advertising budgets.

Enhanced Transparency and Verification: Advertisers are demanding increased transparency and verification throughout the ad supply chain. They seek greater visibility into ad placements, traffic sources, and the overall ad ecosystem. Tools and services that provide transparency and verification help advertisers identify suspicious activities, ensure ad quality, and minimize the risk of ad fraud.

Ad Fraud Education and Training: Ad fraud prevention has become a priority for organizations, leading to increased investment in education and training.

TechGraph: With the rise of ad fraud, many advertisers are understandably concerned about their advertising campaigns’ effectiveness. What steps can advertisers take to ensure their campaigns are not impacted by ad fraud?

Amit Relan: To protect their advertising campaigns from ad fraud, advertisers can take several steps:

  • Collaborate with trustworthy ad networks, publishers, and agencies that have a strong reputation and a track record of combating ad fraud.
  • Utilize ad verification services and tools to monitor ad placements, detect fraudulent activities, and prevent ads from appearing on suspicious or non-compliant websites.
  • Continuously monitor key performance indicators (KPIs) and metrics to identify irregularities or suspicious patterns. Analyze traffic sources, click-through rates, conversion rates, and other relevant data to spot any anomalies.

TechGraph: mFilterIt offers a range of services to prevent ad fraud, including fraud detection, prevention, and analytics. Can you tell us more about these services and how they work together to protect advertisers from ad fraud?

Amit Relan: mFilterIt ad traffic validation solution ensures to identification of anomalies in the ad traffic based on multiple parameters. Its advanced technology detects invalid traffic across the user acquisition funnel and blocks it at every level. The log-level transparency helps advertisers get an understanding of invalid traffic at every stage of the funnel and take measures accordingly. The solution also provides transparency of the types of frauds impacting an ad campaign.


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Krishna Mali
Krishna Mali
Founder & Group Editor of TechGraph.

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