Ad Fraud Blog – Valid8

Every click matters; every click costs money. But what if many of those clicks aren’t even from real users? How do you identify the clicks that you get on each campaign as genuine and from the right audience?  Click fraud has emerged as one of the most complex, persistent threats in the world of digital advertising. It has now evolved into a sophisticated, multi-channel challenge that silently erodes campaign performance across both web and app ecosystems. From automated bots and click farms to SDK spoofing and device manipulation, fraudsters try to exploit every possible entry point of the campaign.  And it’s not a niche problem. According to a latest bad bot report by Imperva, approximately 47% of online traffic is driven by bots, and notably, around 30% of these are harmful bots commonly linked to click fraud and other deceptive activities. Moreover, according to an mFilterIt analysis of 196 campaigns, 17% of ad fraud was detected at the click stage in 2024. Therefore, whether you are running Google Ads, Meta campaigns, mobile UA campaigns through MMPs, or programmatic ad campaigns, you’re likely bleeding budget on clicks that will never convert. Manual detection or built-in platform filters simply can’t keep up with the evolving sophistication level of click fraud.  This is where click fraud prevention tools become extremely essential. They’re not just defensive shields; they are proactive, data-driven intelligence systems that protect your media investments, ensure accuracy, and enable trustworthy analytics to make informed decisions.  How Click Fraud Has Evolved: From Basic Bots to Sophisticated Deception  Click fraud used to be an easy-to-identify activity. Marketers could spot repeated IPs, abnormal click-through rates, or sudden spikes in traffic from suspicious geographies. However, that simplicity is gone.  Fraudsters now use:  AI-powered bots that mimic human-like scrolling and dwell time  Click farms using real devices and users across geographies  SDK spoofing to fake installs and events on mobile  Click injection and click flooding to game attribution models  Advanced proxy and VPN networks to bypass geo-fencing and device ID blacklisting  What makes it worse? These attacks are often customized by channel. Mobile campaigns face attribution and install fraud, while programmatic is targeted through domain spoofing and inventory arbitrage. On the surface, everything may look “normal” unless you dig deeper using multi-channel click fraud prevention tools. What Are Click Fraud Protection Solutions? Click fraud prevention tools are advanced software designed to detect, analyze, block, and report invalid clicks or malicious activities proactively. Their role is not limited to post-click analysis; they help safeguard your campaigns across all stages of the advertising funnel.  These tools are engineered to provide holistic protection across the digital spectrum, including:  Web Advertising: Search engine ads, display banners, social media campaigns, and retargeting  Mobile Advertising: App install campaigns, in-app actions, influencer-driven traffic, and affiliate marketing  Unlike standard filters from ad platforms, click fraud protection tools provide real-time monitoring, customized detection thresholds, in-depth traffic diagnostics, and actionable intelligence.  They not only block fraudulent activity but also deliver high-resolution insights, enabling brands and businesses to optimize targeting, improve media efficiency, and reduce wasted spend with confidence. For performance-driven marketers, these tools are an indispensable part of the martech stack.  Why Legacy Tools Fail in 2025 Tools built on static rules or simple blacklists are no match for detecting click fraud in 2025. These systems:  Can’t detect mobile-specific fraud like click injection or spoofed installs  Often lacks contextual behavior analysis  Miss new fraud vectors due to lack of AI  Fail to provide unified views across web and app platforms.   They’re also reactive, blocking only after fraud has occurred. A modern click fraud prevention strategy must be proactive, predictive, and adaptive.  How a Click Fraud Prevention Tool Works? Key Features You Need to Look For Modern fraud detection solutions don’t just react; they predict and prevent fraud. Here’s how they function and the core features that power them:  Rigorous Monitoring & Device Fingerprinting: Continuously tracks every click across IP address, device ID, browser type, session behavior, time stamps, and geo-location to identify anomalies.  Behavioral Analysis: Analyzes user interactions like mouse movement, dwell time, bounce rate, and frequency to flag inconsistent or bot-like behavior. Each click is assigned a trust score, with suspicious ones automatically flagged or blocked.  AI-Powered Fraud Detection: Uses machine learning trained on various data points and parameters to detect emerging fraud tactics across web, mobile, and programmatic environments.  Spoofed Proxy/VPN Detection: Detects clicks from blacklisted IPs, high-risk devices, and hidden proxies or VPNs often used by fraudsters to disguise their origin.  Click Journey & Traffic Scoring Analysis: Evaluates the full click path, from ad impression to post-click engagement, scoring each interaction based on velocity, engagement metrics, and origin.  Cross-Platform Coverage (Web + App): Provides unified protection across desktop, mobile web, and native apps, closing blind spots in hybrid campaigns.  Custom Rules Engine: Allows advertisers to configure rules around frequency capping, geo-fencing, source filtering, and time targeting to align with campaign-specific needs.  Proactive Blocking with Integration Support: Instantly blocks fraudulent clicks before budget is wasted and integrates seamlessly with platforms like Google Ads, Meta, DV360, AppsFlyer, and MMPs.  Transparent Reporting & Optimization Layer: Offers intuitive and insightful dashboards with fraud trends, high-risk geos, and detailed traffic diagnostics. Reports are shareable across teams to guide media planning and optimization.  Therefore, with all these features, an Ad fraud solution like Valid8 by mFilterIt is built to scale, acting as a strategic layer of defense that fuels better ROI and decision-making.  Case Study: How mFilterIt Drove 1.75X Higher Conversions for a Leading Automobile Brand A major automobile player was running high-intent Google search campaigns to attract new customers. However, despite significant media investment, their conversion rates were lagging expectations.   Upon deeper analysis, we detected that a considerable portion of their traffic was attributed to invalid traffic – clicks and leads. We implemented an active blacklisting strategy using Valid8 – our advanced click fraud prevention tool.  Key Outcomes After Enabling Click Fraud Protection:  13% reduction in Click Fraud  11% drop in Lead Fraud  1.75X increase in Conversion Ratio  $0.47M saved through

In recent years, the MENA region has emerged as one of the fastest-growing digital advertising markets in the world. With ad spend projected to exceed $8 billion by 2026, the region is experiencing an unprecedented surge in number of mobile-first users, rising eCommerce platforms, and innovative app ecosystems. But along with this digital acceleration comes an equally aggressive threat: ad fraud.  According to IAB MENA, up to 20% of ad budgets in the region, roughly $1.25 billion in 2023, may have been wasted due to fraudulent activity like fake clicks, spoofed installs, bot traffic, domain spoofing, and misattributed conversions, etc. And it’s only getting worse. This budget wastage is projected to go up to $1.6 billion by 2026. This staggering figure reveals a silent budget drain that’s not just affecting the bottom lines of brands in MENA – it’s distorting performance metrics, eroding trust, and misleading optimization decisions.  If your campaigns are optimized based on corrupted data, your ROAS is lying to you. If you’re relying on outdated, conventional ad fraud detection tools, you’re exposed to sophisticated tactics that go undetected in your app and web funnel.  Now the question that arises is – How do we tackle this effectively across the entire ecosystem?  Ad fraud in MENA is evolving rapidly, and so should your defense tech stack.  In this article, we’ll explore how ad fraud violates across web and app ecosystems in MENA, why traditional verification methods fall short, and the need for advanced ad fraud detection solutions to protect the digital ad spending of digital-first brands.  What Is Ad Fraud and Why Is MENA Especially at Risk? The Middle East and North Africa (MENA) region faces a particularly elevated risk of ad fraud. Here’s why:  Rapid Digital Growth and Increased Ad Spend Booming Digital Adoption: MENA is witnessing an explosive expansion of digital connectivity and e-commerce, prompting a substantial shift in brand budgets towards online advertising to engage the large scale of digital audiences. Prime Target for Fraudsters: This escalating investment naturally makes the region a highly profitable target for sophisticated ad fraud techniques. Specific Vulnerabilities in the MENA Ad Ecosystem Reliance on Aggregators and Smaller Networks: Many regional marketers depend on affiliate aggregators or smaller ad networks, which often lack robust transparency and rigorous vetting procedures, inadvertently increasing exposure to fraudulent activities. Trust-Based Partnerships: The prevalence of trust-based business relationships can sometimes bypass the need for stringent validation processes, creating openings for fraudsters to infiltrate the ecosystem. Localization Gaps: Generic ad fraud detection tools may not be fully optimized for MENA’s diverse languages and distinct user behaviors, allowing certain fraudulent patterns to slip through undetected. Lack of Benchmarks: The scarcity of widely accepted, region-specific benchmarks for campaign performance complicates the identification of anomalies and the accurate assessment of campaign effectiveness, masking the impact of fraud. Fragmented Technology Infrastructure: Varying levels of programmatic maturity across different MENA countries can result in inconsistent ad delivery, measurement, and fraud detection capabilities. Dependency on Platform-Driven Metrics: A common over-reliance on metrics provided directly by ad platforms, often without independent verification, can lead to a lack of control and transparency, making fraudulent metrics harder to discern.  Types of Web and App Ad Fraud Impacting MENA Brands Understanding how ad fraud operates across the funnel is critical to combating it effectively. Here are the most common forms of ad fraud affecting digital campaigns in the MENA region:  Web Fraud Click Fraud & Click Spamming: Fraudsters use bots or scripts to simulate user clicks, inflating CPC costs and diminishing ROAS. Pixel Stuffing & Ad Stacking: Ads are rendered invisibly (e.g., 1×1 pixels) or layered behind other content to be counted as impressions but never seen. Domain Spoofing: Fraudsters mimic premium publisher domains to sell low-quality or non-existent inventory.  Lead Gen Fraud: Fraudsters submit fake or low-quality leads to exploit CPL campaigns, draining budgets and sales resources. App Fraud Click Injection: Malicious apps on user devices simulate clicks just before a legitimate install, stealing attribution credit. Incentivized Installs: Users are offered rewards (e.g., cashbacks or discounts) to install apps without true interest in skewing retention metrics. Fake Installs & SDK Spoofing: Bots mimic install behavior or exploit app SDKs to fake installs and in-app engagement. When such fraud goes undetected, it doesn’t just waste budgets – it corrupts analytics, misleads media decisions, and diminishes LTV (lifetime value) from fraudulent users who will never convert or engage meaningfully.  How Ad Fraud Impacts Businesses in MENA  Wasted Spend: A large portion of ad budgets go to non-human or low-value traffic sources. Skewed Attribution: Fraudulent actions misattribute conversions, leading brands to invest in ineffective channels or partners. Reduced ROAS: Since bot-driven or false installs never lead to real engagement, return on ad spend drops. Data Misalignment: KPIs become unreliable because of incorrect data, affecting optimization decisions and long-term planning. Brand Risk: Ads placed on spoofed or irrelevant domains damage brand integrity. Fraud also masks real performance issues, giving marketers a false sense of success when in reality, the wins are artificially inflated. Why Traditional Methods Aren’t Enough in MENA’s Digital Landscape  Despite the rising complexity of ad fraud schemes, many advertisers in the MENA region still rely on outdated or incomplete methods of verification. They don’t offer the speed, depth, or contextual intelligence modern marketers need. Here’s why traditional methods no longer provide adequate ad fraud and mobile app fraud protection:  Manual Audits and Blacklists Are Reactive, Not Scalable Relying on manual traffic reviews or static blacklists can only detect known and repeated patterns, missing newer, evolving fraud behaviors.  In a high-volume, mobile-first market like MENA, fraud detection must be proactive and automated to catch dynamic threats before damage is done.  Lack of Standardization Across Ad Tech Partners MENA’s fragmented ad ecosystem includes multiple intermediaries and networks, many of which lack unified fraud detection protocols.  This inconsistency creates data silos and blind spots across platforms, making it difficult for advertisers to trace where fraud is occurring or hold specific partners accountable.  Blind Spots in ROAS, LTV, and

Mobile app advertising is all about data coming from CPI campaigns – ROAS and LTV being the go-to metrics to measure campaign performance and success. But are you sure the metrics you are relying on are giving you the right results?  The numbers on your dashboard are not always true.   As advertisers pour more budget into mobile performance campaigns, many overlook critical vulnerabilities – mobile ad fraud. It’s not just a line-item loss, it’s a performance killer that inflates Return on Ad Spend (ROAS) and erodes Customer Lifetime Value (LTV).  Fraudsters exploit the systems marketers depend on – attribution models and campaign metrics – using sophisticated tactics like click fraud, fake installs, click injection, SDK spoofing, etc.   The result? Campaigns scale based on fake signals, and strategies built on manipulated data lead to long-term business erosion.  In this article, we’ll break down exactly how mobile ad fraud works, why it’s killing your ROAS and LTV, and the steps you can take right now to combat fraud and protect your mobile app marketing investment.  What is Mobile Ad Fraud? Mobile ad fraud is the deliberate manipulation of ad ecosystems to produce fake user interactions – clicks, installs, or post-install events that appear legitimate but are entirely fabricated. These activities are done by sophisticated fraud networks using a range of tools, from bots and emulators to stolen device IDs and malicious SDKs.  The primary objective of fraudsters is to earn money by draining advertising budgets without delivering any real user engagement or business value. This type of fraud not only eats into your ad spending but also corrupts the data you rely on for campaign optimization and ROI measurement.  According to mFilterIt’s analysis, there has been a significant rise in ad fraud in apps at each level of the funnel, the highest being at the install stage:  Common Types of Mobile Ad Fraud Include: Click fraud: Use of bots or click farms to generate invalid clicks, depleting budgets without real engagement. Click injection: Malicious apps trigger fake clicks just before install happens, hijacking attribution for organic or paid traffic. Install farms: Real humans or emulators install apps repeatedly to simulate legitimate installs, often incentivized by rewards. SDK spoofing: Hackers simulate in-app events by manipulating SDK data, making it appear to be genuine user actions. Device farms: A collection of real or emulated devices are used to generate large volumes of fake installs and activity. Attribution fraud: Fraudsters use methods like click spamming or injection to steal credit for installs they didn’t drive.  Understanding the Mobile Attribution Flow To understand how mobile ad fraud destroys ROAS and LTV in mobile advertising campaigns, it is also important to understand the mobile attribution flow. Here’s a step-by-step breakdown of how it works: A user taps on an ad shown on their device.  That click is first logged by the media partner responsible for the ad placement, and the user is redirected to the relevant app store.  Simultaneously, the click data is sent to a Mobile Measurement Partner (MMP) who stores this engagement.  The user installs and launches the app.  When the app is opened for the first time, it triggers an SDK that sends install data back to the MMP.  The MMP matches this install event to previous ad clicks using algorithms and attribution windows.  If a match is found, the install is labeled as ‘non-organic’ and credited to the corresponding media partner.  This data is then reflected in the advertiser’s analytics dashboard, forming the basis of ROI measurement.  Fraudsters use techniques like click injection or spoofed signals to insert themselves into the attribution path at the last moment, stealing credit for real installs or faking installs altogether.  How Mobile Ad Fraud Impacts Your ROAS Return on Ad Spend (ROAS) is one of the most critical metrics for marketers. It tells you whether your advertising investment is bringing returns or not.   1. Inflated ROAS from Fake Installs Fraudulent installs, generated by bots or device farms, appear legitimate on the surface. Campaign dashboards show low Cost Per Installs (CPI), leading marketers to believe their campaigns are effective. But these “users” never convert or engage – they don’t exist.  This false sense of performance skews ROAS calculations, making underperforming channels look profitable. As a result, marketers double down on ineffective campaigns, throwing more money into a bottomless pit. 2. Simulated Post-Install Events Fraudsters use advanced fraud techniques to spoof in-app events such as sign-ups, purchases, or logins to mimic user engagement. These simulated activities trick attribution platforms into registering conversions and inflate downstream metrics.  Campaigns are then optimized for behavior that never actually occurred, misguiding everything from creative strategy to channel selection. 3. Budget Drain Through Attribution Hijacking Fraudsters don’t need to fake the whole user’s journey. Sometimes, they hijack attribution through click fraud, click injection, or click spamming. They steal credit for installs that were actually organic or driven by legitimate partners.  This leads to misallocation of ad spend, with high-performing partners being undervalued while fraudsters receive undue payouts, degrading overall ROI.  How Mobile Ad Fraud Impacts LTV Customer Lifetime Value (LTV) is a long-term metric that reflects the revenue generated by a user over time. LTV is foundational for forecasting, retention strategy, and sustainable growth. But fraud undercuts this in serious ways. 1. Zero-Value Users Coming via Incent Fraud Fake installs and incentivized users attained through malicious techniques like install farms or incent fraud typically show no engagement beyond the install. These users don’t make purchases, complete onboarding, or return to the app, meaning zero contribution to lifetime value. 2. Skewed Retention Metrics When non-human or low-intent users are included in your data, LTV projections are overestimated. You might assume a healthy user base when in reality, it’s full of churned or non-existent users.  3. Deceptive CAC-to-LTV Ratios A campaign might look profitable based on CPA and early event metrics, but if LTV is inflated due to fake users or spoofed events, the actual value delivered will never justify the acquisition cost.  What Marketers Can

With brands shifting a large amount of their budgets to digital platforms, programmatic advertising plays a crucial role in how brands optimize their budget at each stage of the funnel.  The programmatic advertising market in India is still considered to be at a nascent stage; however, it has taken a steep curve and is not going to stop.  According to the Dentsu-e4m Digital Report 2025, programmatic advertising contributed  ₹20,686 crore, accounting for 42% of India’s digital media expenditure by the end of 2024, reflecting a 21% growth over 2023. The report further projects this momentum will continue, with programmatic expected to represent 44% (₹30,405 crore) of the digital advertising market by 2026, growing at a compound annual growth rate (CAGR) of 21.24%.  With the power to automate media buying and provide real-time data, programmatic campaigns offer unmatched scalability and precision. But with great opportunity comes significant risk. If not handled carefully, programmatic campaigns can fall prey to inefficiencies and ad fraud, draining budgets and damaging brand reputation.  This article will guide you through the fundamentals of programmatic advertising, key strategies for success, and how to safeguard your campaigns from programmatic ad fraud. Whether you’re a marketer, advertiser, or decision-maker, this comprehensive guide will help you run campaigns that are both effective and safe.  What is Programmatic Advertising? Programmatic advertising is the automated method of buying and selling digital ad inventory through sophisticated software and real-time bidding (RTB) technologies. Unlike traditional advertising, which involves direct negotiations and manual placements, running programmatic ads enables instant, data-driven decisions regarding which ads to show to which user, and at what price. This automation brings efficiency, scale, and precision, allowing marketers to serve relevant ads to the right audience, at the right time, across websites, mobile apps, and connected TV (CTV) platforms.  Challenges and Limitations in Programmatic Advertising 1. Lack of Transparency Across the Supply Chain The programmatic ecosystem involves multiple intermediaries – DSPs, SSPs, ad exchanges, data providers, and more. This fragmentation often leads to limited visibility into where ads are being served, how much each party takes from the media spend, and what environments your brand appears in. This is referred to as “programmatic black box” making it difficult to determine how much of the budget reaches the publisher versus being absorbed by hidden fees and commissions.   2. Limited Control Over Ad Placement While advertisers can set targeting and exclusion parameters, the automated buying model means there’s still limited control over the final placement in open marketplaces. Ads can end up on irrelevant, low-quality, or even brand-damaging websites if proper safeguards are not in place, diluting campaign effectiveness.   3. Brand Safety Concerns With ads being served in real-time across a vast inventory, there’s always a risk of them appearing next to inappropriate, misleading, or controversial content. This not only affects user perception but can severely damage a brand’s reputation if left unchecked. Fraudsters and low-quality publishers constantly find new ways to bypass basic detection systems. Moreover, not all platforms enforce the same content quality standards, making it harder for marketers to guarantee safe environments for their ads.  4. Programmatic Ad Fraud Threat Programmatic ad fraud refers to malicious activities by fraudsters to manipulate the ad ecosystem for monetary gain. This often involves the use of bots, malware, or spoofed environments to simulate real user behavior, resulting in advertisers paying for non-existent impressions, fake clicks, or fabricated conversions.  For example, fraudsters might use domain spoofing to make a low-quality website appear as a reputable one or deploy botnets that mimic human interaction with ads. These deceptive practices compromise campaign performance, skew data, and go undetected without advanced ad fraud detection solutions.  According to first-party analysis by mFilterIt, conducted across 342 campaigns run in 2024, 31% of invalid traffic in India was coming from programmatic advertising platforms.  The highly automated and fragmented nature of programmatic advertising makes it especially vulnerable to these attacks, underscoring the need for continuous vigilance and robust verification mechanisms.  Why is there a need for fraud detection in Programmatic ad campaigns?  Since programmatic advertising involves a rapid decision-making process, everything cannot be monitored in real-time by humans, which makes these campaigns vulnerable to programmatic ad fraud. Therefore, fraud detection solutions have become an integral part of the ecosystem. These tools verify whether ads are viewable, brand-safe, and served to real users, utilizing pre-bid and post-bid filters, real-time analytics, and machine learning to detect fraudulent activity and ensure quality traffic.  Strategic Tips to Build a Safe and High-Performing Programmatic Ad Fraud Free Campaign Rather than just checking off the setup steps, smart marketers need to focus on strategic execution. Here’s how to ensure your campaign is both effective and fraud-free:  1. Optimize Campaign Reach Through Audience Modeling Use your first-party data (from CRM, website behavior, app engagement) to build micro-targeted audience segments. Supplement with second-party (from trusted partners) and third-party data (from DMPs) when relevant. Implement lookalike modeling and predictive analytics to identify potential high-value segments.  2. Prioritize Inventory Quality via Private Marketplaces (PMPs) Avoid the chaos of open exchanges when possible. Private marketplaces offer access to premium publishers, controlled environments, and better transparency. Programmatic direct is also a comparatively safer option with predetermined pricing and placement.  3. Invest in Contextual Targeting Align your ads with page content that reflects brand values and relevance without relying on user-level data. This enhances performance while staying privacy compliant. 4. Implement Frequency Capping and Creative Rotation Serving the same ad repeatedly frustrates users and depletes ROI. Ensure your campaign respects frequency caps per user and rotates creatives for freshness. Be cautious of fraudulent traffic sources that breach frequency caps to maximize fake impressions, an often-overlooked fraud tactic. 5. Exclude MFA (Made-for-Advertising) Sites MFA sites are low-value domains packed with ads and clickbait content. They exist solely to monetize traffic through ads. These environments offer little to user engagement, dilute brand value, and quietly drain ad budgets. Ensure your inventory sources filter out such domains or apply inclusion lists of verified publishers. 6. Leverage Real-Time Analytics

As an advertiser at a Fintech business, are you constantly stressed over user growth targets, tight budgets, and campaign performance pressures? Seeing the results pouring in through affiliate marketing campaigns, but something is still not working in your favor? So, what’s going wrong? Working with affiliates often feels like the quickest, most scalable, and reliable way to hit those numbers. And to be fair, it works—until it doesn’t. Behind those impressive install numbers hides a different reality—a reality that includes affiliate marketing scams like click spamming, click injection, incentive fraud, etc., which pose significant threats to both the financial integrity of your brand and user trust. We’ve seen it up close: in our analysis of 196 campaigns across industries, install-level fraud alone accounts for 43% of the total ad fraud detected. The question that now arises is – Why aren’t the fraud filters built into MMPs catching these? And more importantly, how do you ensure you’re not paying affiliates for users who never actually existed? This blog breaks it all down. Continue reading further to find the solution – How a full-funnel, validation-first approach strategy can help you protect your growth. Why Affiliate Programs Matter for Fintech Lending App Marketers? Fintech lending apps offer instant credit solutions, personal loans, and buy-now-pay-later (BNPL) options to millions of users. With an extensive range of services, these apps rely heavily on affiliate marketing programs as one of the primary acquisition channels to achieve rapid user growth in a highly competitive environment. Affiliate marketing enables fintech apps to partner with third-party publishers, influencers, and ad networks who promote the app through their owned assets like websites, social media, etc. These programs typically operate on Cost Per Install (CPI) or Cost Per Acquisition (CPA) models, where affiliates are rewarded only when a specific user action, like an app install or registration, is completed. This performance-driven approach makes affiliate marketing an attractive, scalable, and seemingly low-risk strategy for customer acquisition. To maximize reach and conversion, fintech lending apps frequently run targeted campaigns such as: · Referral-based promotions with sign-up bonuses for both parties · Cashback offers upon completing the first transaction or loan disbursal · Limited-time loan offers marketed through affiliate push channels · Influencer-driven traffic from content creators in personal finance and credit niches Therefore, this channel demands substantial investment. According to Juniper Research, the average CPI for fintech apps ranges from $2.50 to $6.00, reflecting the high cost of acquiring quality users. With large-scale campaigns often spanning multiple geographies, fintech advertisers end up spending millions monthly on affiliate-driven traffic, making them a prime target for sophisticated affiliate fraud schemes that exploit these high-payout campaigns. What type of Affiliate Fraud Techniques Impact Fintech App Campaigns? As fintech lending apps continue to scale aggressively through affiliate marketing, they face growing threats from sophisticated fraud techniques designed to exploit CPI and CPA models. These fraudulent activities not only siphon off ad spend but also distort key performance metrics, leading to poor marketing decisions and wasted budgets. Here are the most prevalent forms of affiliate fraud targeting fintech apps: – Click Spamming Click spamming, also known as organic poaching, involves fraudsters bombarding attribution systems with an enormous volume of fake clicks, often generated through malicious apps running in the background on a user’s device. These clicks have no real user intent behind them, but if an install happens later, the fraudulent affiliate is falsely credited. This dilutes attribution accuracy and eats into organic user credit, masking true campaign performance. – Bot-Generated Installs Using advanced scripts or emulators, fraudsters deploy bots to simulate real app installs. These bots mimic user behavior to bypass basic fraud detection, but in reality, there is no actual user engagement. This leads to inflated user acquisition numbers and higher CPIs, with no value delivered. – Click Injection Click injection is another form of attribution fraud where a malicious app on a user’s device monitors installs and broadcasts. Just before a legitimate app install begins, it injects a fraudulent click to hijack the attribution. This tactic is especially common on Android and gives fraudsters credit for installs they didn’t influence. – Incentive Fraud Under an incentive fraud scenario, users are lured to install apps purely for incentives, such as rewards, cashbacks, or gift cards, promoted by deceptive affiliate sources, not the brands. These users have no intention of engaging with the app long-term, resulting in low retention, poor ROI, and skewed user quality metrics. – Event Spoofing Sophisticated fraudsters simulate post-install in-app events like loan applications, repayments, or KYC verifications to trick marketers into believing that real engagement has occurred. These spoofed events distort downstream performance metrics and hinder optimization strategies How to Know if Your App Campaigns are Impacted by Affiliate Fraud? Together, the above-mentioned tactics form a multi-layered affiliate fraud scam that fintech advertisers must address proactively to protect their marketing investments. Here are some of the red flags that marketers and app owners should monitor consistently to uncover fraudulent traffic: – Unusually High Install Volumes with Low Engagement: A sudden spike in installs without a corresponding increase in logins, KYC completions, or loan applications could indicate click spamming or bot-driven installs. – Discrepancies Between Reported Installs and Backend Data: When attribution platforms report high install numbers, but internal app analytics show minimal usage, it’s a strong signal of non-genuine activity. – High Uninstall Rates: If users are uninstalling the app within a few hours or days of installation, it often points to incentivized installs or low-quality affiliate traffic with no long-term value. – Inconsistent Geographic Patterns: Fraudulent traffic may originate from regions that aren’t part of your target audience or display device language/location mismatches. When left unaddressed, these red flags erode both financial resources and user trust, two critical pillars for any fintech business. Why are MMPs not enough to detect Affiliate Fraud in Apps? Most traditional ad fraud detection solutions in the market are not well-equipped to handle the level of sophistication fraudsters now employ, particularly in high-value verticals like