RBI Proposes 1-Hour Pause For High-Value UPI Payments: What It Means For You
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5,000+ LPG Booking Scam Accounts Detected: How Fraudsters Exploits Essential Services During Crisis
Consumer behaviour shifts rapidly during times of uncertainty. People seek immediacy, convenience, and assurance, especially when it comes to essential services. Unfortunately, this urgency is exactly what fraudsters capitalize on. Our fraud detection experts identify various types of scams day in and day out. And what we have witnessed recently is not just another wave of financial fraud, but a shift in how fraud embeds into everyday customer journeys. We have identified scams related to LPG gas bookings due to the shortage, considering the critical situation outside. Fraudsters are leveraging a sophisticated mix of fake websites, phishing scams, social media posts, and messaging platforms to appear legitimate. This is a critical inflection point. Because, unlike traditional investment scams that rely on greed or high-return promises, these scams exploit need and necessity. They target consumers in moments of urgency, when trust is assumed without verification. How Fraudsters Operate Through LPG Booking Scams? Even scams during national events and crises like war situations, pandemic waves, and natural disasters, etc. follow a structured model designed to guide users from discovery to payments. Here’s how LPG booking scam works: Fake messages creating urgency and panic Fraudsters begin by creating panic-driven messaging such as “gas connection will be disconnected” or “limited stock available.” These messages are often linked to ongoing situations like shortages or supply concerns. The objective is to push users into taking quick action without verification. Creation of digital assets like fake websites, social media handles, etc. Once attention is captured, users are directed to fake platforms. These include lookalike booking websites, misleading landing pages, or sponsored links that closely resemble legitimate services. Their purpose is to create a convincing first impression and reduce suspicion. Bulk messaging-based attacks Fraudsters also rely heavily on messaging-based platforms like WhatsApp, Telegram, SMS, etc. to circulate fake booking links, payment links, and even KYC update requests, often framed as urgent actions that need immediate attention. This coordinated, multi-channel presence creates repeated exposure, making the scam appear more legitimate and increasing the likelihood of user interaction without proper verification. Customer care impersonation and call-based fraud In many cases, fraudsters directly interact with users by posing as customer support representatives or gas agency officials. They guide users step-by-step, using scripted conversations to build trust and create a sense of legitimacy. UPI fraud and unauthorized transactions Once trust is established, users are asked to make payments through UPI or bank transfers. These payment details are not linked to official entities, and funds are often routed through multiple mule accounts, making tracking and recovery difficult. Disappearance after payment and no service delivery After the transaction is completed, fraudsters cut off communication. The websites, phone numbers, or links used during the interaction become inactive, leaving users without any confirmation, service, or refund. Why The Rise in Digital Scams Demands a Broader Industry Response? Digital scams or investment scams are not just platform problems, nor solely regulatory challenges. But an ecosystem issue. Brands, digital platforms, regulators, and brand protection technology providers need to collectively rethink how trust is built and protected online. Because the question is no longer “Is this ad or website safe? It is now “Is this interaction authentic?” And that requires a fundamental shift from reactive moderation to proactive intelligence and continuous monitoring across the entire digital landscape. How mFilterIt Helps Identify Digital Threats Using OSINT Technology To tackle such evolving digital scams, the approach needs to go beyond surface-level fraud detection. Here’s how mFilterIt’s brand protection solution helps: Continuous monitoring across digital ecosystems including websites, search engines, social media platforms, and app environments, etc. to detect fake booking websites, phishing links, brand impersonation fraud, and malicious APK distributions. Identifies patterns and anomalies such as sudden spikes in crisis-related keywords (e.g., “urgent booking”), coordinated campaigns, and emerging fraud narratives linked to real-world events. Tracks misuse of brand names, government schemes, and crisis-driven messaging, helping uncover fake ads, sponsored scam campaigns, and misleading promotions designed to build trust. Analyzes social media and messaging platforms to detect fake posts, viral scam creatives, and coordinated disinformation campaigns, including how such content is amplified across networks. Combines AI-led intelligence with human validation to verify critical elements such as payment instruments, UPI IDs, bank accounts, and other suspicious activity signals. Maps complete fraud infrastructure, including linked domains, payment handles, phone numbers, and email IDs, to connect multiple fraudulent assets to a single organized network. Moreover, once fraud is detected. The brand protection solution also helps in: Reporting fraudulent assets to platforms, hosting providers, and domain registrars for takedown. Shares structured intelligence with law enforcement and relevant authorities, including fraud URLs, payment details, and evidence to support investigation. Enables faster identification and blocking of mule accounts, fraudulent payment channels, reducing financial loss and limiting further spread. Issues early warnings and alerts to help prevent large-scale victimization before such scams escalate. Conclusion: Staying Ahead of Evolving Digital and Investment Scams The rise of LPG booking scams highlights a larger shift in how fraud operates today, moving beyond traditional formats and embedding itself into everyday consumer journeys. As fraud becomes more contextual, fast-moving, and harder to detect, relying on reactive measures is no longer enough. Addressing this requires continuous monitoring, deeper intelligence, and faster action to identify and disrupt fraud networks before they scale. To stay ahead of evolving scams, start monitoring and taking action before fraud reaches your consumers. Get in touch with our brand protection experts today. FAQs What is an LPG booking scam? An LPG booking scam is a type of digital fraud where scammers impersonate gas service providers using fake websites, phishing links, or messages to trick users into making payments or sharing sensitive information. These scams often appear during high-demand situations or supply concerns. How does an LPG booking scam work? Fraudsters create urgency through fake messages, redirect users to lookalike booking websites, build trust via calls or messages, and then collect payments through UPI or bank transfers. Once the payment is made, they disappear without delivering any service. What is brand
How Fraudsters Bypass MMP Detection
Mobile Measurement Partners (MMPs) have long been the industry’s first line of defence against mobile ad fraud. Through SDK integrations and last-click attribution, they have helped brands track installs and flag suspicious activity based on known patterns such as: Unusual install spikes Abnormal click-to-install times Repetitive device IDs While this works well for obvious fraud, the challenge today is far more sophisticated. Fraudsters now mimic normal user behaviour, making fraudulent traffic look genuine. In many cases, they have effectively reverse-engineered MMP detection logic and learned how to stay within acceptable thresholds. By carefully blending different traffic types in calculated proportions, bad actors are able to pass MMP checks and continue draining campaign budgets unnoticed. This is why the common concern today is clear: MMPs catch obvious fraud but often miss blended fraud. In this blog, we cover: Why MMPs struggle to catch blended traffic How mixed traffic gets a green signal in campaigns How brands can protect themselves beyond basic MMP checks Why MMPs Struggle to Catch Blended Traffic MMPs are designed to detect fraud using known red flags such as unusual click-to-install times, or repetitive user behavior. But today’s fraudsters have become smarter. Instead of sending clearly fake traffic, they mix fraudulent activity with genuine users so that nothing looks suspicious at first glance. This makes the traffic appear legitimate on the MMP dashboard, while budgets continue to get quietly drained in the background. Bot Traffic – Hiding Behind Volume Bots generate large volumes of clicks and fake installs, creating an illusion of strong campaign activity. When this fake traffic is mixed with real users, the overall data starts to look normal. Click and install ratios are high where one click is followed by one install hence time patterns seem balanced, device IDs appear varied, and nothing stands out as an obvious anomaly. Because MMPs are typically built to detect extreme outliers, this blended fraud often slips through unnoticed. Last-Click Attribution – Stealing Credit for Real Installs In fraud tactics like click spamming and click injection, fraudsters either flood the system with fake clicks or place a click just before a real user completes an install. This helps them hijack last-click attribution and steal credit for a conversion that should go to a genuine source. Since the install itself is real, the MMP often treats it as genuine. The fraud happens at the click stage, which many surface-level detection models fail to catch effectively. Incentivised Traffic – Real People, Misleading Results This is one of the hardest forms of fraud to detect because it involves real people. Users are paid or rewarded to install an app, so all the signals look human; real IP addresses, normal device behavior and natural session activity. To an MMP, this traffic appears completely clean. The problem usually becomes visible only later, when retention and engagement suddenly drop after the campaign budget has already been spent. Read in detail about device fraud How the Data Exposes the Evasion, MMPs Cannot Detect The data below highlights findings from a campaign ran between Sept–Oct 2025, where bot traffic was mixed with organic installs, making it difficult for MMPs to separate real activity from fraudulent traffic. Here’s what the data shows: The conversion rate gap is the clearest proof of hidden invalid traffic: The top source, publisher 1, shows conversion rate falling from 0.24% to 0.10% after bot traffic is removed, meaning nearly 58% of the apparent performance was artificial uplift. Massive click volume is creating a false sense of scale: Publisher 8 delivered 816M clicks, but its clean CVR drops to just 0.02%, huge activity on paper, but almost no genuine conversion value. Strong reported CVR can still hide severe bot contamination: Publisher 11 appears to be a top-performing source with 0.63% reported CVR, but once bots are removed it drops to 0.18%, with 72% bot share, indicating invalid traffic driving the most performance. Bot-heavy traffic is not an outlier – it is widespread: 7 out of 10 visible publishers show bot share above 60%, including sources like publisher 5 (68%), publisher 9 (70%), and publisher 10 (70%), despite all of them marked as clean by MMP. Even mid-volume sources show inflated performance: Publisher 7 drops from 0.20% to 0.08% CVR, while 61% of its traffic is bot, showing that inflation is not limited to only the largest traffic sources. The most dangerous fraud isn’t what MMPs catch, it’s what they don’t. Understanding the evasion tactics is the first step to building detection that actually keeps up. How Brands Can Protect Themselves from Mixed Traffic Beyond Basic MMP Checks MMPs should be treated as the first layer, not the only layer. An independent layer of validation through mobile ad fraud solution like mFilterIt’s empowers brands against mixed traffic, catching sophisticated tactics that MMPs miss – Recover stolen conversions through full click-path validation: Move beyond last-click attribution to validate the complete user journey from first touch to install so click hijacking and attribution theft are identified before they drain budgets. Pinpoint fraud sources with publisher-level transparency: Gain granular visibility down to publisher, sub-publisher, placement, and traffic source level to isolate hidden fraud pockets and eliminate waste at the source. Improve acquisition quality by validating real user intent: Go beyond app install counts and measure retention, session depth, registrations, and purchase signals to separate genuine users from low-intent or incentivised traffic. Surface blended fraud early with CVR and traffic anomaly detection: Monitor conversion gaps, abnormal click bursts, and sudden traffic mix shifts to detect bot-driven or manipulated traffic before it impacts performance metrics. Conclusion Blended fraud is changing the way brands need to think about campaign validation. What once appeared as a reliable defence layer is now being challenged by fraud tactics that are far more calculated and harder to spot. This makes it critical for brands to look beyond standard MMP signals and adopt deeper monitoring frameworks like mFilterIt’s Valid8 that can uncover hidden manipulation across clicks, installs, and post-install behaviour. In a high-investment digital ecosystem, protecting media spends is no longer just about catching obvious fraud, it is about identifying the traffic that is intentionally built to look real. FAQs How do fraudsters bypass MMP detection? They mix fake traffic with real user activity, making fraud look genuine and harder for MMPs to detect. Why do MMPs miss blended fraud? Because blended fraud mimics normal user behaviour and stays within acceptable detection thresholds. What are click injection and click spamming? These are fraud tactics that use fake clicks to steal credit for genuine app installs. How can brands detect
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The $1 Billion Wake-Up Call: FTC Compliance Risks in Affiliate Marketing Explained
The Federal Trade Commission (FTC) is one of the most important regulatory bodies in the U.S., playing a critical role in protecting consumers and preserving trust in the marketplace. For brands, it sets the standards for fair advertising, transparent communication, and ethical business practices, helping prevent deceptive marketing and unfair trade conduct. Hence, non-compliance with FTC guidelines does not just slow growth, it directly impacts credibility, customer trust, and long-term business sustainability. Amazon learned this firsthand, paying $1 billion in civil penalties for misleading customers. For brands running affiliate programs in the U.S., this is not a distant cautionary tale, FTC compliance is the current reality, one that has been playing out for years and shows no sign of slowing down. (Source) FTC boundaries are clearly defined and crossing them, even unintentionally, carries serious financial and legal consequences. Affiliate partnerships remain a powerful growth lever, but their scale introduces complexity that is easy to underestimate. Violations rarely announce themselves. They surface as subtle lapses when some partners mislead your organic traffic, avoid ad disclosures, and claim attribution for what was already headed to you. By the time a complaint is raised or enforcement begins, the damage is done. In 2026, compliance cannot be an afterthought. It must be built into how affiliate marketing programs are managed, monitored and scaled from day one. In this blog, we break down: Common FTC compliance risks in affiliate programs Real-world cases of non-compliance The direct business impact of FTC violations How brands can stay compliant without disrupting affiliate-driven growth Common FTC Compliance Risks in Affiliate Marketing FTC compliance requirements are strict, and when marketing practices fall under direct government regulation, violations can become costly. Below are some of the most common FTC compliance risks in affiliate programs that brands must avoid staying aligned with FTC guidelines- Missing or Unclear Disclosure of Affiliate Relationships One of the most common compliance issues in affiliate programs is the lack of disclosure of partner relationships. When influencers or partners promote a brand’s products, they receive an incentive for purchases made through their links. Hence, while promoting, they must clearly disclose this relationship so customers are aware that their purchase will monetarily benefit the partner or influencer. Such disclosures can be made by using #ad or similar tags placed at the beginning or before the fold. Misleading Claims by Influencers & Publishers While promoting your brand, affiliates may make bold claims that don’t align with your brand messaging to drive conversions. For example, a partner might advertise heavy discounts that don’t actually exist, misleading users into visiting the site. In the process, they drop a cookie – so any future purchase by that user gets attributed to them. Similarly, claiming a product is “guaranteed” without any such promise from the brand can mislead customers. In both cases, the affiliate benefits, but the brand is left exposed to compliance violations and legal risk. Unauthorized Bidding on Brand & Restricted Keywords FTC guidelines emphasize that affiliates must not promote a brand in a way that makes users believe they are interacting with the brand’s official website. However, some partners bid on branded keywords and rank above the official site in search results, redirecting organic traffic. This not only misleads users but also forces brands to pay twice for the same traffic, once to acquire it and again as affiliate commission. If left unchecked, it drives up marketing costs and creates clear compliance and brand protection risks. Fake Reviews & Undisclosed Incentivised Ratings Fake reviews are widespread across social media and platforms like Google, often used to artificially build trust and influence purchase decisions. In many cases, these reviews are incentivized users are offered discounts, cashback, or freebies in exchange for posting positive feedback, without any disclosure. For example, a partner may run a campaign asking users to leave a 5-star review for a product in return for a coupon, creating a false perception of quality and popularity. To a potential customer, this appears as genuine validation, when in reality it is manipulated. FTC guidelines strictly prohibit such practices. If affiliates or partners engage in creating or promoting fake or undisclosed incentivized reviews, the brand itself is held accountable, exposing it to regulatory action, financial penalties, and loss of consumer trust. Inaccurate Pricing, Hidden Terms & Misleading Offer Pages Some affiliates promote exaggerated discounts or offers that do not actually exist. Others hide key conditions such as subscription commitments, additional fees, or eligibility restrictions in fine print. These practices create a misleading experience for consumers who click expecting one offer but encounter different terms later. The FTC considers such deceptive advertising practices a violation, especially when important details are not clearly disclosed upfront. Impact of FTC Violations in Affiliate Programs on Brands The impact of non-compliance in affiliate programs is huge, causing brands both financial and reputational damage. Let’s have a look on the direct business impacts a brand faces due to FTC non-compliance – Consumer refunds – Businesses can be required to compensate or refund customers affected by misleading or deceptive promotions. Legal and investigation costs – FTC investigations often involve expensive legal proceedings, internal audits, and compliance reviews. Mandatory compliance programs – Brands may be required to implement stricter monitoring, training, and reporting systems to prevent future violations. Operational restrictions – Regulators may force changes to marketing practices, advertising claims, or affiliate partnerships. Real-World Use Cases of Non-Compliance in FTC Following real-world cases of FTC non-compliance clearly demonstrate the seriousness and enforcement power of these regulations – Amazon Prime Case The Federal Trade Commission imposed one of its largest penalties on Amazon for misleading customers about its Amazon Prime membership. The company agreed to pay $1 billion in civil penalties after it was found that some users were enrolled in Prime without clear consent and faced difficulties when trying to cancel their subscriptions. In addition to the penalty, about $1.5 billion was allocated for refunds to customers who were unintentionally signed up or discouraged from cancelling their memberships. (Source) Fortnite / Epic Games Case The FTC also fined Epic Games, the creator of Fortnite, $520 million for violating children’s privacy and using design tactics that led players to make unintended in-game purchases. According to the FTC, the game’s interface made it easy for users, especially children, to accidentally spend money without clear consent. Along with the financial
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How a Leading OTA Platform Used Real-Time Pricing Intelligence to Prevent Booking Loss and Protect Margins
This case study explores how mFilterIt’s real-time pricing intelligence solution transformed competitive strategy for a major Online Travel Agency (OTA). They were facing critical challenges, including no live competitor price visibility, delayed discount updates, and undetected booking loss. The OTA needed a smarter, data-driven approach. mFilterIt deployed a Data as a Service (DaaS) feed tracking three key pricing layers: base ticket price (SRP), coupon/discount value, and final customer price across 450+ mapped flight sectors. With automated price gap detection and continuous OTA-vs-competitor comparison by airline and route, the platform enabled faster, targeted discount updates, reduced margin leakage, improved price rank awareness, and unlocked strategic price increases during high-demand periods. The result: a shift from reactive to proactive pricing across every sector. DOWNLOAD FULL CASE STUDY (PDF) Submit REQUEST FREE AUDIT
If Your Brand Safety Strategy Is Global-Only, You’re Already Exposed in India
When a media team says, ‘we’re running a pan-India video campaign,’ they’re treating India as a single content environment. But it isn’t. India is a diverse market. Millions of content pieces go live on various video platforms every day. Each operating in a different language, shaped by different cultural norms, with entirely different definitions of what is acceptable, sensitive, or harmful. This is exactly where the risk begins. As an advertiser running programmatic ad campaigns across video platforms, you assume your targeting and exclusions are doing their job. But even as you read this, your ads could be appearing next to content you would never consciously choose to appear beside. A vashikaran tutorial. A graphic crime reconstruction video. Content in a language your brand safety tool cannot read. And the most concerning part? Traditional brand safety tools and platform filters don’t show you this side of reality. To help you identify this gap before it turns into a brand risk, this blog breaks down: What unsafe ad placements actually look like in India’s content ecosystem Why your current brand safety tools are missing them What India-ready brand safety requires What changes for your brand when you get it right Let’s start with what’s actually happening to your ads. What Content Ad Placements Are Your Ads Actually Running Next To? You didn’t choose these ad placements. But your brand is on them. When advertisers try to tap onto wider audiences through ad campaigns, they approve creatives, audiences, and budgets. They almost never see where their ads actually land. Here are the placement categories that brands in India often appear next to, without knowing it. Placement 1: Occult, Black Magic & Superstition Content What is it? Channels dedicated to vashikaran rituals, black magic spells, tantric practices, and superstition-based content. These videos use occult imagery, ritual settings, and fear-based messaging to attract millions of views across regional markets. Why it’s unsafe? These channels are algorithmically treated as general interest content. Platform classifiers read the title and tags, and often miss what the content actually depicts. A brand’s ad plays in the middle of a black magic ritual video, not because anything went wrong technically, but because nothing flagged it. Brand Impact For FMCG, BFSI, or any brand built on consumer trust, appearing next to content that promotes supernatural harm, fear, and occult practice directly contradicts the brand’s credibility. Viewers in these markets don’t separate the ad from the content. If your brand appeared there, it’s perceived as endorsing it. Placement 2: Made for Kids & Cartoon Content What is it? Children’s cartoon channels or animated content, that are classified by platforms as “Made for Kids.” These channels attract massive viewership across markets and are frequently part of broad run-of-network campaigns. Why is it unsuitable? “Made for Kids” content limits ad personalization, meaning your ad is reaching an unintended, non-converting audience. More critically, a brand running campaign for financial products, or adult-oriented services appearing on children’s content creates an immediate brand suitability issue. Brand Impact Every impression served on such content is a direct drain on campaign budget with zero return, no conversion intent, no brand recall, and no audience value. You end up paying for reach that does nothing for your brand. Placement 3: Adult & Sexually Suggestive Content What is it? Adult fashion content or OTT platform trailers that appear as standard video inventory across platforms. These videos carry no explicit adult content warning but contain visually suggestive material such as nudity, intimate couple scenarios, and adult-oriented fashion that platforms routinely monetize as general content. Why it’s unsafe? The problem here is a categorization gap. This content doesn’t meet the threshold for explicit adult content, so it doesn’t get flagged. But it is still considered under a brand-unsafe zone for most advertisers, particularly family-facing categories. Brand Impact When a trusted brand ad appears mid-roll on adult suggestive content, the viewer’s perception shifts immediately. The brand is no longer seen as careful or credible. For brands that spend heavily on trust-building, the reputational cost of a single misplaced impression, when screenshotted and shared, far exceeds the media value of the placement. Placement 4: Regional or Vernacular Content What is it? Regional language videos, in Bengali, Gujarati, and other vernacular languages, that depict weapons and armed violence in dramatized formats or normalize illegal gambling and Satta culture as regional entertainment. Why is it unsafe? Such content never triggers standard brand safety filters. A Bengali crime thriller and a Gujarati Satta video look identical to a global classifier; both are regional language videos with no English tags to read. Traditional brand safety tools cannot identify the content category, the cultural context, or the risk the placement carries. Brand Impact A brand appearing next to a video depicting a man pointing a gun at a woman, or next to content that normalizes illegal gambling, signals a complete lack of campaign oversight. For any brand associated with responsibility and trust, these placements directly undermine the credibility being built through every other brand touchpoint. Why Traditional Brand Safety Tools Miss Seeing Irrelevant or Brand-Unsafe Ad Placements? Here are the reasons why basic brand safety platform filters and tools fail to identify brand unsafe ad placements: Can’t read regional languages Most tools scan video titles and tags to check for unsafe content. If a vashikaran video is titled entirely in Hindi script with no English text, the tool finds nothing to read, marks it as safe, and your ad runs. Loses accuracy in translation Some tools translate regional content into English before checking it. But slang, coded phrases, and culturally loaded words don’t translate accurately. By the time the tool reads it, harmful content looks completely harmless. Moreover, some phrases or words that might appear to be safe in one region can be controversial or unsafe in another. Relies only on metadata, titles, and tags for classification of content Tools that only read titles and descriptions miss what is actually inside the video. A video titled “family entertainment”
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