Fake IDs have been around for decades, but today’s fraudsters aren’t just printing counterfeit driver’s licenses — they’re using artificial intelligence (AI) to create synthetic identities. These AI fake IDs bypass traditional security checks, making it harder for businesses to distinguish real customers from fraudsters. To stay ahead, organizations need to rethink their fraud prevention solutions and invest in advanced tools to stop bad actors before they gain access. The growing threat of AI Fake IDs AI-generated IDs aren’t just a problem for bars and nightclubs; they’re a serious risk across industries. Fraudsters use AI to generate high-quality fake government-issued IDs, complete with real-looking holograms and barcodes. These fake IDs can be used to commit financial fraud, apply for loans or even launder money. Emerging services like OnlyFake are making AI-generated fake IDs accessible. For $15, users can generate realistic government-issued IDs that can bypass identity verification checks, including Know Your Customer (KYC) processes on major cryptocurrency exchanges.1 Who’s at risk? AI-driven identity fraud is a growing problem for: Financial services – Fraudsters use AI-generated IDs to open bank accounts, apply for loans and commit credit card fraud. Without strong identity verification and fraud detection, banks may unknowingly approve fraudulent applications. E-commerce and retail – Fake accounts enable fraudsters to make unauthorized purchases, exploit return policies and commit chargeback fraud. Businesses relying on outdated identity verification methods are especially vulnerable. Healthcare and insurance – Fraudsters use fake identities to access medical services, prescription drugs or insurance benefits, creating both financial and compliance risks. The rise of synthetic ID fraud Fraudsters don’t just stop at creating fake IDs — they take it a step further by combining real and fake information to create entirely new identities. This is known as synthetic ID fraud, a rapidly growing threat in the digital economy. Unlike traditional identity theft, where a criminal steals an existing person’s information, synthetic identity fraud involves fabricating an identity that has no real-world counterpart. This makes detection more difficult, as there’s no individual to report fraudulent activity. Without strong synthetic fraud detection measures in place, businesses may unknowingly approve loans, credit cards or accounts for these fake identities. The deepfake threat AI-powered fraud isn’t limited to generating fake physical IDs. Fraudsters are also using deepfake technology to impersonate real people. With advanced AI, they can create hyper-realistic photos, videos and voice recordings to bypass facial recognition and biometric verification. For businesses relying on ID document scans and video verification, this can be a serious problem. Fraudsters can: Use AI-generated faces to create entirely fake identities that appear legitimate Manipulate real customer videos to pass live identity checks Clone voices to trick call centers and voice authentication systems As deepfake technology improves, businesses need fraud prevention solutions that go beyond traditional ID verification. AI-powered synthetic fraud detection can analyze biometric inconsistencies, detect signs of image manipulation and flag suspicious behavior. How businesses can combat AI fake ID fraud Stopping AI-powered fraud requires more than just traditional ID checks. Businesses need to upgrade their fraud defenses with identity solutions that use multidimensional data, advanced analytics and machine learning to verify identities in real time. Here’s how: Leverage AI-powered fraud detection – The same AI capabilities that fraudsters use can also be used against them. Identity verification systems powered by machine learning can detect anomalies in ID documents, biometrics and user behavior. Implement robust KYC solutions – KYC protocols help businesses verify customer identities more accurately. Enhanced KYC solutions use multi-layered authentication methods to detect fraudulent applications before they’re approved. Adopt real-time fraud prevention solutions – Businesses should invest in fraud prevention solutions that analyze transaction patterns and device intelligence to flag suspicious activity. Strengthen synthetic identity fraud detection – Detecting synthetic identities requires a combination of behavioral analytics, document verification and cross-industry data matching. Advanced synthetic fraud detection tools can help businesses identify and block synthetic identities. Stay ahead of AI fraudsters AI-generated fake IDs and synthetic identities are evolving, but businesses don’t have to be caught off guard. By investing in identity solutions that leverage AI-driven fraud detection, businesses can protect themselves from costly fraud schemes while ensuring a seamless experience for legitimate customers. At Experian, we combine cutting-edge fraud prevention, KYC and authentication solutions to help businesses detect and prevent AI-generated fake ID and synthetic ID fraud before they cause damage. Our advanced analytics, machine learning models and real-time data insights provide the intelligence businesses need to outsmart fraudsters. Learn more *This article includes content created by an AI language model and is intended to provide general information. 1 https://www.404media.co/inside-the-underground-site-where-ai-neural-networks-churns-out-fake-ids-onlyfake/
Fraud rings cause an estimated $5 trillion in financial damages every year, making them one of the most dangerous threats facing today’s businesses. They’re organized, sophisticated and only growing more powerful with the advent of Generative AI (GenAI). Armed with advanced tools and an array of tried-and-true attack strategies, fraud rings have perfected the art of flying under the radar and circumventing traditional fraud detection tools. Their ability to adapt and innovate means they can identify and exploit vulnerabilities in businesses' fraud stacks; if you don’t know how fraud rings work and the right signs to look for, you may not be able to catch a fraud ring attack until it’s too late. What is a fraud ring? A fraud ring is an organized group of cybercriminals who collaborate to execute large-scale, coordinated attacks on one or more targets. These highly sophisticated groups leverage advanced techniques and technologies to breach fraud defenses and exploit vulnerabilities. In the past, they were primarily humans working scripts at scale; but with GenAI they’re increasingly mobilizing highly sophisticated bots as part of (or the entirety of) the attack. Fraud ring attacks are rarely isolated incidents. Typically, these groups will target the same victim multiple times, leveraging insights gained from previous attack attempts to refine and enhance their strategies. This iterative approach enables them to adapt to new controls and increase their impact with each subsequent attack. The impacts of fraud ring attacks far exceed those of an individual fraudster, incurring significant financial losses, interrupting operations and compromising sensitive data. Understanding the keys to spotting fraud rings is crucial for crafting effective defenses to stop them. Uncovering fraud rings There’s no single tell-tale sign of a fraud ring. These groups are too agile and adaptive to be defined by one trait. However, all fraud rings — whether it be an identity fraud ring, coordinated scam effort, or large-scale ATO fraud scheme — share common traits that produce warning signs of imminent attacks. First and foremost, fraud rings are focused on efficiency. They work quickly, aiming to cause as much damage as possible. If the fraud ring’s goal is to open fraudulent accounts, you won’t see a fraud ring member taking their time to input stolen data on an application; instead, they’ll likely copy and paste data from a spreadsheet or rely on fraud bots to execute the task. Typically, the larger the fraud ring attack, the more complex it is. The biggest fraud rings leverage a variety of tools and strategies to keep fraud teams on their heels and bypass traditional fraud defenses. Fraud rings often test strategies before launching a full-scale attack. This can look like a small “probe” preceding a larger attack, or a mass drop-off after fraudsters have gathered the information they needed from their testing phase. Fraud ring detection with behavioral analytics Behavioral analytics in fraud detection uncovers third-party fraud, from large-scale fraud ring operations and sophisticated bot attacks to individualized scams. By analyzing user behavior, organizations can effectively detect and mitigate these threats. With behavioral analytics, businesses have a new layer of fraud ring detection that doesn’t exist elsewhere in their fraud stack. At a crowd level, behavioral analytics reveals spikes in risky behavior, including fraud ring testing probes, that may indicate a forthcoming fraud ring attack, but would typically be hidden by sheer volume or disregarded as normal traffic. Behavioral analytics also identifies the high-efficiency techniques that fraud rings use, including copy/paste or “chunking” behaviors, or the use of advanced fraud bots designed to mimic human behavior. Learn more about our behavioral analytics solutions and their fraud ring detection capabilities. Learn more
With the rise of digital interactions, identity fraud has become an unassuming threat that impacts individuals, businesses, and institutions worldwide. According to the Federal Trade Commission (FTC), 5.4 million consumer reports regarding fraud and consumer protection were filed in 2023. Identity fraud, which is characterized as when an individual's personal information is stolen and used without their consent for fraudulent purposes, has devastating consequences for consumers, including financial losses, damaged credit scores, legal issues, and emotional distress. Financial institutions face damaging consequences beyond financial losses, including reputational damage, operational disruption, and regulatory scrutiny. As technology advances, so do fraudsters' tactics, making it increasingly challenging to detect and prevent identity-related crimes. So, what are financial institutions to do? Industry-leading institutions apply a layered approach to solving fraud that starts with a fraud risk assessment. What is a fraud risk assessment? When opening a new account, banks typically conduct a fraud risk assessment to verify the identity of the individual or entity applying for the account and to assess the likelihood of fraudulent activity. Banks also assess the applicant's credit history, financial background, and transaction patterns to identify red flags or suspicious activity. Advanced fraud detection tools and technologies are employed to monitor account opening activities in real-time and detect signs of fraudulent behavior. This assessment is crucial for ensuring compliance with regulatory requirements, mitigating the risk of financial loss, and safeguarding against identity theft. Understanding the importance of fraud risk assessments A fraud risk assessment is crucial for banks during account opening as it helps verify the identity of applicants and mitigate the risk of fraudulent activity. By assessing the likelihood and potential impact of identity fraud, banks can implement measures to protect customers' assets and protect against losses in their portfolio. Additionally, conducting thorough risk assessments enables banks to comply with regulatory requirements, which mandate the verification of customer identities to prevent money laundering and terrorist financing. By adhering to these regulations and implementing effective fraud detection measures, banks can enhance trust and confidence among customers, regulators, and stakeholders, reinforcing the integrity and stability of the financial system. 10 tools to consider when building an effective fraud risk assessment Several key factors should be carefully considered in an identity fraud risk assessment to ensure thorough evaluation and effective mitigation of identity fraud risks. Financial institutions should consider emerging threats and trends such as synthetic identity fraud, account takeover attacks, and social engineering scams when conducting a risk assessment. By staying abreast of evolving tactics used by fraudsters, organizations can proactively adapt their fraud prevention strategies and controls. Here are 10 tools that can help catch red flags for fraud prevention: Identity verification: Identity verification is the first line of defense against identity theft, account takeover, and other fraudulent activities. By verifying the identities of individuals before granting access to services or accounts, organizations can ensure that only legitimate users are granted access. Effective identity verification methods, such as biometric authentication, document verification, and knowledge-based authentication, help mitigate the risk of unauthorized access and fraudulent transactions. Implementing robust identity verification measures protects organizations from financial losses and reputational damage and enhances trust and confidence among customers and stakeholders. Device intelligence: Device intelligence provides insights into the devices used in online transactions, enabling organizations to identify and mitigate fraudulent activities. Organizations can detect suspicious behavior indicative of fraudulent activity by analyzing device-related data such as IP addresses, geolocation, device fingerprints, and behavioral patterns. Device intelligence allows organizations to differentiate between legitimate users and fraudsters, enabling them to implement appropriate security measures, such as device authentication or transaction monitoring. Phone data: Phone and Mobile Network Operator (MNO) data offers valuable insights into the mobile devices and phone numbers used in transactions. By analyzing MNO data such as subscriber information, call records, and location data, organizations can verify the authenticity of users and detect suspicious activities. MNO data enables organizations to confirm the legitimacy of phone numbers, detect SIM swapping or account takeover attempts, and identify fraudulent transactions. Leveraging MNO data allows organizations to strengthen their fraud prevention measures, enhance customer authentication processes, and effectively mitigate the risk of fraudulent activities in an increasingly mobile-driven environment. Email attributes: Email addresses serve as a primary identifier and communication channel for users in digital transactions. Organizations can authenticate user identities, confirm account ownership, and detect suspicious activities such as phishing attempts or identity theft by verifying email addresses. Analyzing email addresses enables organizations to identify patterns of fraudulent behavior, block unauthorized access attempts, and enhance security measures. Furthermore, email address validation helps prevent fraudulent transactions, safeguard sensitive information, and protect against financial losses and reputational damage. Leveraging email addresses as part of fraud prevention strategies enhances trustworthiness in digital interactions. Address verification: Address verification provides essential information for authenticating user identities and detecting suspicious activities. By verifying addresses, organizations can confirm the legitimacy of user accounts, prevent identity theft, and detect fraudulent transactions. Address validation enables organizations to ensure that the provided address matches the user's identity and reduces the risk of fraudulent activities such as account takeover or shipping fraud. Behavioral analytics: Behavioral analytics enables organizations to detect anomalies and patterns indicative of fraudulent activity. By analyzing user behavior, such as transaction history, navigation patterns, and interaction frequency, organizations can identify deviations from normal behavior and flag suspicious activities for further investigation. Behavioral analytics allows organizations to create profiles of typical user behavior and detect deviations that may signal fraud, such as unusual login times or transaction amounts. Consortia: Consortia facilitate collaboration and information sharing among organizations to combat fraudulent activities collectively. By joining forces through consortia, organizations can leverage shared data, insights, and resources to more effectively identify emerging fraud trends, patterns, and threats. Consortia enables participating organizations to benefit from a broader and more comprehensive view of fraudulent activities, enhancing their ability to detect and prevent fraud. Risk engines: Risk engines enable real-time analysis of transaction data and user behavior to detect and mitigate fraudulent activities. By leveraging advanced algorithms and machine learning techniques, risk engines assess the risk associated with each transaction and user interaction, flagging suspicious activities for further investigation or intervention. Risk engines help organizations identify anomalies, patterns, and trends indicative of fraudulent behavior, allowing for timely detection and prevention of fraud. Additionally, risk engines can adapt and evolve over time to stay ahead of emerging threats, enhancing their effectiveness in mitigating fraud. Orchestration streamlines and coordinates the various components of a fraud detection and prevention strategy. By orchestrating different fraud prevention tools, technologies, and processes, organizations can optimize their efforts to combat fraud effectively. Orchestration allows for seamless integration and automation of workflows, enabling real-time data analysis and rapid response to emerging threats. Step-up authentication: Step-up authentication provides an additional layer of security to verify users' identities during high-risk transactions or suspicious activities. By requiring users to provide additional credentials or undergo further authentication steps, such as biometric verification or one-time passcodes, organizations can mitigate the risk of unauthorized access and fraudulent transactions. Step-up authentication allows organizations to dynamically adjust security measures based on the perceived risk level, ensuring that stronger authentication methods are employed when necessary. By layering these tools effectively businesses remove gaps that fraudsters would typically exploit. Learn more
A tale of synthetic ID fraud Synthetic ID fraud is an increasing issue and affects everyone, including high-profile individuals. A notable case from Ohio involved Warren Hayes, who managed to get an official ID card in the name of “Santa Claus” from the Ohio Bureau of Motor Vehicles. He also registered a vehicle, opened a bank account, and secured an AAA membership under this name, listing his address as 1 Noel Drive, North Pole, USA. This elaborate ruse unraveled after Hayes, disguised as Santa, got into a minor car accident. When the police requested identification, Hayes presented his Santa Claus ID. He was subsequently charged under an Ohio law prohibiting the use of fictitious names. However, the court—presided over by Judge Thomas Gysegem—dismissed the charge, arguing that because Hayes had used the ID for over 20 years, "Santa Claus" was effectively a "real person" in the eyes of the law. The judge’s ruling raised eyebrows and left one glaring question unanswered: how could official documents in such a blatantly fictitious name go undetected for two decades? From Santa Claus to synthetic IDs: the modern-day threat The Hayes case might sound like a holiday comedy, but it highlights a significant issue that organizations face today: synthetic identity fraud. Unlike traditional identity theft, synthetic ID fraud does not rely on stealing an existing identity. Instead, fraudsters combine real and fictitious details to create a new “person.” Think of it as an elaborate game of make-believe, where the stakes are millions of dollars. These synthetic identities can remain under the radar for years, building credit profiles, obtaining loans, and committing large-scale fraud before detection. Just as Hayes tricked the Bureau of Motor Vehicles, fraudsters exploit weak verification processes to pass as legitimate individuals. According to KPMG, synthetic identity fraud bears a staggering $6 billion cost to banks.To perpetrate the crime, malicious actors leverage a combination of real and fake information to fabricate a synthetic identity, also known as a “Frankenstein ID.” The financial industry classifies various types of synthetic identity fraud. Manipulated Synthetics – A real person’s data is modified to create variations of that identity. Frankenstein Synthetics – The data represents a combination of multiple real people. Manufactured Synthetics – The identity is completely synthetic. How organizations can combat synthetic ID fraud A multifaceted approach to detecting synthetic identities that integrates advanced technologies can form the foundation of a sound fraud prevention strategy: Advanced identity verification tools: Use AI-powered tools that cross-check identity attributes across multiple data points to flag inconsistencies. Behavioral analytics: Monitor user behaviors to detect anomalies that may indicate synthetic identities. For instance, a newly created account applying for a large loan with perfect credit is a red flag. Digital identity verification: Implement digital onboarding processes that include online identity verification with real-time document verification. Users can upload government-issued IDs and take selfies to confirm their identity. Collaboration and data sharing: Organizations can share insights about suspected synthetic identities to prevent fraudsters from exploiting gaps between industries. Ongoing employee training: Ensure frontline staff can identify suspicious applications and escalate potential fraud cases. Regulatory support: Governments and regulators can help by standardizing ID issuance processes and requiring more stringent checks. Closing thoughts The tale of Santa Claus’ stolen identity may be entertaining, but it underscores the need for vigilance against synthetic ID fraud. As we move into an increasingly digital age, organizations must stay ahead of fraudsters by leveraging technology, training, and collaboration. Because while the idea of Spiderman or Catwoman walking into your branch may seem amusing, the financial and reputational cost of synthetic ID fraud is no laughing matter. Learn more
The digital domain is rife with opportunities, but it also brings substantial risks, especially for organizations. Among the innovative tools that have risen to prominence for fraud detection and online security is browser fingerprinting. Whether you're looking to minimize security gaps or bolster your fraud prevention strategy, understanding how this technology works can provide a significant advantage in today’s ever-evolving fraud and identity landscape. This article explores the concept, functionality, and applications of browser fingerprinting while also examining its benefits and relevance for organizations. How does browser fingerprinting work? Browser fingerprinting is a powerful technology designed to collect unique identifying information about a user’s web browser and device. By compiling data points such as browser type, operating system, time zone, and installed plugins, browser fingerprinting creates a distinct profile — or "fingerprint"— that allows websites to recognize returning users without relying on cookies. Here’s a breakdown of its key steps: Data collection: When a user visits a website, their browser sends information, such as user-agent strings or metadata, to the website's servers. This data provides insights about their browser, device, and system. Fingerprint creation: The collected information is processed to generate a unique ID or fingerprint, representing the user's specific configuration. Tracking and analyzing: These fingerprints enable websites to track and analyze user behavior, detect anomalies, and identify users without relying on traditional tracking mechanisms like cookies. For organizations, employing technology that leverages such fingerprints adds an additional layer to identity verification, detecting discrepancies that may indicate fraud attempts. What are the different techniques? Not all browser fingerprinting methods are identical; varying approaches offer different strengths. The most common techniques used today include: Canvas fingerprinting: This method utilizes the "Canvas" element in HTML5. When a website sends a command to draw a hidden image on a user's device, the way the image is rendered reveals unique characteristics about the device's graphics hardware and software. Font fingerprinting: Font fingerprinting involves analyzing the fonts installed on a user's system. Since computers and browsers render text in slightly different ways based on their configurations, the resulting variations aid in identifying users. Plugin enumeration: Browsers and devices often come equipped with plugins or extensions like Flash or Java. Analyzing which plugins are installed, their versions, and their order helps websites build unique fingerprints. What are the benefits of browser fingerprinting? For organizations, browser fingerprinting is not just a technical marvel — it’s a strategic asset. Benefits include: Enhanced fraud detection: Browser fingerprinting detects inconsistencies within user accounts, flagging unauthorized logins, synthetic identity fraud, or account takeover fraud without introducing significant friction for legitimate users. By identifying patterns that deviate from the norm, organizations can better prepare for malicious activities. Learn more about addressing account takeover fraud. Supports multi-layered security: A single security measure often isn't enough to combat advanced fraudulent schemes. Browser fingerprinting pairs seamlessly with other fraud management tools, such as behavioral analytics and risk-based authentication, to provide robust security. See how behavioral analytics can help organizations spot and stop next-generation fraud bots. Seamless user experience: Unlike cookies or authentication codes, browser fingerprinting operates passively in the background. Users remain unaware of the process, ensuring their experience is unaffected while still maintaining security. Level up with Experian's fraud prevention tools Browser fingerprinting offers organizations a game-changing tool to secure online interactions. However, given the growing complexity of fraud threats, organizations will need additional layers of insights and protection. Experian offers integrated, AI-driven fraud prevention solutions tailor-made to tackle challenges in the digital space. By leveraging advanced technologies like browser fingerprinting alongside Experian’s solutions, organizations can safeguard their operations and uphold customer trust while maintaining a frictionless user experience. Learn more about our fraud prevention solutions This article includes content created by an AI language model and is intended to provide general information.
In this article...Understanding the scope of fintech fraudThe importance of fintech fraud preventionSynthetic identity (ID) fraud: A growing threatHow fintech fraud detection and prevention are evolvingGet started today The integration of technology with traditional financial services has unlocked unprecedented convenience and opportunities for consumers and businesses alike. However, this digital shift has opened the door for more sophisticated fraud tactics. With fraudsters continuously refining their methods, fintech companies must invest in advanced fintech fraud detection and prevention solutions. Understanding the scope of fintech fraud As fintech platforms expand, they also attract the attention of cybercriminals. The accessibility of digital financial services can create vulnerabilities that fraudsters exploit, executing everything from personal account takeovers to larger-scale breaches involving synthetic identities. Source: Experian’s 2024 U.S. Identity & Fraud Report To counter these threats, fintech companies must deploy innovative fraud management solutions powered by artificial intelligence (AI), machine learning (ML), and advanced analytics. Unlike traditional methods that often rely on static rules and manual reviews, these solutions can process vast amounts of data, learn from historical patterns, and detect anomalies in real-time. This allows organizations to identify suspicious activities before they lead to significant losses. The importance of fintech fraud prevention While detecting fraud is crucial, preventing it from occurring in the first place is even more important. Fraud prevention solutions aim to create robust systems that stop fraudsters in their tracks before they can cause damage. With the rise of digital financial services, the need for proactive fraud prevention measures has never been greater. These solutions protect both consumers and businesses from financial harm, reducing the risk of financial loss and reputational damage. Advanced fraud prevention solutions employ multi-layered strategies, combining AI-driven fraud detection tools with methods such as multifactor authentication and biometric identity verification. These tools create an extra layer of security, making it difficult for fraudsters to access sensitive data or execute fraudulent transactions. Experian’s fraud prevention solutions offer businesses a comprehensive suite of tools designed to prevent various types of fraud. From real-time transaction monitoring to sophisticated user authentication methods, these solutions provide the protection businesses need to stay ahead of evolving fraud tactics. Synthetic identity (ID) fraud: A growing threat One of the most concerning forms of fraud that fintech companies face is synthetic ID fraud. This type of fraud involves the creation of a fake identity using a combination of real and fabricated information. Fraudsters often steal pieces of personal data—such as Social Security numbers or addresses—and then combine them with fictional information to create a new, synthetic identity. These synthetic identities can be used to open bank accounts, apply for credit cards, or take out loans, leaving businesses and consumers vulnerable to significant financial losses. Synthetic ID fraud is particularly difficult to detect because the synthetic identity often looks legitimate to traditional verification systems. As a result, fintech companies must deploy sophisticated fraud detection systems that can identify synthetic identities before they’re used to commit fraud. Machine learning algorithms, for instance, can analyze behavioral data, detecting discrepancies that may indicate a synthetic identity. Experian is ranked #1 by the Center for Financial Professionals (CeFPro®) for Identity and Fraud. The ranking appeared in CeFPro’s Fintech Leaders Report, a comprehensive annual study of the fintech industry. How fintech fraud detection and prevention are evolving As fraudsters continue to evolve their tactics, fintech companies must remain one step ahead by investing in cutting-edge fraud detection and prevention technologies. Real-time monitoring, predictive analytics, and biometrics are just a few of the technologies shaping the future of fraud detection. By integrating these technologies into their fraud management processes, fintech companies can offer a more secure and seamless experience for their users. With the acquisition of NeuroID, an industry leader in behavioral analytics, Experian has amplified its fraud risk suite by providing a new layer of insight into digital behavioral signals and analytics. Available through our fraud solutions on the Experian Ascend Technology PlatformTM, clients can proactively monitor and analyze a user’s real-time digital behavior, allowing them to confidently navigate the online landscape and provide frictionless customer experiences. Get started today As the fraud landscape continues to evolve, fintech companies must adopt comprehensive solutions to stay ahead of emerging threats. By doing so, they can protect themselves and their customers, ensuring the continued success of digital financial services in the years to come. To learn more, check out our fraud management and fintech solutions. Fraud management solutions Fintech solutions This article includes content created by an AI language model and is intended to provide general information. In this article...
Experian’s ninth annual report on identity and fraud highlights persistent worries among consumers and businesses about fraud, including growing threats from GenAI. In this report, we explore how the evolving fraud landscape is impacting identity verification, customer experience, and business priorities for the future. Our 2024 U.S. Identity and Fraud Report draws insights from surveys of over 2,000 U.S. consumers and 200 businesses. This year’s report dives into: Evolving consumer sentiment over security and experience Businesses’ investments to tackle growing fraud challenges Effective technology solutions to accurately identify and authenticate consumers The impact of GenAI on the fraud landscape To keep pace with the evolving landscape, businesses will need to apply a multi-faceted strategy that leverages multiple types of recognition and security to stop all types of fraud while allowing real customers through. To learn more about our findings and perspective, read the full 2024 U.S. Identity and Fraud Report, watch our on-demand webinar, or read the press release. Download Now Watch Webinar Read Press Release
Gen Z, or "Zoomers," born from 1997 to 2012, are molded by modern transformations. They have witnessed events from post-9/11 impacts to the rise of the internet and the COVID-19 crisis. As early adopters of technology, their lives are intertwined with smartphones, online shopping, social platforms, cloud services, emerging fintech, and artificial intelligence. They are called “digital natives” as they are the first generation to grow up with internet as part of their daily life. Research generally indicates that this post-millennial generation values practicality, favoring financial stability over entrepreneurial pursuits. They appreciate communication tailored to them and often employ social media to cultivate their personal brands. As a generation growing up immersed in technology, they tend to choose digital interactions, seeking to forge robust, secure, genuine, and unconstrained digital experiences. The challenge of identity verification Identity verification presents a considerable challenge for Generation Z. According to a Fortune survey, close to 50% of this demographic regrets not opening financial accounts earlier, citing a lack of readiness to join the financial ecosystem by the age of 18. Consequently, this has given rise to "digital ghosts"—people with minimal or nonexistent financial histories who face challenges when trying to utilize financial services. The 2009 Credit Card Accountability Responsibility and Disclosure Act mandates that individuals under 21 need a cosigner or show income proof to get a credit card, hindering their early financial involvement. Moreover, conventional identity checks are becoming less reliable due to the surge in identity theft. Innovative solutions for verifying Gen Z Verifying identities and preventing fraud among Gen Z presents unique challenges due to their digital-native status and limited credit histories. Here are some effective strategies and approaches that financial institutions can adopt to address these challenges: Leveraging alternative data sources Academic records leverage information from higher learning institutions such as universities, colleges, and vocational schools. This data can be vital for authenticating the identities of younger individuals who may lack a substantial credit history. Employment verification retrieve data confirming the identity and employment status, especially focusing on Gen Z who are new to the job market. Utility and telecom records leverage payment histories for utilities, phone bills, and other recurring services, which can provide additional layers of identity verification. Alternative financial data includes online small dollar lenders, online installment lenders, single payment, line of credit, storefront small dollar lenders, auto title and rent-to-own. Phone-Centric ID Phone-Centric Identity refers to technology that leverages and analyzes mobile, telecom, and other signals for the purposes of identity verification, identity authentication, and fraud prevention. Phone-Centric Identity relies on billions of signals from authoritative sources pulled in real time, making it a powerful proxy for digital identity and trust. Advance authentication technologies Behavioral biometrics analyze user behaviors such as typing patterns, navigation habits, and device usage. These subtle behaviors can help create a unique profile for each user, making it difficult for fraudsters to impersonate them. Adaptive risk-based authentication that adjusts the level of security based on the user's behavior, location, device, and other factors. For example, a higher level of verification might be required for transactions that are deemed unusual or high-risk. Real-time fraud detection AI and machine learning: Deploy AI and machine learning algorithms to analyze transaction patterns and detect anomalies in real-time. These technologies can identify suspicious activities and flag potential fraud. Fraud analytics: Use predictive analytics to assess the likelihood of fraud based on historical data and current behavior. This approach helps in proactively identifying and mitigating fraudulent activities. Secure digital onboarding Digital identity verification: Implement digital onboarding processes that include online identity verification with real-time document verification. Users can upload government-issued IDs and take selfies to confirm their identity. Video KYC (Know Your Customer): Use video calls to conduct KYC processes, allowing bank representatives to verify identities and documents remotely via automated identity verification. This method is secure and convenient for tech-savvy Gen Z customers. Make identity verification easy To authenticate identities and combat fraud within the Gen Z population, financial organizations need to implement a comprehensive strategy utilizing innovative technologies, non-traditional data, and strong protective protocols. Such actions will enable the creation of a trustworthy and frictionless banking environment that appeals to a generation adept in digital interactions, thereby establishing trust and encouraging enduring connections. To learn more about Experian’s automated identity verification solutions, visit our website. Learn more
With more consumers online, bad actors are taking the opportunity to commit more financial crimes, such as account takeover fraud. This online scheme resulted in nearly $13 billion in losses in 2023, up from $11 billion in 2022.1 So, what do organizations need to know about this form of identity theft? And how can they prevent it? Let’s explore one type of account takeover fraud: email account takeover. What is email account takeover? Email account takeover occurs when a fraudster gains access to a legitimate user’s email account through data breaches that expose credentials, purchasing from the dark web, or phishing scams. It's usually one of the first steps in a broader account takeover scheme. Once fraudsters have access to a consumer’s email or social media account, they have access to the private information in that consumer’s inbox: financial statements, health records, and other forms of PII. Fraudsters can also now use the consumer’s email to impersonate them with friends, family, financial institutions or other businesses they interact with. They can also gain access to other accounts and here’s where email account takeover becomes more dangerous. In this attack, the fraudster gains access to an email or mobile account. Once they have an email, they start by trying to guess the user’s password, commonly called a brute force attack, or through password spraying, where they use commonly used passwords, i.e. ‘password’ or ‘123123. A recent Google survey found that 65% of people use the same password for some or all of their online accounts. This, along with a corresponding email address can give fraudsters further entre into a consumer’s other accounts. If unsuccessful, they’ll then execute a ‘forgot password’, password reset, or one-time password. Then, they take over the victim’s account with their financial institution to facilitate the transfer of funds from the compromised account. 57% of businesses are experiencing rising fraud losses associated with account opening and account takeover.2 While email account takeover can be quickly executed, detecting it can take time. Unlike credit card fraud, where an individual may soon notice suspicious activity, an email account takeover can go undetected for longer. The owner may not realize until later that their account has been compromised, especially with a dormant account or secondary account they use less. As a result, criminals have more time to facilitate additional attacks. LEARN MORE: Explore 2024 fraud trends listed by Experian. How does it affect your organization? Account takeover fraud doesn't just impact consumers, it can result in significant financial losses for organizations. For example, if your organization offers credit products, you might have to cover the costs of disputing chargebacks, card processing fees, or providing refunds. In the case of a data breach, you may have to pay fines against your organization for not properly protecting consumer information. Nearly two-thirds of consumers say they’re very or somewhat concerned with online security.3 But email account takeover isn't just costly — it can damage your organization's reputation. Consumers expect organizations to have proper security measures in place to protect their information. If a data breach occurs, your security can seem weak, leading consumers to lose trust in your organization. As a result, they may potentially take their business elsewhere. The importance of prevention While consumers listed identity theft as their top concern when conducting activities online, they’re still interacting, opening new accounts, and transacting digitally.4 Coupled with the rise of account takeover fraud and associated losses, it’s more crucial than ever for organizations to accurately detect and prevent these attacks. To do this, they must have a proactive fraud prevention strategy in place. Account takeover fraud prevention requires your business to maintain and continuously reaffirm confidence in the identity data you collect. Your team can monitor, segment, and proactively act on customer identities that display a higher risk of fraud than was determined at account origination through risk-based fraud detection models, machine learning, and advanced analytics. Experian offers many flexible solutions, including: CrossCore® Solutions are best practice-based groupings of fraud and identity products that enable organizations to solve common to complex issues. For example, our fraud risk solutions include email and phone intelligence to improve verification for thin-files and other challenging populations. Experian offers phone/carrier-based matching capabilities with address validity and occupancy data for >95% of U.S. households. FraudNet is a device intelligence solution that analyzes hundreds of device attributes and prevents fraud on all digital channels. Combining contextual data, behavioral data, and device data, it bridges the gap between physical and digital identity to achieve fraud capture rates that exceed industry averages. To further alleviate account takeover fraud, your organization can offer educational resources for fraud prevention. Using various, strong passwords across their accounts, and changing them regularly, is a foundational way consumers can help ensure their accounts are secure. Leveraging user names that are different from your email can also help. If a fraudster is able to takeover an account and initiate a lost password request, and that password is used for other accounts, that fraudster now has the credentials they need to further defraud that consumer. By spreading awareness about identity fraud risks and providing best practices for prevention, you can better protect your organization and consumers. LEARN MORE: Building a multilayered fraud and identity strategy with CrossCore Solutions Partnering with Experian Email account takeover, along with other types of fraud, can be detected and prevented with the right partner. Experian’s fraud management solutions can help your organization accurately verify customers and assess risk with our account takeover and fraud management solutions. Explore Experian’s account takeover solutions and watch an on-demand recording of our Fraud Risk and Identity Verification Solutions tech showcase. Learn more Watch tech showcase 1 Identity Fraud Cost Americans $43 Billion in 2023, AARP. 2-4 2023 U.S. Identity and Fraud Report, Experian.
Ensuring the reliability of tenant applications is paramount to running a successful property management business. But with an exponential rise in prospective residents using fake financial documents to inflate income and employment status, how do property managers navigate and detect fake paystubs without stepping on a landmine of liability? The marketplace of deception Paystub generator websites As you embrace the commitment to diligence, be aware that some legitimate websites can be unknowingly used by fraudsters to create counterfeit financial documents. Knowledge is your ally here. At the touch of a button, even the minimally tech inclined can produce pay stubs that appear convincing. There are dozens of sites that offer paystub generator software, including: Design and editing software websites that are accessible to people beyond just creative professionals. Popular e-commerce platform stores that host apps capable of creating paystubs. Mobile app stores that allow users to download apps for use on all major mobile devices. Key indicators of a fake paystub Remember, as a property manager or owner, you are responsible for scrutinizing these documents to protect your business interests. Use your awareness to be vigilant, verifying every piece of information to ensure the credibility of prospective tenants. While some of these falsified paystubs may appear to be legitimate, they are usually not perfect. Here are some quick checks which may help you spot a fake or trigger a deeper review quickly. Watch out for elusive typos Erroneous spelling, particularly in company names and financial terms, is a big red flag. Keep your eyes peeled for these unruly characters. Distorted watermarks A legitimate paystub should carry official watermarks or specific symbols that indicate its authenticity. However, be on the lookout for watermarks that seem off — sometimes, they're too conspicuous or amateurish, which can be a tell-tale sign of forgery. Authentic watermarks should be subtle and consistent with the company's brand. Crunching the numbers Inaccurate calculations can unravel a fake paystub. If the numbers just don't add up or pay dates vary inexplicably, you should investigate further. Inconsistent font Professional payroll systems stick to a consistent font. If you notice various font styles and sizes, it's worth investigating further. Authenticity lies in uniformity. Going logo-less? A missing company logo, or one that looks like it was copied from a low-resolution image on the internet, should trigger suspicion. Unusual tax deductions Abnormal tax deductions could indicate someone's fiddling with the figures. Brush up on your tax knowledge or consult with an expert if something seems off-the-wall. Final food for thought Remember, having the right knowledge and tools empowers you to make informed decisions, safeguarding your property from potential fraudsters. Be diligent, stay informed, and leverage technology to support your processes. Action steps to take today Educate your team: Make sure everyone involved in the application review process knows what to look for. Develop a standard operating procedure: Update your existing (or develop) Standard Operating Procedures: As new ways of gaming the system arise, make sure your particular procedures are keeping up with the times. For example, include steps for the following: Understand tenant screening laws in your area. Create consistent resident screening criteria. Check credit report and background. Verify employment and income. Review rental history and evictions (if any). Check criminal record with multi-state search. Interview residents before signing a lease. Follow a consistent policy when accepting or rejecting applicants. Embrace technology: Income and employment verification solutions can verify income directly from a trusted data source and avoid the paystub predicament altogether. Consider implementing a verification system that leaves no room for guesswork. Our verification solution, Experian VerifyTM, provides accurate, efficient, and compliant income and employment verification services. With Experian Verify, property managers can navigate the complexities of tenant-related income and employment verification with ease, ensuring they are adhering to Fair Housing laws and detecting fraudulent behavior. To learn more about how Experian Verify can benefit your property business, please contact us and visit us online. Learn more
In the ever-expanding financial crime landscape, envision the most recent perpetrator targeting your organization. Did you catch them? Could you recover the stolen funds? Now, picture that same individual attempting to replicate their scheme at another establishment, only to be thwarted by an advanced system flagging their activity. The reason? Both companies are part of an anti-fraud data consortium, safeguarding financial institutions (FIs) from recurring fraud. In the relentless battle against fraud and financial crime, FIs find themselves at a significant disadvantage due to stringent regulations governing their operations. Criminals, however, operate without boundaries, collaborating across jurisdictions and international borders. Recognizing the need to level the playing field, FIs are increasingly turning to collaborative solutions, such as participation in fraud consortiums, to enhance their anti-fraud and Anti-Money Laundering (AML) efforts. Understanding consortium data for fraud prevention A fraud consortium is a strategic alliance of financial institutions and service providers united in the common goal of comprehensively understanding and combatting fraud. As online transactions surge, so does the risk of fraudulent activities. However, according to Experian’s 2023 U.S. Identity and Fraud Report, 55% of U.S. consumers reported setting up a new account in the last six months despite concerns around fraud and online security. The highest account openings were reported for streaming services (43%), social media sites and applications (40%), and payment system providers (39%). Organizations grappling with fraud turn to consortium data as a robust defense mechanism against evolving fraud strategies. Consortium data for fraud prevention involves sharing transaction data and information among a coalition of similar businesses. This collaborative approach empowers companies with enhanced data analytics and insights, bolstering their ability to combat fraudulent activities effectively. The logic is simple: the more transaction data available for analysis by artificial-intelligence-powered systems, the more adept they become at detecting and preventing fraud by identifying patterns and anomalies. Advantages of data consortiums for fraud and AML teams Participation in an anti-fraud data consortium provides numerous advantages for a financial institution's risk management team. Key benefits include: Case management resolution: Members can exchange detailed case studies, sharing insights on how they responded to specific suspicious activities and financial crime incidents. This collaborative approach facilitates the development of best practices for incident handling. Perpetrator IDs: Identifying repeat offenders becomes more efficient as consortium members share data on suspicious activities. Recognizing patterns in names, addresses, device fingerprints, and other identifiers enables proactive prevention of financial crimes. Fraud trends: Consortium members can collectively analyze and share data on the frequency of various fraud attempts, allowing for the calibration of anti-fraud systems to effectively combat prevalent types of fraud. Regulatory changes: Staying ahead of evolving financial regulations is critical. Consortiums enable FIs to promptly share updates on regulatory changes, ensuring quick modifications to anti-fraud/AML systems for ongoing compliance. Who should join a fraud consortium? A fraud consortium can benefit any organization that faces fraud risks and challenges, especially in the financial industry. However, some organizations may benefit more, depending on their size, type, and fraud exposure. Some of the organizations that should consider joining a fraud consortium are: Financial institutions: Banks, credit unions, and other financial institutions are prime targets for fraudsters, who use various methods such as identity theft, account takeover, card fraud, wire fraud, and loan fraud to steal money and information from them. Fintech companies: Fintech companies are innovative and disruptive players in the financial industry, who offer new and alternative products and services such as digital payments, peer-to-peer lending, crowdfunding, and robot-advisors. Online merchants: Online merchants are vulnerable to fraudsters, who use various methods such as card-not-present fraud, friendly fraud, and chargeback fraud to exploit their online transactions and payment systems. Why partner with Experian? What companies need is a consortium that allows FIs to collaboratively research anti-fraud and AML information, eliminating the need for redundant individual efforts. This approach promotes tighter standardization of anti-crime procedures, expedited deployment of effective anti-fraud/AML solutions, and a proactive focus on preventing financial crime rather than reacting to its aftermath. Experian Hunter is a sophisticated global application fraud and risk management solution. It leverages detection rules to screen incoming application data for identifying and preventing fraudulent activities. It matches incoming application data against multiple internal and external data sources, shared fraud databases and dedicated watch lists. It uses client-flexible matching rules to crossmatch data sources for highlighting data anomalies and velocity attempts. In addition, it looks for connections to previous suspected and known fraudulent applications. Hunter generates a fraud score to indicate a fraud risk level used to prioritize referrals. Suspicious applications are moved into the case management tool for further investigation. Overall, Hunter prevents application fraud by highlighting suspicious applications, allowing you to investigate and prevent fraud without inconveniencing genuine customers. To learn more about our fraud management solutions, visit us online or request a call. Learn more This article includes content created by an AI language model and is intended to provide general information.
Finding a reliable, customer-friendly way to protect your business against new account fraud is vital to surviving in today's digital-driven economy. Not only can ignoring the problem cause you to lose valuable money and client goodwill, but implementing the wrong solutions can lead to onboarding issues that drive away potential customers. The Experian® 2023 Identity and Fraud Report revealed that nearly 70 percent of businesses reported fraud loss in recent years, with many of these involving new account fraud. At the same time, problems with onboarding caused 37 percent of consumers to drop off and take their business elsewhere. In other words, your customers want protection, but they aren't willing to compromise their digital experience to get it. You need to find a way to meet both these needs when combating new account fraud. What is new account fraud? New account fraud occurs any time a bad actor creates an account in your system utilizing a fake or stolen identity. This process is referred to by different names, such as account takeover fraud, account creation fraud, or account opening fraud. Examples of some of the more common types of new account fraud include: Synthetic identity (ID) fraud: This type of fraud occurs when the scammer uses a real, stolen credential combined with fake credentials. For example, they might use someone's real Social Security number combined with a fake email. Identity theft: In this case, the fraudster uses personal information they stole to create a new scam account. Fake identity: With this type of fraud, scammers create an account with wholly fake credentials that haven't been stolen from any particular person. New account fraud may target individuals, but the repercussions spill over to impact entire organizations. In fact, many scammers utilize bots to attempt to steal information or create fake accounts en masse, upping the stakes even more. How does new account fraud work? New account fraud begins at a single weak security point, such as: Data breaches: The Bureau of Justice reported that in 2021 alone, 12 percent of people ages 16 or older received notifications that their personal information was involved in a data breach.1 Phishing scams: The fraudster creates an email or social media account that pretends to be from a legitimate organization or person to gain confidential information.2 Skimmers: These are put on ATMs or fuel pumps to steal credit or debit card information.2 Bot scrapers: These tools scrape information posted publicly on social media or on websites.2 Synthetic ID fraud: 80 percent of new account fraud is linked to synthetic ID fraud.3 The scammer just needs one piece of legitimate information. If they have a real Social Security number, they might combine it with a fake name and birth date (or vice versa.) After the information is stolen, the rest of the fraud takes place in steps. The fake or stolen identity might first be used to open a new account, like a credit card or a demand deposit account. Over time, the account establishes a credit history until it can be used for higher-value targets, like loans and bank withdrawals. How can organizations prevent new account fraud? Some traditional methods used to combat new account fraud include: Completely Automated Public Turing Tests (CAPTCHAs): These tests help reduce bot attacks that lead to data breaches and ensure that individuals logging into your system are actual people. Multifactor authentication (MFA): MFA bolsters users' password protection and helps guard against account takeover. If a scammer tries to take over an account, they won't be able to complete the process. Password protection: Robust password managers can help ensure that one stolen password doesn't lead to multiple breaches. Knowledge-based authentication: Knowledge-based authentication can be combined with MFA solutions, providing an additional layer of identity verification. Know-your-customer (KYC) solutions: Businesses may utilize KYC to verify customers via government IDs, background checks, ongoing monitoring, and the like. Additional protective measures may involve more robust identity verification behind the scenes. Examples include biometric verification, government ID authentication, public records analysis, and more. Unfortunately, these traditional protective measures may not be enough, for many reasons: New account fraud is frequently being perpetrated by bots, which can be tougher to keep up with and might overwhelm systems. Institutions might use multiple security solutions that aren't built to work together, leading to overlap and inefficiency. Security measures may create so much friction in the account creation process that potential new customers are turned away. How we can help Experian's fraud management services provide a multi-layered approach that lets businesses customize solutions to their particular needs. Advanced machine learning analytics utilizes extensive, proprietary data to provide a unique experience that not only protects your company, but it also protects your customers' experience. Customer identification program (CIP) Experian's KYC solutions allow you to confidently identify your customers via a low-friction experience. The tools start with onboarding, but continue throughout the customer journey, including portfolio management. The tools also help your company comply with relevant KYC regulations. Cross-industry analysis of identity behavior Experian has created an identity graph that aggregates consumer information in a way that gives companies access to a cross-industry view of identity behavior as it changes over time. This means that when a new account is opened, your company can determine behind the scenes if any part of the identity is connected to instances of fraud or presents actions not normally associated with the customer's identity. It's essentially a new paradigm that works faster behind the scenes and is part of Experian's Ascend Fraud Platform™. Multifactor authentication solutions Experian's MFA solutions utilize low-friction techniques like two-factor authentication, knowledge-based authentication, and unique one-time password authentication during remote transactions to guard against hacking. Synthetic ID fraud protection Experian's fraud management solutions include robust protection against synthetic ID fraud. Our groundbreaking technology detects and predicts synthetic identities throughout the customer lifecycle, utilizing advanced analytics capabilities. CrossCore® CrossCore combines risk-based authentication, identity proofing, and fraud detection into one cloud platform, allowing for real-time decisions to be made with flexible decisioning workflows and advanced analytics. Interactive infographic: Building a multilayered fraud and identity strategy Precise ID® The Precise ID platform lets customers choose the combination of fraud analytics, identification verification, and workflows that best meet their business needs. This includes machine-learned fraud risk models, robust consumer data assets, one-time passwords (OTPs), knowledge-based authentication (KBAs), and powerful insights via the Identity Element Network®. Account takeover fraud represents a significant threat to your business that you can't ignore. But with Experian's broad range of solutions, you can keep your systems secure while not sacrificing customer experience. Experian can keep your business secure from new account fraud Experian's innovative approach can streamline your new account fraud protection. Learn more about how our fraud management solutions can help you. Learn more References 1. Harrell, Erika. "Just the Stats: Data Breach Notifications and Identity Theft, 2021." Bureau of Justice Statistics, January 2024. https://bjs.ojp.gov/data-breach-notifications-and-identity-theft-2021 2. "Identity Theft." USA.gov, December 6, 2023. https://www.usa.gov/identity-theft 3. Purcell, Michael. "Synthetic Identity Fraud: What is It and How to Combat It." Thomson Reuters, April 28, 2023. https://legal.thomsonreuters.com/blog/synthetic-identity-fraud-what-is-it-and-how-to-combat-it/
While bots have many helpful purposes, they have unfortunately become a tool for malicious actors to gain fraudulent access to financial accounts, personal information and even company-wide systems. Almost every business that has an online presence will have to face and counter bot attacks. In fact, a recent study found that across the internet on a global scale, malicious bots account for 30 percent of automated internet activity.1 And these bots are becoming more sophisticated and harder to detect. What is a bot attack and bot fraud? Bots are automated software applications that carry out repetitive instructions mimicking human behavior.2 They can be either malicious or helpful, depending on their code. For example, they might be used by companies to collect data analytics, scan websites to help you find the best discounts or chat with website visitors. These "good" bots help companies run more efficiently, freeing up employee resources. But on the flip side, if used maliciously, bots can commit attacks and fraudulent acts on an automated basis. These might even go undetected until significant damage is done. Common types of bot attacks and frauds that you might encounter include: Spam bots and malware bots: Spam bots come in all shapes and sizes. Some might scrape email addresses to entice recipients into clicking on a phishing email. Others operate on social media sites. They might create fake Facebook celebrity profiles to entice people to click on phishing links. Sometimes entire bot "farms" will even interact with each other to make a topic or page appear more legitimate. Often, these spam bots work in conjunction with malware bots that trick people into downloading malicious files so they can gain access to their systems. They may distribute viruses, ransomware, spyware or other malicious files. Content scraping bots: These bots automatically scrape content from websites. They might do so to steal contact information or product details or scrape entire articles so they can post duplicate stories on spam websites. DDoS bots and click fraud bots: Distributed denial of service (DDoS) bots interact with a target website or application in such large numbers that the target can't handle all the traffic and is overwhelmed. A similar approach involves using bots to click on ads or sponsored links thousands of times, draining advertisers' budgets. Credential stealing bots: These bots use stolen usernames and passwords to try to log into accounts and steal personal and financial information. Other bots may try brute force password cracking to find one combination that works so they can gain unauthorized access to the account. Once the bot learns consumer’s legitimate username and password combination on one website, they can oftentimes use it to perform account takeovers on other websites. In fact, 15 percent of all login attempts across industries in 2022 were account takeover attacks.1 AI-generated bots: While AI, like ChatGPT, is vastly improving the technological landscape, it's also providing a new avenue for bots.3 AI can create audio and videos that appear so real that people might think they're a celebrity seeking funds. What are the impacts of bot attacks? Bot attacks and bot fraud can have a significant negative impact, both at an individual user level and a company level. Individuals might lose money if they're tricked into sending money to a fake account, or they might click on a phishing link and unwittingly give a malicious actor access to their accounts. On a company level, the impact of a bot attack can be even more widespread. Sensitive customer data might get exposed if the company falls victim to a malware attack. This can open the door for the creation of fake accounts that drain a company's money. For example, a phishing email might lead to demand deposit account (DDA) fraud, where a scammer opens a fraudulent account in a customer's name and then links it to new accounts, like new lines of credit. Malware attacks can also cause clients to lose trust in the company and take their business elsewhere.A DDoS attack can take down an entire website or application, leading to a loss of clients and money. A bot that attacks APIs can exploit design flaws to steal sensitive data. In some cases, ransomware attacks can take over entire systems and render them unusable. How can you stop bot attacks? With so much at risk, stopping bot attacks is vital. But some of the most typical defenses have core flaws. Common methods for stopping bot attacks include: CAPTCHAs: While CAPTCHAs can protect online systems from bot incursions, they can also create friction with the user process. Firewalls: To stop DDoS attacks, companies might reduce attack points by utilizing firewalls or restricting direct traffic to sensitive infrastructures like databases.4 Blocklists: These can prevent IPs associated with attacks from accessing your system entirely. Multifactor authentication (MFA): MFA requires two forms of identification or more before granting access to an account. Password protection: Password managers can ensure employees use strong passwords that are different for each access point. While the above methods can help, many simply aren't enough, especially for larger companies with many points of potential attacks. A piecemeal approach can also lead to friction on the user's side that may turn potential clients away. Our 2024 Identity and Fraud Report revealed that up to 38 percent of U.S. adults stopped creating a new account because of the friction they encountered during the onboarding process. And often, this friction is in place to try to stop fraudulent access. Incorporating behavioral analytics to combat attacks Another effective way to enhance bot detection is through the use of behavioral analytics. This technology helps track user activity and identify patterns that may suggest malicious bot behavior. By analyzing aspects such as typing speed, mouse movement and the way users interact with websites, businesses can gain real-time insights into whether a visitor is human or a bot. Behavioral analytics in fraud uses machine learning and advanced algorithms to continuously monitor and refine user behavior patterns. This allows businesses to identify bot attacks more accurately and prevent them before they cause harm. By analyzing real-time behaviors, such as how fast someone enters information or their browsing habits, businesses can flag suspicious activity that traditional methods might miss. Why partner with Experian? What companies need is fraud and bot protection with a positive customer experience. We provide account takeover fraud prevention solutions that can help protect your company from bot attacks, fraudulent accounts and other malicious attempts to access your sensitive data. Experian's approach embodies a paradigm shift where fraud detection increases efficiency and accuracy without sacrificing customer experience. We can help protect your company from bot attacks, fraudulent accounts and other malicious attempts to access your sensitive data. Learn more This article includes content created by an AI language model and is intended to provide general information. 1"Bad bot traffic accounts for nearly 30% of APAC internet traffic," SMEhorizon, June 13, 2023. https://www.smehorizon.com/bad-bot-traffic-accounts-for-nearly-30-of-apac-internet-traffic/2"What is a bot?" AWS. https://aws.amazon.com/what-is/bot/3Nield, David. "How ChatGPT — and bots like it — can spread malware," Wired, April 19, 2023. https://www.wired.com/story/chatgpt-ai-bots-spread-malware/4"What is a DDoS attack?" AWS. https://aws.amazon.com/shield/ddos-attack-protection/
It's 2024, and it has never been easier to buy a car in person or online, but automobiles are not quite as affordable as prior to the pandemic. While everyone is looking for the best car deal, some folks are pushing it too far and are falling for auto scams. What is auto lending fraud? Fraud perpetrators are drawn to sectors they perceive as highly lucrative. The accessibility of online vehicle financing and purchasing, coupled with the substantial financial magnitude associated with automotive transactions, renders the auto industry an optimal avenue for cash-out endeavors. Auto lending fraud refers to deceptive or fraudulent activities related to obtaining or processing auto finance. This can involve various schemes aimed at misleading lenders, financial institutions, or individuals involved in the lending process. Criminal networks now operate on social media sites like Facebook and Telegram, offering a unique car buying service using synthetic identities. They create synthetic identities, finance cars with no down payment, and deliver vehicles to addresses chosen by buyers. The process involves selecting a car online, sending a small amount of dollars and a photo against a white background, and receiving a fake driver's license. Those networks claim to exploit car sites' policies successfully. While appealing to those in urgent need of a car, the service poses significant risks as the synthetic identity may be used for other fraudulent activities beyond car purchase. Who is at risk? Everyone involved in the car buying process is at risk of falling victim to auto loan fraud. Car buyers looking to secure financing, as well as lenders, need to be aware of the potential red flags and take necessary precautions to safeguard their interests. Thieves leverage the internet and electronic transactions to perpetrate auto loan fraud. While the growth of online commerce has improved many aspects of trade, it has also made personally identifiable information and financial details vulnerable to data breaches. Unscrupulous individuals can gain unauthorized access to such information, providing the foundation for various identity theft schemes. The internet also facilitates the creation of seemingly legitimate documents that support auto loan fraud. Online services exist to help fraudsters fabricate income statements and fake employment verification from fictitious companies. This trend has made auto loan fraud an increasingly popular method for acquiring vehicles with minimal cash and risk. Another auto loan fraud trend is the increased use of CPN (Credit Privacy Number). Credit Repair firms introduced a novel strategy targeting consumers — the CPN (Credit Privacy Number). Marketed as a nine-digit alternative to a Social Security Number (SSN), CPNs are purportedly usable for obtaining credit. However, it is crucial to note that utilizing a CPN for credit applications constitutes a criminal offense, potentially leading to legal consequences, and car dealerships should not accept them. Detecting auto loan fraud There are several types of auto loan fraud worth noting to better understand the landscape: Income fabrication: Prospective buyers may falsify their income details to qualify for a larger loan or better terms. Lenders should verify income using documents like pay stubs, tax returns, or bank statements and watch out for inconsistencies. Employment misrepresentation: Applicants could lie about their job titles or employment status. Lenders should verify employment details through HR departments or by directly contacting the employer. Trade-in vehicle deception: Some individuals may overstate the value of their trade-in vehicle to secure a higher loan amount. Lenders should perform thorough appraisals or consult trusted sources to ascertain the accurate value of the trade-in. Identity fraud: Fraudsters can assume someone else's identity, commit first party fraud or create a fictitious persona to obtain an auto loan. Lenders must verify the applicant's identity using reliable identification documents and consider using identity verification tools. Forged documentation: Fraudsters may forge or alter documents like income statements, bank statements, or driver's licenses. Lenders should scrutinize documents carefully for discrepancies or signs of tampering. Straw borrower fraud: In this scenario, someone with poor credit convinces a friend or relative with better credit to front the deal, posing as the buyer. A better credit score allows for better terms or a more valuable vehicle. The actual buyer may continue to make payments to the friend, or the loan may become delinquent, negatively affecting the friend's credit score. In extreme cases, the straw buyer is part of a fraud ring, and the vehicle has already been sold in a foreign market. Synthetic identity fraud: Data breaches providing personally identifying information enable identity theft schemes. Perpetrators use illicitly acquired information to create false borrower profiles that appear authentic. These profiles typically have excellent credit, a social security number, an affluent home address, stable employment, and other attributes that make them seem like desirable borrowers. However, a detailed investigation reveals subtle inconsistencies indicative of high risk. How to prevent auto loan fraud To combat auto loan fraud and protect profitability, auto lenders can leverage technological advancements. By applying analytics and machine learning to millions of loan applications and histories, you can identify fraudulent patterns and inconsistencies. Machine learning can determine the type of suspected fraud and provide a confidence factor to guide further investigation and verification. Additionally, you should: Conduct thorough background checks on prospective buyers and verify their personal information and documents. and verify their personal information and documents. Implement a comprehensive loan underwriting process that includes income verification, employment verification, and collateral evaluation. Educate employees about common fraud schemes, warning signs, and best practices to ensure they remain vigilant during loan applications. Foster a culture of cooperation with local law enforcement agencies, sharing information about suspected fraudsters to help prevent future incidents. It is important for individuals and businesses to be vigilant and report any suspicious activity. Car dealerships and financial institutions work to prevent fraud through proper identification verification, credit checks, and adherence to legal and ethical standards. If you suspect fraudulent activity or identity theft, it is crucial to report it to the appropriate authorities immediately. Gearing-up Taking advantage of the latest fintech capabilities, such as cloud-based loan origination that integrates analytics, machine learning, and automated verification services, can significantly reduce the likelihood of fraudulent applications becoming another auto lending fraud statistic. By combining the best data with our automated ID verification checks, Experian helps you safeguard your business and onboard customers efficiently. Our best-in-class solutions employ device recognition, behavioral biometrics, machine learning, and global fraud databases to spot and block suspicious activity before it becomes a problem. Learn more about our automotive fraud prevention solutions *This article includes content created by an AI language model and is intended to provide general information.
Financial institutions, merchants, and e-commerce platforms are no strangers to fraud, especially in the realm of payments. With the rise of digital currency, fraudsters are becoming more inventive, making it increasingly difficult to detect and prevent payment fraud. In this blog post, we discuss payment fraud and ways to protect your organization and your customers. What is payment fraud? Payment fraud occurs when someone uses false or stolen payment information to make a purchase or transaction. The most common types of payment fraud include: Phishing: Through emails or text messages, scammers disguise themselves as trustworthy sources to lure recipients into sharing their personal information, such as account passwords and credit card numbers. Card not present fraud: This type of fraud is one of the most challenging forms of payment fraud to detect and prevent. It occurs when a criminal uses a stolen or compromised credit card to make a purchase online, in-person, or by other means where the card is not physically present at the time of the transaction. Account takeover fraud: This type of fraud occurs when fraudsters gain unauthorized access to an individual’s account and carry out fraudulent transactions. They take over accounts by gathering and using personal or financial details to impersonate their victims. The rise of online payment fraud Online payments have become a prime destination for fraudsters as more consumers choose to store card details and make purchases digitally. As a result, consumers believe that it’s the responsibility of businesses to protect them online. If there’s a lack of trust and safety, consumers will have no problem switching providers, leading to declines in customer loyalty and monetary losses for organizations. No matter the type of payment fraud, it can result in devastating consequences for your organization and your customers. According to Experian’s 2024 U.S. Identity and Fraud Report, fraud scams and bank fraud schemes resulted in more than $458 billion in losses globally. On the consumer side, 52 million Americans had fraudulent charges on their credit or debit cards, with unauthorized purchases exceeding $5 billion. Given these findings, it’s more important than ever to implement robust online payment fraud detection and prevention measures. How can payment fraud be detected and prevented? Approaches to payment fraud detection and prevention have evolved over time. Some of the current and emerging trends include: Additional layers of security: Security measures like two-factor authentication, a CVV code, and a billing zip code can help verify a customer’s identity and make it more difficult for fraudsters to complete a transaction. Enhanced identity verification: A credit card owner verification solution, like Experian LinkTM, matches the customer identity with the credit card being presented for payment, allowing businesses to make better decisions, reduce false declines, and protect legitimate customers. Artificial intelligence (AI) and machine learning: AI-powered models and machine learning algorithms can identify patterns consistent with fraudulent activity in real time, resulting in proactive fraud prevention and reduced financial losses. Behavioral analytics: Using behavioral analytics to monitor user behavior, such as how they navigate a website or interact with the payment process, can help identify inconsistencies and potential fraud. Token-based authentication: Tokenization protects card information by replacing sensitive data with a unique identifier (token), which makes data breaches less damaging. How Experian can help As the payments landscape continues to evolve, so do fraudsters. Experian offers a wide range of payment fraud analytics, account takeover fraud prevention and fraud management solutions that allow you to better detect and prevent payment fraud. Your organization’s reputation and your customers’ trust shouldn’t be compromised. To learn more, visit us today. Learn more This article includes content created by an AI language model and is intended to provide general information.