Tag: fraud prevention

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 

In this article...What is credit card fraud?Types of credit card fraudWhat is credit card fraud prevention and detection?How Experian® can help with card fraud prevention and detection With debit and credit card transactions becoming more prevalent than cash payments in today’s digital-first world, card fraud has become a significant concern for organizations. Widespread usage has created ample opportunities for cybercriminals to engage in credit card fraud. As a result, millions of Americans fall victim to credit card fraud annually, with 52 million cases reported last year alone.1 Preventing and detecting credit card fraud can save organizations from costly losses and protect their customers and reputations. This article provides an overview of credit card fraud detection, focusing on the current trends, types of fraud, and detection and prevention solutions. What is credit card fraud? Credit card fraud involves the unauthorized use of a credit card to obtain goods, services or funds. It's a crime that affects individuals and businesses alike, leading to financial losses and compromised personal information. Understanding the various forms of credit card fraud is essential for developing effective prevention strategies. Types of credit card fraud Understanding the different types of credit card fraud can help in developing targeted prevention strategies. Common types of credit card fraud include: Card not present fraud occurs when the physical card is not present during the transaction, commonly seen in online or over-the-phone purchases. In 2023, card not present fraud was estimated to account for $9.49 billion in losses.2 Account takeover fraud involves fraudsters gaining access to a victim's account to make unauthorized transactions. In 2023, account takeover attacks increased 354% year-over-year, resulting in almost $13 billion in losses.3,4 Card skimming, which is estimated to cost consumers and financial institutions over $1 billion per year, occurs when fraudsters use devices to capture card information from ATMs or point-of-sale terminals.5 Phishing scams trick victims into providing their card information through fake emails, texts or websites. What is credit card fraud prevention and detection? To combat the rise in credit card fraud effectively, organizations must implement credit card fraud prevention strategies that involve a combination of solutions and technologies designed to identify and stop fraudulent activities. Effective fraud prevention solutions can help businesses minimize losses and protect their customers' information. Common credit card fraud prevention and detection methods include: Fraud monitoring systems: Banks and financial institutions employ sophisticated algorithms and artificial intelligence to monitor transactions in real time. These systems analyze spending patterns, locations, transaction amounts, and other variables to detect suspicious activity. EMV chip technology: EMV (Europay, Mastercard, and Visa) chip cards contain embedded microchips that generate unique transaction codes for each purchase. This makes it more difficult for fraudsters to create counterfeit cards. Tokenization: Tokenization replaces sensitive card information with a unique identifier or token. This token can be used for transactions without exposing actual card details, reducing the risk of fraud if data is intercepted. Multifactor authentication (MFA): Adding an extra layer of security beyond the card number and PIN, MFA requires additional verification such as a one-time code sent to a mobile device, knowledge-based authentication or biometric/document confirmation. Transaction alerts: Many banks offer alerts via SMS or email for every credit card transaction. This allows cardholders to spot unauthorized transactions quickly and report them to their bank. Card verification value (CVV): CVV codes, typically three-digit numbers printed on the back of cards (four digits for American Express), are used to verify that the person making an online or telephone purchase physically possesses the card. Machine learning and AI: Advanced algorithms can analyze large datasets to detect unusual patterns that may indicate fraud, such as sudden large transactions or purchases made in different geographic locations within a short time frame. Advanced algorithms can analyze large datasets to detect unusual patterns that may indicate fraud, such as sudden large transactions or purchases made in different geographic locations within a short time frame. Behavioral analytics: Monitoring user behavior to detect anomalies that may indicate fraud. Education and awareness: Educating consumers about phishing scams, identity theft, and safe online shopping practices can help reduce the likelihood of falling victim to credit card fraud. Fraud investigation units: Financial institutions have teams dedicated to investigating suspicious transactions reported by customers. These units work to confirm fraud, mitigate losses, and prevent future incidents. How Experian® can help with card fraud prevention and detection Credit card fraud detection is essential for protecting businesses and customers. By implementing advanced detection technologies, businesses can create a robust defense against fraudsters. Experian® offers advanced fraud management solutions that leverage identity protection, machine learning, and advanced analytics. Partnering with Experian can provide your business with: Comprehensive fraud management solutions: Experian’s fraud management solutions provide a robust suite of tools to prevent, detect and manage fraud risk and identity verification effectively.  Account takeover prevention: Experian uses sophisticated analytics and enhanced decision-making capabilities to help businesses drive successful transactions by monitoring identity and flagging unusual activities. Identifying card not present fraud: Experian offers tools specifically designed to detect and prevent card not present fraud, ensuring secure online transactions.  Take your fraud prevention strategies to the next level with Experian's comprehensive solutions. Explore more about how Experian can help. Learn More Sources 1 https://www.security.org/digital-safety/credit-card-fraud-report/ 2 https://www.emarketer.com/chart/258923/us-total-card-not-present-cnp-fraud-loss-2019-2024-billions-change-of-total-card-payment-fraud-loss 3 https://pages.sift.com/rs/526-PCC-974/images/Sift-2023-Q3-Index-Report_ATO.pdf 4 https://www.aarp.org/money/scams-fraud/info-2024/identity-fraud-report.html 5 https://www.fbi.gov/how-we-can-help-you/scams-and-safety/common-scams-and-crimes/skimming This article includes content created by an AI language model and is intended to provide general information. 

In this article...What is a TOAD attack?How TOAD attacks happenEffective countermeasures Keeping TOADS at bay with Experian Imagine receiving a phone call informing you that your antivirus software license is about to expire. You decide to renew it over the phone, and before you know it, you have been “TOAD-ed”! What is a TOAD attack? Telephone-Oriented Attack Deliveries (TOADs) are an increasingly common threat to businesses worldwide. According to Proofpoint's 2024 State of the Phish Report, 10 million TOAD attacks are made every month, and 67% of businesses globally were affected by a TOAD attack in 2023. In the UK alone, businesses have lost over £500 million to these scams, while in the United States the reported monetary loss averaged $43,000 per incident, with some losses exceeding $1 million.TOADs involve cybercriminals using real phone numbers to impersonate legitimate callers, tricking victims into divulging sensitive information or making fraudulent transactions. This type of attack can result in substantial financial losses and reputational damage for businesses. How TOAD attacks happen TOAD attacks often involve callback phishing, where victims are tricked into calling fake call centers. Before they strike, scammers will gather a victim's credentials from various sources, such as past data breaches, social media profiles, and information bought on the dark web. They will then contact the individual through applications like WhatsApp or call their phone directly. Here is a common TOAD attack example: Initial contact: The victim receives an email from what appears to be a reputable company, like Amazon or PayPal. Fake invoice: The email contains a fake invoice for a large purchase, prompting the recipient to call a customer service number. Deception: A scammer, posing as a customer service agent, convinces the victim to download malware disguised as a support tool, granting the scammer access to the victim's computer and personal information. These techniques keep improving. One of the cleverer tricks of TOADs is to spoof a number or email so they contact you as someone you know. Vishing is a type of phishing that uses phone calls, fake numbers, voice changers, texts, and social engineering to obtain sensitive information from users. It mainly relies on voice to fool users. (Smishing is another type of phishing that uses texts to fool users, and it can be combined with phone calls depending on how the attacker works.) According to Rogers Communication website, an employee in Toronto, Canada got an email asking them to call Apple to change a password. They followed the instructions, and a “specialist” helped them do it. After receiving their password, the cyber criminals used the employee's account to send emails and deceive colleagues into approving a fake payment of $5,000. Artificial intelligence (AI) is also making it easier for TOAD phishing attacks to happen. A few months ago, a Hong Kong executive was fooled into sending HK$200m of his company's funds to cyber criminals who impersonated senior officials in a deepfake video meeting. Effective countermeasures To combat TOAD attacks, businesses must implement robust solutions. Employee training and awareness: Regular training sessions and vishing simulations help employees recognize and respond to TOAD attacks. Authentication and verification protocols: Implementing multi-factor authentication (MFA) and call-back verification procedures enhances security for sensitive transactions. Technology solutions: Bots and spoofing detection and voice biometric authentication technologies help verify the identity of callers and block fraudulent numbers. Monitoring and analytics: Advanced fraud detection and behavioral analytics identify anomalies and unusual activities indicative of TOAD attacks. Secure communication channels: Ensure consumers have access to verified customer service numbers and promote secure messaging apps. A strong strategy should also involve using advanced email security solutions with AI fraud detection and machine learning (ML) to effectively defend against TOAD threats. These can help identify and stop phishing emails. Regular security audits and updates are necessary to find and fix vulnerabilities, and an incident response plan should be prepared to deal with and reduce any breaches. By integrating technology, processes, and people into their strategy, organizations can develop a strong defense against TOAD attacks. Keeping TOADS at bay with Experian®  By working and exchanging information with other businesses and industry groups, you can gain useful knowledge about new or emerging threats and defense strategies. Governments and organizations like the Federal Communications Commission (FCC) have a shared duty to defend the private sector and public consumers from TOAD attacks, while many of the current rules and laws seem to lag behind what criminals are doing. By combining the best data with our automated ID verification processes, Experian® helps you protect your business and reputation. 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 *This article includes content created by an AI language model and is intended to provide general information.

With e-commerce booming and more transactions occurring online, the threat of chargeback fraud has never been more significant. In this article, we'll explore chargeback fraud, why it's a growing problem, and, most importantly, how to prevent it. Whether you're a small or large business, understanding and implementing robust chargeback fraud prevention measures is critical to protecting your organization. Understanding chargeback fraud Before we can prevent chargeback fraud, we need to know what we're dealing with. A chargeback happens when a cardholder disputes a transaction, or files a chargeback request, leading to the reversal of the payment to the merchant. Chargebacks can occur for various reasons including: Fraudulent transactions: If a card is stolen or its information is used without authorization, like in the case of account takeover fraud or card not present fraud, the cardholder can dispute the charges. Unauthorized transactions: Even if the cardholder didn't lose their card, they might notice charges they didn't make. Quality issues: If the product or service doesn't meet the cardholder's expectations or has a defect, they might dispute the charge. Billing errors: Sometimes, billing mistakes happen, such as being charged multiple times for the same transaction. Subscription cancellations: When a cardholder cancels a subscription but continues to be billed they can dispute the charges. While there are legitimate reasons for chargebacks, chargeback fraud, also known as friendly fraud, occurs when a customer makes a legitimate purchase with their credit card and then disputes the charge by filing a chargeback request. Unlike third-party fraud, where the cardholder's information is stolen or used without permission, in chargeback fraud, the cardholder initiates the dispute to avoid paying for goods or services they legitimately received. Chargeback fraud can take various forms: False claims of non-receipt: The cardholder claims they never received the purchased item, even though they did. Unauthorized transaction claims: The cardholder denies making the purchase, even though they did so legitimately. Product/service dissatisfaction: The cardholder claims dissatisfaction with the product or service as a reason for disputing the charge, even if the product or service was as described. Subscription services: The cardholder signs up for a subscription service and then disputes the recurring charges as unauthorized or unwanted. Why chargeback fraud is on the rise Chargeback fraud is becoming more pervasive for a couple of reasons. First, as e-commerce grows, so does the opportunity for fraud. Without face-to-face interactions, fraudsters can pull off their schemes more easily. Second, the process of issuing chargebacks has become consumer-friendly, with banks often siding with the cardholder without deep scrutiny of the claim. Finally, with the rise of subscription-based services and digital goods, the incidence of "friendly fraud" is increasing. The impact and repercussions of chargeback fraud The impact of chargeback fraud can be felt across several areas within a business. Financially, it's a clear and direct loss. There are also significant operational costs associated with managing chargebacks, including potential product loss, bank and related fees, and administrative work. However, the less tangible, more insidious repercussions involve damage to the business's reputation. A high chargeback rate can lead to a merchant account being suspended or terminated, causing a loss of the ability to process credit card payments. A tarnished reputation can further lead to losing consumer trust, which can be hard to regain. How to prevent chargeback fraud Preventing and managing chargeback fraud often involves implementing fraud prevention solutions, providing clear communication and customer support, and disputing illegitimate chargebacks with evidence when possible. Here are key actions you can take to protect your business against chargeback fraud: Educate and communicate with customers: Ensure your customers are fully aware of your return and refund policies. Be clear and transparent in your communications about what happens in the event of a disputed transaction. This can significantly reduce misunderstandings that often lead to legitimate chargebacks. Implement stringent transaction verification processes: Utilize Address Verification Services (AVS) and Card Verification Value (CVV2) verification for online and over-the-phone transactions. These credit card authentication services add an extra layer of security and can establish the validity of a purchase. Keep meticulous records: Document all transactions, including emails, phone calls, and any other purchase-related correspondence. In the event of a dispute, these records can serve as compelling evidence to defend the transaction. Immediate shipment and tracking: Ship products as quickly as possible after purchase and provide tracking information to customers. This delights customers and provides tangible proof of delivery should a chargeback be disputed. Utilize advanced fraud detection tools: Many fraud detection services are available that can instantly flag potentially fraudulent transactions, from monitoring for suspicious spending patterns to IP tracking for online orders. Examples include: Tokenization: Tokenization replaces sensitive card data with a "token," a random string of characters that is useless to fraudsters. This token can be stored or transmitted easily, with the actual payment information securely kept off-site. Machine learning and AI: Machine learning and AI fraud detection solutions can analyze vast amounts of transaction data to detect patterns and anomalies, thus flagging potentially fraudulent activity in real-time. The role of customer support in chargeback prevention While the above tools can help your organization prevent fraudulent charge backs, you likely already have a key tool in your company that can help mitigate chargebacks altogether. Your customer support team is your front line in chargeback prevention. Train them to handle customer inquiries effectively and resolve issues before they escalate. Offer multiple contact channels: Give customers several ways to reach your support team, such as email, phone, and live chat. The more easily they can contact you, the less likely they are to resort to a chargeback. Ensure prompt and courteous service: A positive and responsive customer service experience can turn a potential chargeback into a loyalty-building opportunity. Make refunds and returns as easy as possible for your customers. Additionally, clear and generous policies will reduce dissatisfaction and the likelihood of chargebacks. How Experian can help with chargeback fraud prevention Chargeback fraud can be a daunting prospect for any business, but with the right strategies in place, you can protect your business, your customers and your bottom line. Experian’s fraud management solutions provide robust verification options and layered risk management to help reduce the risk of chargeback fraud. Our advanced fraud detection solutions leverage machine learning algorithms and behavioral analytics to confirm the identity of customers during transactions, identify suspicious patterns and activities, and offer deeper insights that enhance fraud prevention strategies. These solutions can help detect potential instances of chargeback fraud in real-time or during post-transaction analysis. Learn More *This article includes content created by an AI language model and is intended to provide general information.

The world of finance can be a dangerous place, where cunning schemes lurk in the shadows, ready to pounce on unsuspecting victims. In the ever-evolving landscape of financial crime, the insidious ‘pig butchering’ scam has emerged as a significant threat, targeting both financial institutions and their clients. What is a ‘pig butchering’ scam? ‘Pig butchering’ scams are named after the practice of farmers fattening up their livestock before “butchering” them. This comparison describes the core of ‘pig butchering’ scams, where criminals entice victims to participate in investment schemes and cryptocurrency fraud. Originating in Southeast Asia and now rampant in the United States, these scams often start with online interactions via social media or dating applications. Scammers build trust with the victim, eventually gaining access to their online accounts. They "fatten the pig" by enticing more cryptocurrency investments and then make off with their ill-gotten gains. The repercussions are staggering, with reported losses exceeding $3.5 billion in 2023 alone according to an AP News article, and around 40,000 victims in the United States, including cases of losses as massive as $4 million. The real-life impact The story of “RB,” a San Francisco man who engaged with a scammer named "Janey Lee," serves as a stark warning. Through social media, Janey orchestrated an elaborate scheme, promising "RB” substantial returns in cryptocurrency investment. Seduced by false promises, “RB” emptied his life savings into the scam, only to be rescued by a Federal Bureau of Investigation (FBI) intervention, narrowly avoiding financial ruin.1 Malicious actors are improving their targeting skills, and often pursue executives and victims with a large sum of money, such as C-level officials from financial institutions. This past February, a $50 million pig slaughtering fraud incident caused the CEO of a local bank in Kansas to lose all his funds and the bank to collapse a few months later. FinCEN's vigilance and updates The Financial Crimes Enforcement Network (FinCEN) remains vigilant, issuing advisories to financial institutions to combat ‘pig butchering’ scams. Their latest advisory highlights evolving scam tactics, including aggressive promotions, using money mules for illegal fund transfers, and leveraging new financial products like decentralized finance (DeFi) platforms to obfuscate transactions. FinCEN also warns about red flags such as large and sudden investments from older customers, quick fund withdrawals after big deposits, and the frequent use of coins or mixers that hide transactions. Financial institutions are encouraged to: Report any suspicious activities by using specific terms like "pig butchering fraud advisory" in their reports to make analysis and response easier. File suspicious activity reports (SARs) using the key term “FIN-2023-PIGBUTCHERING.” Guide potential victims to report to the FBI’s IC3 or the Security and Exchange Commission (SEC’s) reporting system. A call to action for financial institutions The fight against ‘pig butchering’ scams requires proactive measures from financial institutions: Enhance fraud detection and anti-money laundering (AML) programs: Implement robust systems compliant with regulatory guidelines, conduct thorough customer enhanced due diligence, and leverage fraud detection software to spot anomalies and red flags., and leverage fraud detection software to spot anomalies and red flags. Leverage data analytics: Utilize data analytics tools to monitor customer behavior, identify irregular patterns, and swiftly detect potential ‘pig butchering’ activities. Employee training: Educate employees on scam risks, fraud detection techniques, and FinCEN red flags to empower them as the first line of defense., and FinCEN red flags to empower them as the first line of defense. Community education: Educate customers on recognizing and avoiding investment scams, promoting awareness, and safeguarding their assets. Navigating challenges with effective solutions ‘Pig butchering’ scams cause not only money losses but also personal troubles and reputational harm. Awareness, learning, and cooperation are essential in protecting from these complex financial fraudsters, securing the safety and confidence of your institutions and stakeholders. By combining the best data with our automated identification verification processes, you can protect your business and onboard new talents efficiently. Our industry-leading 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 1San Francisco Chronical (2023). Crypto Texting Scam *This article includes content created by an AI language model and is intended to provide general information.

In a financial world that's increasingly connected and complex, monitoring transactions is not just good business practice — it's a regulatory necessity. Anti-money laundering (AML) transaction monitoring stands as a crucial barrier against financial crimes, which ensures the integrity of financial systems worldwide. For financial institutions, the challenges of AML compliance and the tools to meet them continue to evolve. In this blog post, we'll walk through the basics, best practices, and future of AML transaction monitoring. What is AML transaction monitoring? AML transaction monitoring refers to the systems and processes financial institutions use to detect and report potentially suspicious transactions to the Financial Crimes Enforcement Network (FinCEN) under the United States Department of Treasury, which spearheads the efforts to track financial crimes — money laundering and financing of criminal or terrorist activities. By continuously monitoring customer transactions and establishing patterns of behavior, suspicious activities can be identified for further investigation. The role of AML transaction monitoring AML transaction monitoring identifies potential criminal activities and helps maintain a clean and efficient financial ecosystem. By being proactive in preventing the misuse of services, organizations can protect their reputation, strengthen customer trust, and uphold regulatory requirements. The challenge of false positives However, AML compliance is not without challenges. The systems in place often produce many 'false positives', transactions identified as potentially suspicious that, after investigation, turn out to be mundane. These false alarms can overwhelm compliance departments, leading to inefficiency and potentially missing real red flags. Why is AML transaction monitoring important? Understanding the importance of AML transaction monitoring requires a broader look at the implications of financial crimes. Money laundering often supports other serious crimes such as drug trafficking, fraud, and even terrorism. The ability to interrupt the flow of illicit funds also disrupts these additional criminal networks. Furthermore, for organizations, the cost of non-compliance can be substantial — financially and reputationally. Penalties for inadequate AML controls can be hefty, signaling the need for robust monitoring systems. Specifics on compliance Compliance with AML regulations is not a choice but a must. Financial institutions are required to comply with AML laws and regulations to protect their businesses and the industry as a whole. This includes understanding and adhering to regulation changes, which can be complex and have significant operational impacts. How does AML transaction monitoring work? There are two main approaches to transaction monitoring: Rule-based systems: These rely on pre-defined rules that flag transactions exceeding certain thresholds, originating from high-risk countries, or involving specific types of activities. Scenario-based systems: These use more sophisticated algorithms to analyze transaction patterns and identify anomalies that might not be captured by simple rules. This can include analyzing customer behavior, source of funds, and the purpose of transactions. Most organizations use a combination of both approaches. Transaction monitoring software is a valuable tool, but it's important to remember that it's not a foolproof solution. Human analysis is still essential to investigate flagged transactions and determine if they are truly suspicious. Implementing AML transaction monitoring solutions Implementing a robust AML transaction monitoring system requires the right technology and the right strategy. Beyond the software, it's about embedding a culture of compliance within the organization. Choosing the right AML solution The right AML solution should be based on the specific needs of the institution, the complexity of its operations, and the sophistication of the fraud landscape it faces. It's imperative to pick a solution that is agile, scalable, and integrates seamlessly with existing systems. Leveraging KYC and CIP programs Know your customer (KYC) and customer identification program (CIP) are deeply connected to transaction monitoring. Implementing a robust KYC program helps to establish a strong customer identity, whereas a solid CIP ensures that essential customer information is verified at the time of account opening. Automation and AI in AML compliance Automation and AI are revolutionizing AML compliance, especially in transaction monitoring. AI systems, with their ability to learn and evolve, can significantly reduce false positives, making the compliance process more efficient and effective. Advanced AML solutions and the future Technological advancements are constantly reshaping the AML landscape, including solutions incorporating big data analysis and machine learning. Utilizing big data for better insights: Big data analytics provides an unprecedented ability to spot potential money laundering by analyzing vast amounts of transactional data, allowing for better contextual understanding and the ability to identify patterns of suspicious activity. Machine learning and predictive analytics: Machine learning technologies have the potential to refine transaction monitoring by continuously learning new behaviors and adapting to evolving threats. Predictive analytics can help in identifying potential risks well in advance and taking pre-emptive actions. The human element in AML Despite the advancing technology, the human element remains crucial. AML systems are only as good as the people who operate them. Organizations must invest in: Continuous training and skill development: Continuous training ensures that employees remain updated on regulations, compliance techniques, and the latest tools. Developing a team with AML expertise is an investment in the institution's security and success. Cultivating a compliance culture: Cultivating a corporate culture that values compliance is vital. From the highest levels of management to front-line staff, a mindset that embraces the duty to protect against financial crime is a powerful asset in maintaining an effective AML program. How we can help As a leader in fraud prevention and identity verification, Experian’s AML solutions can help you increase the effectiveness of your AML program to efficiently comply with federal and international AML regulations while safeguarding your organization from financial crime. We provide data, models, and automated systems and processes to monitor, detect, investigate, document and report potential money laundering activities across the entire customer lifecycle. Learn more about Experian’s AML solutions *This article includes content created by an AI language model and is intended to provide general information.

Financial institutions have long relied on anti-money laundering (AML) and anti-fraud systems to protect themselves and their customers. These departments and systems have historically operated in siloes, but that’s no longer best practice.  Now, a new framework that integrates fraud and AML, or FRAML, is taking hold as financial institutions see the value of sharing resources to fight fraud and other financial crimes.  You don’t need to keep them separated For fraudsters, fraud and money laundering go hand-in-hand. By definition, someone opening an account and laundering money is committing a crime. The laundered funds are also often from illegal activity — otherwise, they wouldn’t need to be laundered.  For financial institutions, different departments have historically owned AML and anti-fraud programs. In part, because AML and fraud prevention have different goals: AML is about staying compliant: AML is often owned by an organization’s compliance department, which ensures the proper processes and reporting are in place to comply with relevant regulations.  Fraud is about avoiding losses: The fraud department identifies and stops fraudulent activity to help protect the organization from reputational harm and fraud losses. As fraudsters’ operations become more complex, the traditional separation of the two departments may be doing more harm than good.  Common areas of focus There has always been some overlap in AML and fraud prevention. After all, an AML program can stop criminals from opening or using accounts that could lead to fraud losses. And fraud departments might stop suspicious activity that’s a criminal placing or layering funds. While AML and fraud both involve ongoing account monitoring, let’s take a closer look at similarities during the account creation: Verifying identities: Financial institutions’ AML programs must include know your customer (KYC) procedures and a Customer Identification Program (CIP). Being able to verify the identity of a new customer can be important for tracing transactions back to an individual or entity later. Similarly, fraud departments want to be sure there aren’t any red flags when opening a new account, such as a connection between the person or entity and previous fraudulent activity.  Preventing synthetic identity fraud: Criminals may try to use synthetic identities to avoid triggering AML or fraud checks. Synthetic identity fraud has been a growing problem, but the latest solutions and tools can help financial institutions stop synthetic identity fraud across the customer lifecycle.  Detecting money mules: Some criminals recruit money mules rather than using their own identity or creating a synthetic identity. The mules are paid to use their legitimate bank account to accept and transfer funds on behalf of the criminal. In some cases, the mule is an unwitting victim of a scam and an accomplice in money laundering.  Although the exact requirements, tools, processes, and reports for AML and fraud differ, there’s certainly one commonality — identify and stop bad actors.    Interactive infographic: Building a multilayered fraud and identity strategy The win-win of the FRAML approach Aligning AML and fraud could lead to cost savings and benefits for the organization and its customers in many ways. Save on IT costs: Fraud and AML teams may benefit from similar types of advanced analytics for detecting suspicious activity. In 2023, around 60 percent of businesses were using or trying to use machine learning (ML) in their fraud strategies, but a quarter said cost was impeding implementation.1 If fraud and AML can share IT resources and assets, they might be able to better afford the latest ML and AI solutions.  Avoid duplicate work: Cost savings can also happen if you can avoid having separate AML and fraud investigations into the same case. The diverse backgrounds and approaches to investigations may also lead to more efficient and successful outcomes.  Get a holistic view of customers: Sharing information about customers and accounts also might help you more accurately assess risk and identify fraud groups.  Improve your customer experience: Shared data can also reduce customer outreach for identity or transaction verifications. Creating a single view of each account or customer can also improve customer onboarding and account monitoring, leading to fewer false positives and a better customer experience.  Some financial institutions have implemented collaboration with the creation of a new team, sometimes called the financial crimes unit (FCU). Others may keep the departments separate but develop systems for sharing data and resources.  Watch the webinar: Fraud and identity challenges for Fintechs How Experian can help  Creating new systems and changing company culture doesn’t happen overnight, but the shift toward collaboration may be one of the big trends in AML and fraud for 2024. As a leader in identity verification and fraud prevention, Experian can offer the tools and strategies that organizations need to update their AML and fraud processes across the entire customer lifecycle.  CrossCore® is our integrated digital identity and fraud risk platform which enables organizations to connect, access, and orchestrate decisions that leverage multiple data sources and services. CrossCore cloud platform combines risk-based authentication, identity proofing and fraud detection, which enables organizations to streamline processes and quickly respond to an ever-changing environment. In its 2023 Fraud Reduction Intelligence Platforms (FRIP), Kuppinger Cole wrote, “Once again, Experian is a Leader in Fraud Reduction Intelligence Platforms. Any organizations looking for a full-featured FRIP service with global support should consider Experian CrossCore.”  Learn more about Experian’s AML and fraud solutions. 1. Experian (2023). Experian's 2023 Identity and Fraud Report  

Know Your Customer (KYC) procedures are a requirement for banks and other financial institutions to collect and verify the identity of their customers. When a bank verifies the identity of another organization or its owners, the process may be called Know Your Business (KYB) instead.  As part of banks’ anti-money laundering (AML) programs, KYC can help stop corruption, money laundering and terrorist financing. Creating and maintaining KYC programs is also important for regulatory compliance, reputation management and fraud prevention.  READ: How to Build a Know Your Customer Checklist – Everything You Need to Know The three components of KYC programs Banks can largely determine how to set up their KYC and AML programs within the applicable regulatory guidelines. In the United States, KYC needs to happen when banks initially onboard a new customer. But it’s not a one-and-done event—ongoing customer and transaction monitoring is also important.  Customer Identification Program (CIP) Creating a robust Customer Identification Program (CIP) is an essential part of KYC. At a minimum, a bank’s CIP requires it to collect the following information from new customers: Name Date of birth Address Identification number, such as a Social Security number (SSN) or Employer Identification Number (EIN) Banks' CIPs also have to use risk-based procedures to verify customers’ identities and form a reasonable belief that they know the customer's true identity.1 This might involve comparing the information from the application to the customer’s government-issued ID, other identifying documents and authoritative data sources, such as credit bureau databases. Additionally, the bank's CIP will govern how the bank:  Retains the customer’s identifying information Compares customer to government lists  Provides customers with adequate notices Banks can create CIPs that meet all the requirements in various ways, and many use third-party solutions to quickly collect data, detect forged or falsified documents and verify the provided information.  INFOGRAPHIC: Streamlining the Digital Onboarding Process: Beating Fraud at its Game Customer due diligence (CDD)  CIP and CDD overlap, but the CIP primarily verifies a customer’s identity while customer due diligence (CDD) helps banks understand the risk that each customer poses. To do this, banks try to understand what various types of customers do, what those customers’ normal banking activity looks like, and in contrast, what could be unusual or suspicious activity.  Financial institutions can use risk ratings and scores to evaluate customers and then use simplified, standard or enhanced due diligence (EDD) processes based on the results. For example, customers who might pose a greater risk of laundering money or financing terrorism may need to undergo additional screenings and clarify the source of their funds. Ongoing monitoring Ongoing or continuous monitoring of customers’ identities and transactions is also important for staying compliant with AML regulations and stopping fraud.  The monitoring can help banks spot a significant change in the identity of the customer, beneficial owner or account, which may require a new KYC check. Unusual transactions can also be a sign of money laundering or fraud, and they may require the bank to file a suspicious activity report (SAR). Why is KYC important in banking? Understanding and implementing KYC processes can be important for several reasons:  Regulatory compliance: Although the specific laws and rules can vary by country or region, many banks are required to have AML procedures, including KYC. The fines for violating AML regulations can be in the hundreds of millions— a few banks have been fined over $1 billion for lax AML enforcement and sanctions breaching. Reputation management: In some cases, enforcement actions and fines were headline news. Banks that don’t have robust KYC procedures in place risk losing their customers' trust and respect.  Fraud prevention: In addition to the regulatory requirements, KYC policies and systems can also work alongside fraud management solutions for banks. Identity verification at onboarding can help banks identify synthetic identities attempting to open money mule accounts or take out loans. Ongoing monitoring can also be important for identifying long-term fraud schemes and large fraud rings.  ON-DEMAND WEBINAR: Fraud Strategies for a Positive Customer Experience KYC in a digital-first world Many financial institutions have been going through digital transformations. Part of that journey is updating the systems and tools in place to meet the expectations of customers and regulators.  An Experian survey found that about half of consumers (51 percent) consider abandoning the creation of a new account because of friction or a less-than-positive experience — that increased to 69 percent for high-income households.2 The survey wasn’t specific to financial services, but friction could be a problem for banks wanting to attract new account holders. Just as access to additional data sources and machine learning help automate underwriting, financial institutions can use technological advances to add an appropriate amount of friction based on various risk signals. Some of these can be run in the background, such as an electronic Consent Based Social Security Number Verification (eCBSV) check to verify the customer’s name, SSN and date of birth match the Social Security Administration’s records. Others may require more customer involvement, such as taking a selfie that’s then compared to the image on their photo ID — Experian CrossCore® Doc Capture enables this type of verification.  Experian is a leader in identity and data management  Experian's identity verification solutions use proprietary and third-party data to help banks manage their KYC procedures, including identity verification and Customer Identification Programs. By bundling identity verification with fraud assessment, banks can stop fraudsters while quickly resolving identity discrepancies. The automated processes also allow you to offer a low-friction identity verification experience and use step-up authentications as needed.  Learn more about Experian’s identity solutions.  1FDIC (2021). Customer Identification Program 2Experian (2023). Experian's 2023 Identity and Fraud Report

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.

This article was updated on March 4, 2024. If you steal an identity to commit fraud, your success is determined by how long it takes the victim to find out. That window gets shorter as businesses get better at knowing when and how to reach an identity owner when fraud is suspected. In response, frustrated fraudsters have been developing techniques to commit fraud that does not involve a real identity, giving them a longer run-time and a bigger payday.  That's the idea behind  synthetic identity (SID) fraud — one of the fastest-growing types of fraud.  Defining synthetic identity fraud Organizations tend to have different  definitions of synthetic identity fraud, as a synthetic identity will look different to the businesses it attacks. Some may see a new account that goes bad immediately, while others might see a longer tenured account fall delinquent and default. The qualifications of the synthetic identity also change over time, as the fraudster works to increase the identity’s appearance of legitimacy. In the end, there is no person to confirm that fraud has occurred, in the very best case, identifying a synthetic identity is inferred and verified. As a result, inconsistent reporting and categorization can make tracking and fighting SID fraud more difficult.  To help create a more unified understanding and response to the issue, the Federal Reserve and 12 fraud experts worked together to develop a definition. In 2021, the  Boston Federal Reserve  published the result, “Synthetic identity fraud is the use of a combination of personally identifiable information to fabricate a person or entity to commit a dishonest act for personal or financial gain."1 To break down the definition, personally identifiable information (PII) can include:  Primary PII:  Such as a name, date of birth (DOB), Social Security number (SSN) or another government-issued identifier. When combined, these are generally unique to a person or entity. Secondary PII:  Such as an address, email, phone number or device ID. These elements can help verify a person or entity's identity.   Synthetic identities are created when fraudsters establish an identity from scratch using fake PII. Or they may combine real and fake PII (I.e., a stolen SSN with a fake name and DOB) to create a new identity. Additionally, fraudsters might steal and use someone's SSN to create an identity - children, the  elderly  and incarcerated people are popular targets because they don't commonly use credit.4 But any losses would still be tied to the SID rather than the victim. Exploring the Impact of SID fraud The most immediate and obvious impact of SID fraud is the fraud losses. Criminals may create a synthetic identity and spend months  building up its credit profile, opening accounts and increasing credit limits. The identities and behaviors are constructed to look like legitimate borrowers, with some having a record of on-time payments. But once the fraudster decides to monetize the identity, they can apply for loans and max out credit cards before ‘busting out’ and disappearing with the money.  Aite-Novaric Group estimates that SID fraud losses totaled $1.8 billion in 2020 and will increase to $2.94 billion in 2024.2 However, organizations that do not identify SIDs may classify a default as a credit loss rather than a fraud loss.  By some estimates, synthetic identity fraud could account for up to 20 percent of loan and credit card charge-offs, meaning the annual charge-off losses in the U.S. could be closer to $11 billion.3 Additionally, organizations lose time and resources on collection efforts if they do not identify the SID fraud.  Those estimates are only for unsecured U.S. credit products. But fraudsters use synthetic identities to take out secured loans, including auto loans.   As part of schemes used to steal relief funds during the pandemic, criminals used synthetic identities to open demand deposit accounts to receive funds. These accounts can be used to launder money from other sources and commit peer-to-peer payment fraud. Deposit account holders are also a primary source of cross-marketing for some financial institutions. Criminals can take advantage of vulnerable onboarding processes for deposit accounts where there’s low risk to the institution and receive offers for lending products. Building a successful SID prevention strategy Having an effective SID prevention strategy is more crucial than ever for organizations. Aside from fraud losses, consumers listed identity theft as their top concern when conducting activities online. And while 92% of businesses have an identity verification strategy in place, 63% of consumers are "somewhat confident" or "not very confident" in businesses' ability to accurately identify them online. Read: Experian's 2023 Identity and Fraud Report Many traditional fraud models and identity verification methods are not designed to detect fake people. And even a step up to a phone call for verification isn't enough when the fraudster will be the one answering the phone. Criminals also quickly respond when organizations update their fraud detection methods by looking for less-protected targets. Fraudsters have even signed their SIDs up for social media accounts and apps with low verification hurdles to help their SIDs pass identity checks.5  Understand synthetic identity risks across the lifecycle  Synthetic Identities are dynamic. When lending criteria is tightened to synthetics from opening new accounts, they simply come back when they can qualify. If waiting brings a higher credit line, they’ll wait. It’s important to recognize that synthetic identity isn’t a new account or a portfolio management problem - it’s both.    Use analytics that are tailored to synthetic identity  Many of our customers in the financial services space have been trying to solve synthetic identity fraud with credit data. There’s a false sense of security when criteria is tightened and losses go down—but the losses that are being impacted tend to not be related to credit. A better approach to synthetic ID fraud leverages a larger pool of data to assess behaviors and data linkages that are not contained in traditional credit data.  You can then escalate suspicious accounts to require additional reviews, such as screening through the Social Security Administration's Electronic Consent Based SSN Verification (eCBSV) system or more stringent document verification.  Find a trusted partner  Experian's interconnected data and analytics platforms offer lenders turnkey identity and synthetic identity fraud solutions. In addition, lenders can take advantage of the risk management system and continuous monitoring to look for signs of SIDs and fraudulent activity, which is important for flagging accounts after opening. These tools can also help lenders identify and prevent other common forms of fraud, including account takeovers, e-commerce fraud, child identity theft fraud and elderly fraud. Learn more about our synthetic identity fraud solutions. Learn more 1Federal Reserve Bank (2021). Defining Synthetic Identity Fraud 2Aite Novarica (2022). Synthetic Identity Fraud: Solution Providers Shining Light into the Darkness 3Experian (2022). Preventing synthetic identity fraud 4The Federal Reserve (2022). Synthetic Identity Fraud: What Is it and Why You Should Care? 5Experian (2022). Preventing synthetic identity fraud 

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/

Spoiler alert: Gen AI is everywhere, including the top of Experian’s list of fraud trends 2024. “The speed and complexity of fraud attacks due to new technology and sophisticated fraudsters is leaving both businesses and consumers at risk in 2024,” said Kathleen Peters, chief innovation officer at Experian Decision Analytics in North America. “At Experian, we’re constantly innovating to deliver data-driven solutions to help our customers fight fraud and to protect the consumers they serve.” To deter fraudulent activity in 2024, businesses and consumers must get tactical for their fraud fighting strategies. And for businesses, the need for more sophisticated fraud protection solutions leveraging data and technology is greater than ever before. Experian suggests consumers and businesses watch out for these big five rounding out our fraud trends 2024. Generative AI: Generative AI accelerates DIY fraud: Experian predicts fraudsters will use generative AI to accelerate “do-it-yourself” fraud ranging from deepfake content – think emails, voice and video – as well as code creation to set up scam websites. A previous blog post of ours highlighted four types of generative AI used for fraud, including fraud automation at scale, text content generation, image and video manipulation and human voice generation. The way around it? Fight AI fraud with AI as part of a multilayered fraud prevention solution. Fraud at bank branches: Bank branches are making a comeback. A growing number of consumers prefer visiting bank branches in person to open new accounts or get financial advice with the intent to conduct safer transactions. However, face-to-face verification is not flawless and is still susceptible to human error or oversight. According to an Experian report, 85% of consumers report physical biometrics as the most trusted and secure authentication method they’ve recently encountered, but the measure is only currently used by 32% of businesses to detect and protect against fraud. Retailers, beware: Not all returns are as they appear. Experian predicts an uptick in cases where customers claim to return their purchases, only for the business to receive an empty box in return. Businesses must be vigilant with their fraud strategy in order to mitigate risk of lost goods and revenue. Synthetic identity fraud will surge: Pandemic-born synthetic identities may have been dormant, but now have a few years of history, making it easier to elude detection leading to fraudsters using those dormant accounts to “bust out” over the next year. Cause-related and investment deception: Fraudsters are employing new methods that strike an emotional response from consumers with cause-related asks to gain access to consumers’ personal information. Experian predicts that these deceptive cause-related methods will surge in 2024 and beyond. How businesses and consumers feel about fraud in 2024 According to an Experian report, over half of consumers feel they’re more of a fraud target than a year ago and nearly 70% of businesses report that fraud losses have increased in recent years. Business are facing mounting challenges – from first-party fraud and credit washing to synthetic identity and the yet-to-be-known impacts generative AI may have on fraud schemes. Synthetic identity fraud has been mentioned in multiple Experian Fraud Forecasts and the threat is ever growing. As technology continues to enhance consumers’ connectedness, it also heightens the stakes for various fraud attacks. As highlighted by this list of fraud trends 2024, the ways that fraudsters are looking to deceive is increasing from all angles. “Now more than ever, businesses need to implement a multilayered approach to their identity verification and fraud prevention strategies that leverages the latest technology available,” said Peters. Consumers are increasingly at risk from sophisticated fraud schemes. Increases in direct deposit account and check fraud, as well as advanced technologies like deepfakes and AI-generated phishing emails, put consumers in a precarious position. The call to action for consumers is to remain vigilant of seemingly authentic interactions. Experian can help with your fraud strategy To learn more about Experian’s fraud prevention solutions, please visit https://www.experian.com/business/solutions/fraud-management.  Download infographic Watch Future of Fraud webinar

Review of Findings & Front-line Insights Panel Participants: Richard Goldberg (Moderator) – Constangy, Brooks, Smith & Prophete, LLP Michael Bruemmer – Experian Sean Renshw – RSM US, LLP Mark Greisiger – NetDiligence About NetDiligence Cyber Claims Study It is NetDiligence’s 13th year of doing this Cyber Claims Study. A total of 9,028 claims were analyzed during the past five years 2018-2022.An observation from the over 9,000 Cyber Claims (5000 of which are brand new claims this past year in 2023) analyzed is while many of the categories over the last five years have remained the same, the data has changed, sometimes dramatically. About Experian We provide call center coverage, notification coverage, as well as, identity theft protection, and all the consumer resolutions that go along with it for about 5000 data breaches every year, and I was delighted to be on the panel. Key Insights Experian has proudly sponsored the annual NetDiligence Cyber Claims Study for three years. During this time, I’ve witnessed companies adapt and transform their operations to confront the growing tide of cyber threats. The evolution of their infrastructure to anticipate and respond to these challenges has been remarkable and necessary. However, despite my front-row seat in this fast-changing landscape, the results of each study never fail to surprise and intrigue me. The insights from the latest study, conducted in 2023, continue to shape our understanding of the evolving cyber landscape. Ransomware’s Dominance Mark kicked off the discussion by shedding light on the escalating costs associated with cyber incidents. In 2022, the average incident cost for SME organizations remained stable at $169,000 (similar to the combined five-year window from 2018 to 2022 at about 175,000). However, there was a substantial increase for large companies, reaching $20.3 million in 2022 (and if you look at the five-year average, it was about 13 million). This surge raised eyebrows and set the stage for a deep dive into ransomware, a leading cause of concern. Examining Ransomware Trends The conversation swiftly shifted to ransomware, a pervasive threat in the cyber insurance landscape. As I stated, at Experian we see a correlation between the rise in ransomware and third-party breaches. Most of the industry experts on the panel participate in a Ransomware Advisory Group together. Mark brought up a good insight from our advisory group on the brazen tactics employed by threat actors lately, showcasing their intimate knowledge of the cyber insurance world. Business Sectors Under Siege Richard and Sean added to the discussion the top ten business sectors affected by ransomware, with professional services leading the pack. The impact on technology, with a payout of $830,000, stood out as well. Beyond Ransomware The conversation broadened to encompass other types of losses, such as social engineering and business email compromise. The focus on business interruption emerged as a key concern for cyber insurance claims, with the industry grappling with criminal acts versus non-criminal acts. Looking Ahead As the discussion unfolded, industry experts, including myself, expressed eagerness to anticipate the future cyber landscape. Predictions range from the industry mutating to the emergence of new players in the nation-state game. The role of artificial intelligence and innovative solutions from new vendors becomes a focal point of interest. In conclusion, the NetDiligence Cyber Claims Study 2023 Report paints a vivid picture of the challenges and transformations within the cyber insurance domain. The increasing sophistication of threat actors, coupled with evolving business strategies, sets the stage for continuous adaptation and innovation in the fight against cyber threats. As we look ahead, the resilience of businesses and the collaboration between industry stakeholders will play a pivotal role in shaping the cybersecurity landscape. I invite you to access the report and view the discussion replay for a deeper understanding of the challenges and transformations within the cyber insurance claims domain. Get NetDiligece Cyber Claims Study resources on-demand now! Download the report Watch the webinar NetDiligence’s latest Cyber Claims Study and Webinar, sponsored by Experian Data Breach, is available on-demand. This report serves as a resounding call to action, prompting businesses to ready themselves against cyber threats. Dive in to get insights and stay one step ahead of cyber adversaries.

This article was updated on February 12, 2024. The Buy Now, Pay Later (BNPL) space has grown massively over the last few years. But with rapid growth comes an increased risk of fraud, making "Buy Now, Pay Never" a crucial fraud threat to watch out for in 2024 and beyond. What is BNPL? BNPL, a type of short-term financing, has been around for decades in different forms. It's attractive to consumers because it offers the option to split up a specific purchase into installments rather than paying the full total upfront. The modern form of BNPL typically offers four installments, with the first payment at the time of purchase, as well as 0% APR and no hidden fees. According to an Experian survey, consumers cited managing spending (34%), convenience (31%), and avoiding interest payments (23%) as main reasons for choosing BNPL. Participating retailers generally offer BNPL at point-of-sale, making it easy for customers to opt-in and get instantly approved. The customer then makes a down payment and pays off the installments from their preferred account. BNPL is on the rise The fintech and online-payment-driven world is seeing a rise in the popularity of BNPL. According to Experian research, 3 in 4 consumers have used BNPL in 2023, with 11% using BNPL weekly to make purchases. The interest in BNPL also spans generations — 36% of Gen Z, 43% of Millennials, 32% of Gen X, and 12% of Baby Boomers have used this payment method. The risks of BNPL While BNPL is a convenient, easy way for consumers to plan for their purchases, experts warn that with lax checkout and identity verification processes it is a target for digital fraud. Experian predicts an uptick in three primary risks for BNPL providers and their customers: identity theft, first-party fraud, and synthetic identity fraud. WATCH: Fraud and Identity Challenges for Fintechs Victims of identity theft can be hit with charges from BNPL providers for products they have never purchased. First-party and synthetic identity risks will emerge as a shopper's buying power grows and the temptation to abandon repayment increases. Fraudsters may use their own or fabricated identities to make purchases with no intent to repay. This leaves the BNPL provider at the risk of unrecoverable monetary losses and can impact the business' risk tolerance, causing them to narrow their lending band and miss out on properly verified consumers. An additional risk lies with fraudsters who may leverage account takeover to gain access to a legitimate user's account and payment information to make unauthorized purchases. READ: Payment Fraud Detection and Prevention: What You Need to Know Mitigating BNPL risks Luckily, there are predictive credit, identity verification, and fraud prevention tools available to help businesses minimize the risks associated with BNPL. Paired with the right data, these tools can give businesses a comprehensive view of consumer payments, including the number of outstanding BNPL loans, total BNPL loan amounts, and BNPL payment status, as well as helping to detect and apply the relevant treatment to different types of fraud. By accurately identifying customers and assessing risk in real-time, businesses can make confident lending and fraud prevention decisions. To learn more about how Experian is enabling the protection of consumer credit scores, better risk assessments, and more inclusive lending, visit us or request a call. And keep an eye out for additional in-depth explorations of our Future of Fraud Forecast. Learn more Future of Fraud Forecast