Tag: fraud prevention

Income and employment verification fraud is surging in the tenant screening industry, putting traditional verification methods under intense pressure. As economic uncertainty grows and document forgery becomes more sophisticated, it's clear that legacy processes are no longer sufficient. Recent findings highlight the urgency for change. According to the NMHC Pulse Survey, 93.3% of property managers reported encountering fraud in the past year, with 84.3% citing falsified paystubs and fake employment references as the most common tactics. As AI-generated forgeries become increasingly convincing and accessible, relying solely on manual review is proving inadequate. A Shift in Strategy: Toward Smarter Income and Employment Verification Historically, tenant screeners have relied on methods such as manual document review, direct employer contact, payroll APIs, and verification of assets (VOA). While these remain important, they are no longer capable of keeping pace with today’s verification challenges. In response, many screening companies are exploring new income verification tools that offer improved fraud prevention, lower operational costs, and faster turnaround. These innovations include layered approaches that combine observed data, permissioned uploads, and automated fraud detection technologies. Introducing Observed Data in Tenant Screening One emerging solution in the fight against rental application fraud is the use of observed data during tenant screening. This method uses [KA1] collectively sourced insights to assess whether an applicant’s income and employment claims are likely to be accurate. Observed data is drawn from a consortium of financial institutions, lenders, and dealerships. It includes a confidence grade based on actual financial behavior, such as account activity and application history, which are then compiled and analyzed to form a current view of income and employment patterns. [CC2]  These insights are drawn from the latest self-reported data submitted by consumers through loan applications, providing screening companies with a dynamic, data-driven benchmark for verification. Although this method is not FCRA-compliant and cannot be used to approve or deny applications, it is highly effective as an early step in the screening process. A confidence score is often included to help screeners assess how closely an applicant’s stated information aligns with observed trends and can help screening companies to better assess their prioritization queue to determine if more data points are needed. Why Observed Data Matters To combat fraud without driving up costs or slowing down the tenant screening process, screening companies need reliable, efficient tools. Observed data supports this need by offering a faster, more scalable approach to assessing risk. Key benefits include: Early detection of discrepancies in reported income or employment The ability to prioritize high-risk applications for further review A more cost-effective alternative before committing to premium verification services For instance, if an applicant has a strong credit report and clean background check, and observed data supports their stated income, further verification may be unnecessary. If inconsistencies are flagged, screening companies can escalate to tools such as AI document analysis or direct outreach. Fraud Prevention Through Smarter Workflows The use of observed data also aligns with a broader shift toward AI document fraud detection and layered verification strategies. Instead of applying the same tools to every application, screening companies can now implement decision trees that use lower-cost tools first, escalating only when risk or uncertainty increases. This adaptive approach is particularly relevant as screener companies strive to improve accuracy and efficiency at scale. By deploying observed data as a first step, tenant screening professionals can better allocate resources while remaining vigilant against fraud Future Proofing Verificaiton As the income and employment verification landscape evolves, screening companies must move beyond legacy methods and adopt tools that are responsive to today’s challenges. Observed data provides a scalable, low friction starting point that supports smarter decision-making and better fraud detection. Coming to our next blog: We will explore how manual research verifications and AI-powered document upload solutions enhance the effectiveness of modern income verification tools, creating a more resilient and adaptable tenant screening process.  

In today’s digital lending landscape, fraudsters are more sophisticated, coordinated, and relentless than ever. For companies like Terrace Finance — a specialty finance platform connecting over 5,000 merchants, consumers, and lenders — effectively staying ahead of these threats is a major competitive advantage. That is why Terrace Finance partnered with NeuroID, a part of Experian, to bring behavioral analytics into their fraud prevention strategy. It has given Terrace’s team a proactive, real-time defense that is transforming how they detect and respond to attacks — potentially stopping fraud before it ever reaches their lending partners. The challenge: Sophisticated fraud in a high-stakes ecosystem Terrace Finance operates in a complex environment, offering financing across a wide range of industries and credit profiles. With applications flowing in from countless channels, the risk of fraud is ever-present. A single fraudulent transaction can damage lender relationships or even cut off financing access for entire merchant groups. According to CEO Andy Hopkins, protecting its partners is a top priority for Terrace:“We know that each individual fraud attack can be very costly for merchants, and some merchants will get shut off from their lending partners because fraud was let through ... It is necessary in this business to keep fraud at a tolerable level, with the ultimate goal to eliminate it entirely.” Prior to NeuroID, Terrace was confident in its ability to validate submitted data. But with concerns about GenAI-powered fraud growing, including the threat of next-generation fraud bots, Terrace sought out a solution that could provide visibility into how data was being entered and detect risk before applications are submitted. The solution: Behavioral analytics from NeuroID via Experian After integrating NeuroID through Experian’s orchestration platform, Terrace gained access to real-time behavioral signals that detected fraud before data was even submitted. Just hours after Terrace turned NeuroID on, behavioral signals revealed a major attack in progress — NeuroID enabled Terrace to respond faster than ever and reduce risk immediately. “Going live was my most nerve-wracking day. We knew we would see data that we have never seen before and sure enough, we were right in the middle of an attack,” Hopkins said. “We thought the fraud was a little more generic and a little more spread out. What we found was much more coordinated activities, but this also meant we could bring more surgical solutions to the problem instead of broad strokes.” Terrace has seen significant results with NeuroID in place, including: Together, NeuroID and Experian enabled Terrace to build a layered, intelligent fraud defense that adapts in real time. A partnership built on innovation Terrace Finance’s success is a testament to what is  possible when forward-thinking companies partner with innovative technology providers. With Experian’s fraud analytics and NeuroID’s behavioral intelligence, they have built a fraud prevention strategy that is proactive, precise, and scalable. And they are not stopping there. Terrace is now working with Experian to explore additional tools and insights across the ecosystem, continuing to refine their fraud defenses and deliver the best possible experience for genuine users. “We use the analogy of a stream,” Hopkins explained. “Rocks block the flow, and as you remove them, it flows better. But that means smaller rocks are now exposed. We can repeat these improvements until the water flows smoothly.” Learn more about Terrace Finance and NeuroID Want more of the story? Read the full case study to explore how behavioral analytics provided immediate and long-term value to Terrace Finance’s innovative fraud prevention strategy. Read case study

In today’s digital payments landscape, fraudsters are constantly developing new tactics to exploit vulnerabilities. One of the most common credit card schemes financial institutions and merchants face are BIN attacks. But what exactly is a BIN attack, and how does BIN attack fraud work? What is a BIN attack? BIN attacks, a type of card not present fraud, target the Bank Identification Number (BIN) ­— the first six to eight digits of a credit or debit card number that identify the issuing financial institution. Fraudsters use these digits to systematically generate and test potential card number combinations. The goal of a BIN attack is to discover valid card numbers that can be used for fraudulent transactions. Because BINs are publicly available and consistent across card issuers, they provide a predictable framework for attackers. How does it differ from other types of payment fraud? Payment fraud takes many forms, but BIN attacks stand apart because of their scale and automation. Card testing fraud vs. BIN attacks: Both involve criminals running authorization attempts to identify valid card details. However, card testing typically uses data from a single stolen card, while BIN attacks systematically generate thousands of possible card numbers from a known BIN range. Account takeover fraud vs. BIN attacks: In an account takeover, fraudsters gain access to a customer’s existing account, often through phishing or stolen login credentials. BIN attacks don’t require account access — instead, they exploit card number patterns to guess valid accounts. What are the consequences of a BIN attack? BIN attacks don’t just result in stolen card numbers — they create wide-ranging business risks that can impact operations, revenue and customer trust. For financial institutions and merchants, the ripple effects can be significant: High transaction volumes: BIN attacks are carried out using automated scripts or bots that fire off thousands of transaction attempts per minute. This traffic can overwhelm payment systems, slow down processing and disrupt the checkout experience for legitimate customers. Increased chargebacks: Once fraudsters identify valid cards, they make unauthorized purchases that often result in chargebacks. Both merchants and issuers absorb these losses — merchants lose revenue, while issuers reimburse cardholders. Network and processing costs: Every transaction attempt — even those declined during a BIN attack — still incurs network and processing fees. Merchants and issuers can end up paying for thousands of authorization requests, draining resources. Reputational damage: Today’s consumers expect seamless and secure payments. If they experience frequent declines, blocked cards or fraudulent activity, their trust in the institution or merchant erodes. How to protect against BIN attack fraud Mitigating BIN attacks requires a proactive, layered defense strategy. Financial institutions and merchants should consider: Advanced fraud detection and analytics: BIN attacks generate massive volumes of fraudulent traffic. By leveraging AI-driven analytics and machine learning, institutions and merchants can monitor for unusual transaction patterns, velocity spikes and bot-driven activity. Identity and device intelligence: Fraudsters often hide behind bots, stolen IP addresses and compromised devices. With identity verification and device intelligence solutions, merchants and institutions can better determine whether a transaction is coming from a legitimate customer or a fraudster testing card details. Multi-factor authentication (MFA): BIN attacks succeed on speed and automation, firing off thousands of transactions. MFA can help disrupt this process by requiring additional proof of identity from the customer, such as facial recognition or one-time passcodes. Credit card authentication: BIN attacks exploit the gap between payment credentials and the identity of the person using them. A solution like Experian LinkTM seamlessly connects the payment instrument with the digital identity presented for payment, helping merchants to reduce false declines, fraud and operating expenses. Build a stronger defense against BIN attacks BIN attacks are a growing threat in today’s digital payments ecosystem. But with the right safeguards in place, organizations can stay ahead. Learn how Experian can help you strengthen your fraud defenses to reduce losses and protect customer trust. Learn more

Lending fraud – what is it? Lending fraud is a deceptive practice in which individuals or entities intentionally provide false or misleading information during the loan application process to secure credit or financial gain. This can include using fake identities, inflating income, forging documentation, or applying for loans without the intention of repayment.   The consequences are significant: lenders suffer financial losses, consumers experience identity theft or damaged credit scores, and the economic system bears increased risk and regulatory scrutiny. Loan fraud is a growing concern across consumer, commercial, and mortgage lending sectors, affecting institutions of all sizes. How do I safeguard my organization from loan fraud?    Preventing lending fraud is a complex, ongoing challenge that requires a multi-layered and holistic approach. As fraud tactics become more sophisticated, especially with the rise of generative AI and digital lending channels, financial institutions must continually evolve their defenses.  Strong identity verification is the first line of defense. Lenders should implement advanced authentication tools beyond basic KYC (Know Your Customer) checks. This includes biometric verification, document verification, and device intelligence —technologies that assess the authenticity of the user and the device used during the application process. These tools can help detect synthetic identities — false identities created using a blend of real and fabricated information — increasingly used in loan fraud schemes.  Another crucial strategy is real-time data analytics and behavioral monitoring. Lenders can quickly identify anomalies that may indicate fraudulent activity by analyzing applicant behavior, credit history, device usage patterns, and geolocation data in real time. For example, if an applicant submits multiple loan applications from different IP addresses in a short time frame, that could raise a red flag for potential lending fraud.  Employee training and awareness are also essential. Frontline staff must be equipped to identify warning signs, such as inconsistencies in application documents or rushed, high-pressure loan requests. Regular fraud prevention training helps employees stay alert and aligned with the organization’s risk management protocols.  57% of financial institutions reported direct fraud losses exceeding $500,000 in the past year, with 25% exceeding $1 million.1 Consumers reported losing more than $12.5 billion to fraud in 2024, which represents a 25% increase over the prior year.2 In addition, robust internal controls and auditing mechanisms are critical in prevention. Organizations should regularly audit loan origination processes and investigate unusual approval patterns to detect insider fraud or systemic vulnerabilities.  Finally, consumer education is a vital, often overlooked, aspect of combating loan fraud. Lenders should provide resources to help customers understand the risks of identity theft, encourage them to monitor their credit reports regularly, and empower them to report any suspicious activity. A well-informed customer base can be a valuable early warning system for fraud.  With digital lending becoming the norm, preventing lending fraud means staying ahead of increasingly tech-savvy fraudsters. Leveraging data, technology, and education together builds a stronger, more resilient fraud defense framework.  Lending fraud + Experian – How we can help  With access to the industry’s most advanced fraud detection and identity verification tools, partnering with us gives you a potent edge in combating lending fraud. As a global leader in data, analytics, and technology, our comprehensive and accurate sets of consumer information enable you to spot risks that might be invisible through conventional means. Our approach combines rich data insights with powerful machine learning algorithms, delivering fraud prevention tools that are intelligent, scalable, and highly adaptive.  Our fraud detection technologies are designed to protect every stage of the lending lifecycle. From real-time identity verification and multi-factor authentication solutions to behavioral biometrics and device intelligence, so you can detect synthetic identities, manipulated applications, and other forms of loan fraud before they lead to financial loss.  In an era where trust is currency, partnering with us doesn’t just help protect against lending fraud — it enhances your reputation as a secure, responsible lender. You gain the confidence of your customers by providing safe, streamlined lending experiences while meeting compliance requirements and reducing operational risk. With us, you’re not just reacting to fraud—you’re anticipating it, preventing it, and confidently growing your business.  Learn more 1State of Fraud Benchmark Report. Alloy. (2024). 2New FTC Data Show a Big Jump in Reported Losses to Fraud to $12.5 Billion in 2024. Federal Trade Commission. (2025, March 10). 

Experian is proud to be a Thought Leadership Sponsor at this year’s Federal Identity Forum & Expo (FedID)! We’re bringing the latest innovations in fraud prevention, identity verification, and behavioral analytics – all designed to help government agencies protect access, ensure trust, and stay ahead of evolving threats.

Now in its tenth year, Experian’s U.S. Identity and Fraud Report continues to uncover the shifting tides of fraud threats and how consumers and businesses are adapting. Our latest edition sheds light on a decade of change and unveils what remains consistent: trust is still the cornerstone of digital interactions. This year’s report draws on insights from over 2,000 U.S. consumers and 200 businesses to explore how identity, fraud and trust are evolving in a world increasingly shaped by generative artificial intelligence (GenAI) and other emerging technologies. Highlights: Over a third of companies are using AI, including generative AI, to combat fraud. 72% of business leaders anticipate AI-generated fraud and deepfakes as major challenges by 2026. Nearly 60% of companies report rising fraud losses, with identity theft and payment fraud as top concerns. Digital anxiety persists with 57% of consumers worried about doing things online. Ready to go deeper? Explore the full findings and discover how your organization can lead with confidence in an evolving fraud landscape. Download report Watch on-demand webinar Read press release  

Powered by GenAI and increasingly accessible fraud tools, fraud threats are evolving faster than ever. Traditional fraud detection solutions alone are struggling to keep up with evolving fraud rings, fraud bots, and attack strategies, pushing businesses to explore smarter, more adaptive defenses. That’s why many organizations are turning to User and Entity Behavior Analytics (UEBA) as protection against growing threats, especially internal ones. But what exactly is UEBA, and how does it differ from other solutions, like behavioral analytics?

Bot fraud has long been a major concern for digital businesses, but evolving attacks at all stages in the customer lifecycle have overshadowed an ever-present issue: click fraud. Click fraud is a cross-departmental challenge for businesses, and stopping it requires a level of insight and understanding that many businesses don’t yet have. It’s left many fraud professionals asking: What is click fraud? Why is it so dangerous? How can it be prevented? What is click fraud? A form of bot fraud, click fraud occurs when bots drive fraudulent clicks to websites, digital ads, and emails. Click fraud typically exploits application flows or digital advertising; traffic from click bots appears to be genuine but is actually fraudulent, incurring excessive costs through API calls or ad clicks. These fraudulent clicks won’t result in any sales but will reveal sensitive information, inflate costs, and clutter data. What is the purpose of click fraud? It depends on the target. We've seen click bots begin (but not complete) insurance quotes or loan applications, gathering information on competitors’ rates. In other cases, fraudsters use click fraud to drive artificial clicks to ads on their sites, resulting in increased revenue from PPC/CPC advertising. The reasons behind click fraud vary widely, but, regardless of its intent, the impacts of it affect businesses deeply. The dangers of click fraud On the surface, click fraud may seem less harmful than other types of fraud. Unlike application fraud and account takeover fraud, consumers’ data isn’t being stolen, and fraud losses are relatively minuscule. But click fraud can still be detrimental to businesses' bottom lines: every API call incurred by a click bot is an additional expense, and swarms of click bots distort data that’s invaluable to fraud attack detection and customer acquisition. The impact of click fraud extends beyond that, though. Not only can click bots gather sensitive data like insurance quotes, but click fraud can also be a gateway to more insidious fraud schemes. Fraud rings are constantly looking for vulnerabilities in businesses’ systems, often using bots to probe for back-door entrances to applications and ways to bypass fraud checks. For example: if an ad directs to an unlisted landing page that provides an alternate entry to a business’s ecosystem, fraudsters can identify this through click fraud and use bots to find vulnerabilities in the alternate application process. In doing so, they lay the groundwork for larger attacks with more tangible losses. Keys to click fraud prevention Without the right tools in place, modern bots can appear indistinguishable from humans — many businesses struggle to identify increasingly sophisticated bots on their websites as a result. Allowing click fraud to remain undetected can make it extremely difficult to know when a more serious fraud attack is at your doorstep. Preventing click fraud requires real-time visibility into your site’s traffic, including accurate bot detection and analysis of bot behavior. It’s one of many uses for behavioral analytics in fraud detection: behavioral analytics identifies advanced bots pre-submit, empowering businesses to better differentiate click fraud from genuine traffic and other fraud types. With behavioral analytics, bot attacks can be detected and stopped before unnecessary costs are incurred and sensitive information is revealed. Learn more about our behavioral analytics for fraud detection.

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/

March is a time when the idea of luck is in the air, with St. Patrick’s Day celebrations and hopeful thoughts of pots of gold at the end of the rainbow. But while the "Luck of the Irish" may be a fun idea, scammers take advantage of this sentiment to exploit people through fraudulent lottery scams and prize schemes. Take, for example, the so-called "Luck of the Irish" scams that flood inboxes and phone lines every March. You might receive a message claiming you have won the "Irish National Lottery" or another grand prize, but there is a catch—you need to pay fees or provide sensitive personal information to claim it. Before you know it, the scammers have vanished with your money or used your data for further fraud. Red flags of lottery scams Financial institutions can help protect clients by educating them on the warning signs of fraudulent lottery schemes. According to the FTC website, here are three clear indicators that a prize is too good to be true: You must pay to claim your winnings – Legitimate lotteries do not require winners to pay taxes, fees, or handling charges upfront. If you are asked to send money to claim a prize, it is a scam. You never entered the lottery – If you did not buy a ticket or enter a sweepstake, you cannot win. Any message saying otherwise is a red flag. They ask for personal or financial information – No legitimate lottery will ask for your Social Security number, bank details, or credit card information to process winnings. How scammers operate Lottery scammers use a variety of tactics to trick victims, including: Impersonating well-known brands or government agencies to appear credible. Sending fake checks that later bounce after victims have sent money. Using high-pressure tactics, such as claiming the offer is time sensitive. Requesting payment through difficult-to-trace methods like gift cards, wire transfers, or cryptocurrency. How financial institutions can help clients stay safe Banks and financial institutions play a critical role in protecting their clients from falling victim to lottery scams. Here is how they can help: Educate clients: Provide fraud awareness materials explaining common scams, red flags, and safe financial practices. Implement transaction monitoring: Monitor for suspicious transactions, especially those involving large wire transfers or unusual payments to unknown entities. Encourage multi-factor authentication: Strengthening account security can prevent unauthorized transactions if scammers obtain a victim’s personal information. Offer a safe reporting channel: Encourage clients to report suspected scams so the institution can take preventive action and share warnings with others. Final thoughts Winning the lottery may be a dream for many, but no real jackpot comes with a catch. Financial institutions can be the first line of defense by helping clients recognize scams before they lose money. The best approach? Remind clients that the only "pot of gold" worth chasing is the one they have earned and safeguarded through smart financial habits. And finally, check out this educational tune with a catchy rhythm, designed to raise awareness about scams. Learn more

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

Fraud never sleeps, and neither do the experts working to stop it. That’s why we’re thrilled to introduce Meet the Maker, our new video series spotlighting the brilliant minds behind Experian’s cutting-edge fraud solutions. In our first episode, Matt Ehrlich, Senior Director of Identity and Fraud Product Management, and Andrea Nighswander, Senior Director of Global Solution Strategy, share how they use data, advanced analytics, and deep industry expertise to stay ahead of fraudsters. With 35+ years of combined experience, these fraud-fighting veterans know exactly what it takes to keep bad actors at bay. Watch now for an exclusive look at the minds shaping the future of fraud prevention.    Stay tuned for more episodes featuring the visionaries driving fraud innovation.

As Valentine’s Day approaches, hearts will melt, but some will inevitably be broken by romance scams. This season of love creates an opportune moment for scammers to prey on individuals feeling lonely or seeking connection. Financial institutions should take this time to warn customers about the heightened risks and encourage vigilance against fraud. In a tale as heart-wrenching as it is cautionary, a French woman named Anne was conned out of nearly $855,000 in a romance scam that lasted over a year. Believing she was communicating with Hollywood star Brad Pitt; Anne was manipulated by scammers who leveraged AI technology to impersonate the actor convincingly. Personalized messages, fabricated photos, and elaborate lies about financial needs made the scam seem credible. Anne’s story, though extreme, highlights the alarming prevalence and sophistication of romance scams in today’s digital age. According to the Federal Trade Commission (FTC), nearly 70,000 Americans reported romance scams in 2022, with losses totaling $1.3 billion—an average of $4,400 per victim. These scams, which play on victims’ emotions, are becoming increasingly common and devastating, targeting individuals of all ages and backgrounds. Financial institutions have a crucial role in protecting their customers from these schemes. The lifecycle of a romance scam Romance scams follow a consistent pattern: Feigned connection: Scammers create fake profiles on social media or dating platforms using attractive photos and minimal personal details. Building trust: Through lavish compliments, romantic conversations, and fabricated sob stories, scammers forge emotional bonds with their targets. Initial financial request: Once trust is established, the scammer asks for small financial favors, often citing emergencies. Escalation: Requests grow larger, with claims of dire situations such as medical emergencies or legal troubles. Disappearance: After draining the victim’s funds, the scammer vanishes, leaving emotional and financial devastation in their wake. Lloyds Banking Group reports that men made up 52% of romance scam victims in 2023, though women lost more on average (£9,083 vs. £5,145). Individuals aged 55-64 were the most susceptible, while those aged 65-74 faced the largest losses, averaging £13,123 per person. Techniques scammers use Romance scammers are experts in manipulation. Common tactics include: Fabricated sob stories: Claims of illness, injury, or imprisonment. Investment opportunities: Offers to “teach” victims about investing. Military or overseas scenarios: Excuses for avoiding in-person meetings. Gift and delivery scams: Requests for money to cover fake customs fees. How financial institutions can help Banks and financial institutions are on the frontlines of combating romance scams. By leveraging technology and adopting proactive measures, they can intercept fraud before it causes irreparable harm. 1. Customer education and awareness Conduct awareness campaigns to educate clients about common scam tactics. Provide tips on recognizing fake profiles and unsolicited requests. Share real-life stories, like Anne’s, to highlight the risks. 2. Advanced data capture solutions Implement systems that gather and analyze real-time customer data, such as IP addresses, browsing history, and device usage patterns. Use behavioral analytics to detect anomalies in customer actions, such as hesitation or rushed transactions, which may indicate stress or coercion. 3. AI and machine learning Utilize AI-driven tools to analyze vast datasets and identify suspicious patterns. Deploy daily adaptive models to keep up with emerging fraud trends. 4. Real-time fraud interception Establish rules and alerts to flag unusual transactions. Intervene with personalized messages before transfers occur, asking “Do you know and trust this person?” Block transactions if fraud is suspected, ensuring customers’ funds are secure. Collaborating for greater impact Financial institutions cannot combat romance scams alone. Partnerships with social media platforms, AI companies, and law enforcement are essential. Social media companies must shut down fake profiles proactively, while regulatory frameworks should enable banks to share information about at-risk customers. Conclusion Romance scams exploit the most vulnerable aspects of human nature: the desire for love and connection. Stories like Anne’s underscore the emotional and financial toll these scams take on victims. However, with robust technological solutions and proactive measures, financial institutions can play a pivotal role in protecting their customers. By staying ahead of fraud trends and educating clients, banks can ensure that the pursuit of love remains a source of joy, not heartbreak. Learn more

Picture this: you’re sipping your morning coffee when an urgent email from your CEO pops up in your inbox, requesting sensitive information. Everything about it seems legit — their name, email address, even their usual tone. But here’s the twist: it’s not actually them. This is the reality of spoofing attacks. And these scenarios aren’t rare. According to the Federal Bureau of Investigation (FBI), spoofing/phishing is the most common type of cybercrime.¹   In these attacks, bad actors disguise their identity to trick individuals or systems into believing the communication is from a trusted source. Whether it’s email spoofing, caller ID spoofing, or Internet Protocol (IP) spoofing, the financial and reputational consequences can be severe. By understanding how these attacks work and implementing strong defenses, organizations can reduce their risk and protect sensitive information. Let’s break down the key strategies for staying one step ahead of cybercriminals. What is a spoofing attack? A spoofing attack occurs when a threat actor impersonates a trusted source to gain access to sensitive information, disrupt operations or manipulate systems. Common types of spoofing attacks include: Email spoofing: Fraudulent emails are carefully crafted to mimic legitimate senders, often including convincing details like company logos, real employee names, and professional formatting. These emails trick recipients into sharing sensitive information, such as login credentials or financial details, or prompt them to download malware disguised as attachments. For example, attackers might impersonate a trusted vendor to redirect payments or a senior executive requesting immediate access to confidential data. Caller ID spoofing: Attackers manipulate phone numbers to impersonate trusted contacts, making calls appear as if they are coming from legitimate organizations or individuals. This tactic is often used to extract sensitive information, such as account credentials, or to trick victims into making payments. For instance, a scammer might pose as a bank representative calling to warn of suspicious activity on an account, coercing the recipient into sharing private information or transferring funds. IP spoofing: IP addresses are falsified to disguise the origin of malicious traffic to bypass security measures and mask malicious activity. Cybercriminals use this method to redirect traffic, conduct man-in-the-middle attacks, where a malicious actor intercepts and possibly alters the communication between two parties without their knowledge, or overwhelm systems with distributed denial-of-service (DDoS) attacks. For example, attackers might alter the source IP address of a data packet to appear as though it is coming from a trusted source, making it easier to infiltrate networks and compromise sensitive data. These tactics are often used in conjunction with other cyber threats, such as phishing or bot fraud, making detection and prevention more challenging. How behavioral analytics can combat spoofing attacks Traditional fraud prevention methods provide a strong foundation but behavioral analytics adds a powerful layer to fraud stacks. By examining user behavior patterns, behavioral analytics enhances existing tools to: Detect anomalies that signal a spoofing attack. Identify bot fraud attempts, where automated scripts mimic legitimate users. Enhance fraud prevention solutions with friction-free, real-time insights. Behavioral analytics is particularly effective when paired with device and network intelligence and machine learning (ML) solutions. These advanced tools can continuously adapt to new fraud tactics, ensuring robust protection against evolving threats. The role of artificial intelligence (AI) and ML in spoofing attack prevention AI fraud detection is revolutionizing how organizations protect themselves from spoofing attacks. By leveraging AI analytics and machine learning solutions, organizations can: Analyze vast amounts of data to identify spoofing patterns. Automate threat detection and response. Strengthen overall fraud prevention strategies. These technologies are essential for staying ahead of cybercriminals, particularly as they increasingly use AI to perpetrate attacks.   Best practices for preventing spoofing attacks Organizations can take proactive steps to minimize the risk of spoofing attacks. Key strategies include: Implementing robust authentication protocols: Use multifactor authentication (MFA) to verify the identity of users and systems. Monitoring network traffic: Deploy tools that can analyze traffic for signs of IP spoofing or other anomalies. Leveraging behavioral analytics: Adopt advanced fraud prevention solutions that include behavioral analytics to detect and mitigate threats. Educating employees: Provide training on recognizing phishing attempts and other spoofing tactics. Partnering with fraud prevention experts: Collaborate with trusted providers like Experian to access cutting-edge solutions tailored to your needs. Why proactive prevention matters The financial and reputational damage caused by spoofing attacks can be devastating. Organizations that fail to implement effective prevention measures risk: Losing customer trust. Facing regulatory penalties. Incurring significant financial losses. Businesses can stay ahead of cyber threats by prioritizing spoofing attack prevention and leveraging advanced technologies such as behavioral analytics, AI fraud detection, and machine learning, Investing in fraud prevention solutions today is essential for protecting your organization’s future. How we help organizations detect spoofing attacks Spoofing attacks are an ever-present danger in the digital age. With tactics like IP spoofing and bot fraud becoming more sophisticated, businesses must adopt advanced strategies to safeguard their operations. Our comprehensive suite of fraud prevention solutions can help businesses tackle spoofing attacks and other cyber threats. Our advanced technologies like behavioral analytics, AI fraud detection and machine learning solutions, enable organizations to: Identify and respond to spoofing attempts in real-time. Detect anomalies and patterns indicative of fraudulent behavior. Strengthen defenses against bot fraud and IP spoofing. Ensure compliance with industry regulations and standards. Click ‘learn more’ below to explore how we can help protect your organization. Learn more 1 https://www.ic3.gov/AnnualReport/Reports/2023_IC3Report.pdf This article includes content created by an AI language model and is intended to provide general information. 

Financial identity theft is one of the biggest threats to a consumer’s financial wellness in today’s digital age.1 It occurs when someone steals their personal and financial information, such as their name, address, Social Security Number (SSN), credit card, or bank account numbers, and uses it to make unauthorized purchases or access their financial accounts without their permission. This can severely damage their credit score and financial standing, often taking significant time and effort to resolve. Financial identity theft can also harm organizations, taking a toll on bottom lines due to lost employee productivity and more severe consequences if the stolen identity exposes the organization to a data breach.   How financial identity theft happens  Financial identity theft can occur through various methods, including:  Skimming: Thieves use skimming devices at ATM machines or gas pumps to steal credit or debit card information. These devices can be hard to detect, making it easy for thieves to capture card details without the owner's knowledge.  Phishing: Scammers send emails or text messages that appear to be from a bank or other financial institution, asking for personal information. These messages often look legitimate, tricking consumers into providing sensitive data.  Social engineering: Thieves impersonate someone in authority to trick consumers into giving them their personal or financial information. This can happen over the phone, in person, or through digital communication.  Data breaches: Hackers gain access to large databases of personal and financial information through breaches at companies or organizations. This stolen data can then be sold or used to commit identity theft.  Stealing mail: Thieves steal mail from mailboxes or trash cans to obtain personal financial information. This can include bank statements, credit card offers, and other documents containing sensitive data.  Account takeover: Thieves use stolen personal information to access existing financial accounts. They can change account details, make unauthorized transactions, and even open new accounts, causing significant financial damage.  Protecting consumers from financial identity theft  Organizations play a crucial role in protecting their consumers from financial identity theft. A few strategies that organizations and financial institutions can implement to protect their customers include:  Implement strong authentication methods: Use multi-factor authentication (MFA) to add an extra layer of security. This requires users to provide two or more verification factors to gain access to their accounts, significantly reducing the risk of unauthorized access.  Educate consumers: Offer services to educate consumers about the risks of identity theft and provide tips on protecting their personal information. This includes advising them to use strong, unique passwords and to be cautious of phishing scams.   Monitor for suspicious activity: Use advanced monitoring systems to detect unusual activity in consumer accounts. This can help identify potential fraud early, ensuring that any threats are addressed before they cause significant harm.  Provide identity theft protection services: Offer services that monitor consumers' credit reports and alert them to suspicious activity. These services provide continuous oversight, helping consumers stay informed and protected against potential identity theft.  Why prioritizing financial wellness matters  Investing in your customers' financial wellness not only benefits them but also brings significant advantages to your organization. Some key benefits of helping your customers improve their financial wellness include:  Increased customer loyalty: Investing in your customers' financial wellness builds trust and strengthens your relationship, leading to higher customer retention and loyalty.  Reduced customer delinquency: Educating your customers on financial management can lead to fewer missed payments and defaults, reducing your risk and improving overall financial stability.  Higher customer engagement: Providing financial wellness resources and tools encourages your customers to engage more frequently with your organization, fostering a deeper connection.  Competitive advantage: Offering financial wellness programs can differentiate you from your competitors, making you more attractive to potential customers who value financial education and support.  Positive social impact: By helping your customers improve their financial health, you contribute to the overall economic well-being of the community, creating a positive social impact.  Reduced risk of data breach: Compromised employee credentials are one of the most common gateways for data breaches. By educating consumers on protecting their financial well-being, you also protect your organization from data breach threats.   Experian Partner Solutions: Protecting your customers   We offer a range of tools to help you support your customers on their financial wellness journey and defend against bad actors. With our partnership, you can offer your customers access to:  Credit and identity monitoring and alerts: Keep consumers engaged with reliable credit tools that monitor their credit reports and personal information to alert them of potential threats, such as dark web exposure or suspicious activity. Our advanced monitoring systems provide real-time alerts, helping your consumers take immediate action to protect their financial health.  Identity restoration: Provide peace of mind by helping your consumers reclaim their identity if they fall victim to identity theft. Our dedicated identity restoration specialists guide consumers through recovery, ensuring they regain control of their financial identity quickly and efficiently.  Data breach resolution: Manage consumer data breach and crisis incidents confidently, helping to mitigate the impact on affected individuals. We offer comprehensive breach response services, including notification, monitoring, and support, to help organizations handle breaches effectively and maintain consumer trust.  Credit education: Empower consumers with the knowledge and tools to understand and improve their credit health, building customer loyalty and supporting their journey towards better financial wellness. Our educational resources and personalized advice enable consumers to make informed financial decisions and achieve their financial goals.  Protecting against financial identity theft requires a collaborative effort between consumers and organizations. By partnering with us, you can offer comprehensive financial and identity protection solutions that engage, educate, and empower your customers to better manage their financial lives. This not only helps protect your customers, but also builds trust and loyalty, positioning your organization as a trusted advocate in financial wellness and identity protection.  Learn more View infographic 1Identity Theft Resource Center, Consumer Aftermath Report.  This article includes content created by an AI language model and is intended to provide general information.