Fraud & Identity Management

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  

In early 2025, European authorities shut down a cybercriminal operation called JokerOTP, responsible for over 28,000 phishing attacks across 13 countries. According to Forbes, the group used one-time password (OTP) bots to bypass two-factor authentication (2FA), netting an estimated $10 million in fraudulent transactions. It's just one example of how fraudsters are exploiting digital security gaps with AI and automation. What is an OTP bot? An OTP bot is an automated tool designed to trick users into revealing their one-time password, a temporary code used in multifactor authentication (MFA). These bots are often paired with stolen credentials, phishing sites or social engineering to bypass security steps and gain unauthorized access. Here’s how a typical OTP bot attack works: A fraudster logs in using stolen credentials. The user receives an OTP from their provider. Simultaneously, the OTP bot contacts the user via SMS, call or email, pretending to be the institution and asking for the OTP. If the user shares the OTP, the attacker gains control of the account. The real risk: account takeover OTP bots are often just one part of a larger account takeover strategy. Once a bot bypasses MFA, attackers can: Lock users out of their accounts Change contact details Drain funds or open fraudulent lines of credit Stopping account takeover means detecting and disrupting the attack before access is gained. That’s where strong account takeover/login defense becomes critical, monitoring suspicious login behaviors and recognizing high-risk signals early. How accessible are OTP bots? Mentions of OTP bots on dark web forums jumped 31% in 2024. Bot services offering OTP bypass tools were being sold for just $10 to $50 per attack. One user on a Telegram-based OTP bot platform reported earning $50,000 in a month.   The barrier to entry for fraudsters is low, and these figures highlight just how easy and profitable it is to launch OTP bot attacks at scale. The evolution of fraud bots OTP bots are one part of the rising wave of fraud bots. According to our report, The Fraud Attack Strategy Guide, bots accounted for 30% of fraud attempts at the beginning of 2024. By the end of the year, that number had risen to 80% — a nearly threefold increase in just 12 months. Today’s fraud bots are more dynamic and adaptive than before. They go beyond simple scripts, mimicking human behavior, shifting tactics in real time and launching large-scale bot attacks across platforms. Some bypass OTPs entirely or refine their tactics with each failed attempt. With generative AI in the mix, bot-based fraud is getting faster, cheaper and harder to detect. Effective fraud defense now depends on detecting intent, analyzing behavior in real time and stopping threats earlier in the process. Read this blog: Learn more about identifying and stopping bot attacks. A cross-industry problem OTP bots can target any organization that leverages 2FA, but the impact varies by sector. Financial services, fintech and buy now, pay later (BNPL) providers are top targets for OTP bot attacks due to high-value accounts, digital onboarding and reliance on 2FA. In one case outlined in The Fraud Strategy Attack Guide, a BNPL provider saw 25,000+ bot attempts in 90 days, with over 3,000 bots completing applications, bypassing OTP or using synthetic identities. Retail and e-commerce platforms face attacks designed to take over customer accounts and make unauthorized purchases using stored payment methods, gift cards or promo credits. OTP bots can help fraudsters trigger and intercept verification codes tied to checkout or login flows. Healthcare and education organizations can be targeted for their sensitive data and widespread use of digital portals. OTP bots can help attackers access patient records, student or staff accounts, or bypass verification during intake and application flows, leading to phishing, insurance fraud or data theft. Government and public sector entities are increasingly vulnerable as fraudsters exploit digital services meant for public benefits. OTP bots may be used to sign up individuals for disbursements or aid programs without their knowledge, enabling fraudsters to redirect payments or commit identity theft. This abuse not only harms victims but also undermines trust in the public system. Across sectors, the message is clear: the bots are getting in too far before being detected. Organizations across all industries need the ability to recognize bot risk at the very first touchpoint; the earlier the better. The limitations of OTP defense OTP is a strong second factor, but it’s not foolproof. If a bot reaches the OTP stage, it's highly likely that they've already: Stolen or purchased valid credentials Found a way to trigger the OTP Put a social engineering play in motion Fighting bots earlier in the funnel The most effective fraud prevention doesn’t just react to bots at the OTP step; it stops them before they trigger OTPs in the first place. But to do that, you need to understand how modern bots operate and how our bot detection solutions, powered by NeuroID, fight back. The rise of GenAI-powered bots Bot creation has become dramatically easier. Thanks to generative AI and widely available bot frameworks, fraudsters no longer need deep technical expertise to launch sophisticated attacks. Today’s Gen4 bots can simulate human-like interactions such as clicks, keystrokes, and mouse movements with just enough finesse to fool traditional bot detection tools. These bots are designed to bypass security controls, trigger OTPs, complete onboarding flows, and even submit fraudulent applications. They are built to blend in. Detecting bots across two key dimensions Our fraud detection solutions are purpose-built to uncover these threats by analyzing risk signals across two critical dimensions. 1. Behavioral patternsEven the most advanced bots struggle to perfectly mimic human behavior. Our tools analyze thousands of micro-signals to detect deviations, including: Mouse movement smoothness and randomness Typing cadence, variability and natural pauses Field and page transition timing Cursor trajectory and movement velocity Inconsistent or overly “perfect” interaction patterns By identifying unnatural rhythms or scripted inputs, we can distinguish real users from automation before the OTP step. 2. Device and network intelligenceIn parallel, our technology examines device and network indicators that often reveal fraud at scale: Detection of known bot frameworks and automation tools Device fingerprinting to flag repeat offenders Link analysis connecting devices across multiple sessions or identities IP risk, geolocation anomalies and device emulation signals This layered approach helps identify fraud rings and coordinated bot attacks, even when attackers attempt to mask their activity. A smarter way to stop bots We offer both a highly responsive, real-time API for instant bot detection and a robust dashboard for investigative analytics. This combination allows fraud teams to stop bots earlier in the funnel — before they trigger OTPs, fill out forms, or submit fake credentials — and to analyze emerging trends across traffic patterns. Our behavioral analytics, combined with device intelligence and adaptive risk modeling, empowers organizations to act on intent rather than just outcomes. Good users move forward without friction. Bad actors are stopped at the source. Ready to stop bots in their tracks? Explore Experian’s fraud prevention services. Learn more *This article includes content created by an AI language model and is intended to provide general information.

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?

Fraud never sleeps, and neither do the experts working to stop it. That’s why we’re back with episode two of Meet the Maker, our video series spotlighting the brilliant minds behind Experian’s cutting-edge fraud solutions. In this episode, Nash Ali, Head of Operational Strategy, and Dave Tiezzi, Senior Vice President of Payments and New Markets, share how the power of NeuroID’s behavioral analytics and device and network intelligence, combined with Experian Link’s credit card owner verification, helps e-commerce merchants combat key fraud threats, while providing a seamless checkout experience. With decades of experience in payments and fraud, these fraud-fighting experts know exactly what it takes to stop fraud, minimize friction, and reduce chargebacks so e-commerce merchants can protect the most crucial stage of the buying process. Watch now for an exclusive look at the minds shaping the future of fraud prevention.  Interested in learning more about our fraud management solutions? Watch previous episode Learn more

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.

The days of managing credit risk, fraud prevention, and compliance in silos are over. As fraud threats evolve, regulatory scrutiny increases, and economic uncertainty persists, businesses need a more unified risk strategy to stay ahead. Our latest e-book, Navigating the intersection of credit, fraud, and compliance, explores why 94% of forward-looking companies expect credit, fraud, and compliance to converge within the next three years — and what that means for your business.1 Key insights include: The line between fraud and credit risk is blurring. Many organizations classify first-party fraud losses as credit losses, distorting the true risk picture. Fear of fraud is costing businesses growth. 68% of organizations say they’re denying too many good customers due to fraud concerns. A unified approach is the future. Integrating risk decisioning across credit, fraud, and compliance leads to stronger fraud detection, smarter credit risk assessments, and improved compliance. Read the full e-book to explore how an integrated risk approach can protect your business and fuel growth. Download e-book 1Research conducted by InsightAvenue on behalf of Experian

With cybersecurity threats on the rise, organizations are turning to token-based authentication as a secure and efficient solution to safeguard sensitive data and systems. Data breaches impacted 1.1 billion individuals in 2024, a staggering 490% increase from the previous year.1 Token-based authentication is a method of verifying a user's identity through digital tokens rather than traditional means such as passwords. These tokens are temporary and serve as access keys, allowing users to securely interact with systems, applications, and networks. The goal of token authentication is to strengthen security while improving the user experience. Instead of relying solely on static credentials (like passwords), which can be intercepted or stolen, leveraging a type of multi-factor authentication like tokens adds an additional layer of security by functioning as dynamic access credentials. How token-based authentication works Token authentication unfolds through a series of steps to ensure robust security. Here's a simplified breakdown of how it works in practice: User request and authentication: When a user attempts to log in, they provide their credentials (e.g., username and password). These credentials are verified by the authentication server. Token generation: After verifying the user's credentials, the server generates a token — a cryptographically secured string often containing information like the user's ID and permissions. Token sent to the user: The generated token is sent back to the user or their device to confirm authentication. Token usage for access: Now authenticated, the user uses the token to access the system or application. The token is passed along with each request to ensure the user is authorized to proceed. Token validation: Each time a token is presented to the server, its integrity and expiration are verified. If the token is valid, access is granted; if not, the session is terminated. Token expiration and renewal: Tokens are typically temporary and expire after a set period. Users must either re-authenticate or renew the token for continued access. This limits the time window during which a stolen token can be misused. Types of token authentication methods Token authentication comes in different forms to meet various use case requirements. Common types include: JSON Web Tokens (JWT) Lightweight, self-contained, and easily transferred between clients and servers, JWT is one of the most widely used token formats. It includes claims, which are bits of information about a user encoded within the token, such as roles and permissions. Example: A financial application uses JWTs to ensure only registered users can access private account data. OAuth tokens OAuth is an industry-standard authorization protocol that uses tokens to grant limited access to applications without revealing the user's credentials. It’s often used for third-party service integration. Example: When you log into an e-commerce platform using your Google credentials, OAuth tokens authorize access. Session tokens These are temporary tokens stored on the server to track authenticated sessions, commonly used in web applications to ensure secure browsing. Example: Online banking platforms rely on session tokens for secure user sessions. Refresh tokens Refresh tokens are designed to renew access tokens without requiring the user to log in repeatedly. They extend session durations while maintaining a high-security standard. Example: A subscription service app uses refresh tokens to maintain a seamless user experience without frequent logouts. Benefits of token-based authentication Token-based authentication offers several advantages that make it a preferred security measure for organizations of all sizes. Enhanced security: Tokens reduce the risk of breaches as they are temporary and encrypted. They’re also specific to sessions, applications, or devices, meaning unauthorized users cannot reuse stolen tokens effectively. Elimination of password reliance: Tokens reduce dependence on static passwords, which are often reused and susceptible to brute-force attacks. This bolsters an organization’s overall cybersecurity posture. Improved user experience: Token authentication allows for more seamless interactions by minimizing the need for repeated logins. With features like single sign-on (SSO), users enjoy convenient access to multiple platforms with a single token. Scalability: Tokens are flexible and can adapt to varied business use cases, making them ideal for organizations of all scales. For instance, application programming interfaces (APIs) and microservices can communicate securely via token exchanges. Supports compliance: Token-based authentication helps organizations meet regulatory compliance requirements by offering robust access control and audit trails. This is critical for industries like finance, healthcare, and e-commerce. Cost efficiency: While implementing token-based authentication may require an initial investment, it reduces long-term risks and costs associated with data breaches, system downtime, and customer trust. How Experian can help strengthen your authentication process At Experian, we recognize that strong security measures should never compromise the user experience. That's why we offer cutting-edge identity solutions tailored to meet the needs of organizations. Our tools allow you to integrate token-based authentication seamlessly into your systems while ensuring compliance with security best practices and industry regulations. Are you ready to take your business's security and user experience to the next level? Visit us online today. Learn more 12024-2025 Data Breach Response Guide, Experian, 2024. This article includes content created by an AI language model and is intended to provide general information.