Loading...

The Ultimate Guide to Credit Card Fraud Detection

Published: July 23, 2024 by Julie Lee

In this article…

With debit and credit card transactions becoming more prevalent than cash payments in today’s digital-first world, card fraud has become a significant concern for organizations. Widespread usage has created ample opportunities for cybercriminals to engage in credit card fraud. As a result, millions of Americans fall victim to credit card fraud annually, with 52 million cases reported last year alone.1

Preventing and detecting credit card fraud can save organizations from costly losses and protect their customers and reputations. This article provides an overview of credit card fraud detection, focusing on the current trends, types of fraud, and detection and prevention solutions.

What is credit card fraud?

Credit card fraud involves the unauthorized use of a credit card to obtain goods, services or funds. It’s a crime that affects individuals and businesses alike, leading to financial losses and compromised personal information. Understanding the various forms of credit card fraud is essential for developing effective prevention strategies.

Types of credit card fraud

Understanding the different types of credit card fraud can help in developing targeted prevention strategies. Common types of credit card fraud include:

  • Card not present fraud occurs when the physical card is not present during the transaction, commonly seen in online or over-the-phone purchases. In 2023, card not present fraud was estimated to account for $9.49 billion in losses.2
  • Account takeover fraud involves fraudsters gaining access to a victim’s account to make unauthorized transactions. In 2023, account takeover attacks increased 354% year-over-year, resulting in almost $13 billion in losses.3,4
  • Card skimming, which is estimated to cost consumers and financial institutions over $1 billion per year, occurs when fraudsters use devices to capture card information from ATMs or point-of-sale terminals.5
  • Phishing scams trick victims into providing their card information through fake emails, texts or websites.

What is credit card fraud prevention and detection?

To combat the rise in credit card fraud effectively, organizations must implement credit card fraud prevention strategies that involve a combination of solutions and technologies designed to identify and stop fraudulent activities. Effective fraud prevention solutions can help businesses minimize losses and protect their customers’ information. Common credit card fraud prevention and detection methods include:

  • Fraud monitoring systems: Banks and financial institutions employ sophisticated algorithms and artificial intelligence to monitor transactions in real time. These systems analyze spending patterns, locations, transaction amounts, and other variables to detect suspicious activity.
  • EMV chip technology: EMV (Europay, Mastercard, and Visa) chip cards contain embedded microchips that generate unique transaction codes for each purchase. This makes it more difficult for fraudsters to create counterfeit cards.
  • Tokenization: Tokenization replaces sensitive card information with a unique identifier or token. This token can be used for transactions without exposing actual card details, reducing the risk of fraud if data is intercepted.
  • Multifactor authentication (MFA): Adding an extra layer of security beyond the card number and PIN, MFA requires additional verification such as a one-time code sent to a mobile device, knowledge-based authentication or biometric/document confirmation.
  • Transaction alerts: Many banks offer alerts via SMS or email for every credit card transaction. This allows cardholders to spot unauthorized transactions quickly and report them to their bank.
  • Card verification value (CVV): CVV codes, typically three-digit numbers printed on the back of cards (four digits for American Express), are used to verify that the person making an online or telephone purchase physically possesses the card.
  • Machine learning and AI: Advanced algorithms can analyze large datasets to detect unusual patterns that may indicate fraud, such as sudden large transactions or purchases made in different geographic locations within a short time frame. Advanced algorithms can analyze large datasets to detect unusual patterns that may indicate fraud, such as sudden large transactions or purchases made in different geographic locations within a short time frame.
  • Behavioral analytics: Monitoring user behavior to detect anomalies that may indicate fraud.
  • Education and awareness: Educating consumers about phishing scams, identity theft, and safe online shopping practices can help reduce the likelihood of falling victim to credit card fraud.
  • Fraud investigation units: Financial institutions have teams dedicated to investigating suspicious transactions reported by customers. These units work to confirm fraud, mitigate losses, and prevent future incidents.

How Experian® can help with card fraud prevention and detection

Credit card fraud detection is essential for protecting businesses and customers. By implementing advanced detection technologies, businesses can create a robust defense against fraudsters. Experian® offers advanced fraud management solutions that leverage identity protection, machine learning, and advanced analytics. Partnering with Experian can provide your business with:

  • Comprehensive fraud management solutions: Experian’s fraud management solutions provide a robust suite of tools to prevent, detect and manage fraud risk and identity verification effectively.
  • Account takeover prevention: Experian uses sophisticated analytics and enhanced decision-making capabilities to help businesses drive successful transactions by monitoring identity and flagging unusual activities.
  • Identifying card not present fraud: Experian offers tools specifically designed to detect and prevent card not present fraud, ensuring secure online transactions.

Take your fraud prevention strategies to the next level with Experian’s comprehensive solutions. Explore more about how Experian can help.

Learn More

Sources

1 https://www.security.org/digital-safety/credit-card-fraud-report/

2 https://www.emarketer.com/chart/258923/us-total-card-not-present-cnp-fraud-loss-2019-2024-billions-change-of-total-card-payment-fraud-loss

3 https://pages.sift.com/rs/526-PCC-974/images/Sift-2023-Q3-Index-Report_ATO.pdf

4 https://www.aarp.org/money/scams-fraud/info-2024/identity-fraud-report.html

5 https://www.fbi.gov/how-we-can-help-you/scams-and-safety/common-scams-and-crimes/skimming

This article includes content created by an AI language model and is intended to provide general information.

Related Posts

Unmasking Fraud Rings: Understanding and Combating Org...

Apply DA Tag

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

Published: February 27, 2025 by Presten Swenson

Read More

Meet the Maker: The Visionaries Powering Experian’s Fr...

Apply DA Tag

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.

Published: February 21, 2025 by Julie Lee

Read More

Why Credit Risk, Fraud, and Compliance Are Converging ...

Apply DA Tag

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

Published: February 20, 2025 by Julie Lee

Read More