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Credential Stuffing Prevention: How Experian’s Behavioral Analytics Solutions Can Help

Published: December 18, 2024 by Laura Burrows

In today’s digital landscape, where data breaches and cyberattacks are rampant, businesses face increasing security challenges. One of the most prevalent threats is credential stuffing—a cyberattack in which malicious actors use stolen username and password combinations to gain unauthorized access to user accounts. As more personal and financial data gets leaked or sold on the dark web, these attacks become more sophisticated, and the consequences for businesses and consumers alike can be devastating.

But there are ways to proactively fight credential stuffing attacks and protect your organization and customers. Solutions like our identity protection services and behavioral analytics capabilities powered by NeuroID, a part of Experian, are helping businesses prevent fraud and ensure a safer user experience.

What is credential stuffing?

Credential stuffing is based on the simple premise that many people reuse the same login credentials across multiple sites and platforms. Once cybercriminals can access a data breach, they can try these stolen usernames and passwords across many other sites, hoping that users have reused the same credentials elsewhere.

This form of attack is highly automated, leveraging botnets to test vast numbers of combinations in a short amount of time. If an attacker succeeds, they can steal sensitive information, access financial accounts, or carry out fraudulent activities.

While these attacks are not new, they have become more effective with the proliferation of stolen data from breaches and the increased use of automated tools. Traditional security methods—such as requiring complex passwords or multi-factor authentication (MFA)—are useful but not enough to prevent credential stuffing fully.

How we can help protect against credential stuffing

We offer comprehensive fraud prevention tools and multi-factor authentication solutions to help you identify and mitigate credential stuffing threats.

We use advanced identity verification and fraud detection technology to help businesses assess and authenticate user identities in real-time. Our platform integrates with existing authentication and risk management solutions to provide layered protection against credential stuffing, phishing attacks, and other forms of identity-based fraud.

Another key element in our offering is behavioral analytics, which goes beyond traditional methods of fraud detection by focusing on users’ data entry patterns and interactions.

NeuroID and Experian partner to combat credential stuffing

We recently acquired NeuroID, a company specializing in behavioral analytics for fraud detection, to take the Experian digital identity and fraud platform to the next level. 

Advanced behavioral analytics is a game-changer for preventing credential-stuffing attacks. While biometrics track characteristics, behavioral analytics track distinct actions. For example, with behavioral analytics, every time a person inputs information, clicks in a box, edits a field, and even hovers over something before clicking on it or adding the information to it, those actions are tracked. However, unlike biometrics, this data isn’t used to connect to a single identity. Instead, it’s information businesses can use to learn more about the experience and the intentions of someone on the site.

NeuroID and Experian’s paired fraud detection capabilities offer several distinct advantages in preventing credential stuffing attacks:

  1. Real-time threat detection: Analyze thousands of behavioral signals in real-time to detect user behavior that suggests bots, fraud rings, credential stuffing attempts, or any number of other cybercriminal attack strategies.
  2. Fraud risk scoring: Based on behavioral patterns, assign a fraud risk score to each user session. High-risk sessions can trigger additional authentication steps, such as CAPTCHA or step-up authentication, helping to stop credential stuffing before it occurs.
  3. Invisible to the user: Unlike traditional authentication methods, behavioral analytics work seamlessly in the background. Users do not need to take extra steps—such as answering additional security questions or entering one-time passwords.
  4. Adaptive and self-learning: As users interact with your website or app, our system continuously adapts to their unique behavior patterns. Over time, the system becomes even more effective at distinguishing between legitimate and malicious users without collecting any personally identifiable information (PII).

Why behavioral data is critical in combating credential stuffing

Credential stuffing attacks rely on the ability to mimic legitimate login attempts using stolen credentials. Behavioral analytics, however, can spot the subtle differences between human and bot behavior, even if the attacker has the correct credentials. By integrating behavioral analytics, you can:

  • Prevent automated attacks: Bots often interact with websites in unnatural ways—speeding through form fields, using erratic mouse movements, or attempting logins from unusual or spoofed geographic locations. Behavioral analytics can flag these behaviors before an account is compromised.
  • Detect account takeovers early: If a legitimate user’s account is taken over, behavioral analytics can detect the change in interactions. By monitoring behavior, businesses can detect account takeover attempts much earlier than traditional methods.
  • Lower false positive rates: Traditional fraud prevention tools often rely on rigid rule-based systems that can block legitimate users, especially if their login patterns slightly differ from the norm. On the other hand, behavioral analytics analyzes a user’s real-time behavioral data without relying on traditional static data such as passwords or personal information. This minimizes unnecessary flags on legitimate customers (while still detecting suspicious activity).
  • Improve customer experience: Since behavioral analytics is invisible to users and requires no extra friction (like answering security questions), the login and transaction verification process is much smoother. Customers are not inconvenienced, and businesses can reduce the risk of fraud without annoying their users.

The future of credential stuffing prevention

Credential stuffing is a growing threat in today’s interconnected world, but with the right solutions, businesses can significantly reduce the risk of these attacks. By integrating our fraud prevention technologies and behavioral analytics capabilities, you can stay ahead of the curve in securing user identities and preventing unauthorized access.

The key benefits of combining traditional identity verification methods with behavioral analytics are higher detection rates, reduced friction for legitimate users, and an enhanced user experience overall. In an era of increasingly sophisticated cybercrime, using data-driven behavioral insights to detect user riskiness is no longer just a luxury—it’s a necessity.

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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/

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