Business Protection Strategies Against Unauthorized Account Usurpation
In the digital age, new account fraud has become a significant concern for various industries, including gaming, dating websites, e-commerce, and financial institutions. This form of fraud, which can involve creating fake accounts for criminal activity or taking over existing accounts, can lead to substantial losses and damage to users' trust.
New account fraud can manifest in several ways. It can involve stealing personal information to create new accounts for illicit purposes, or it can involve the creation of entirely fake personas. In some cases, fraudsters may use a combination of both real and fake data to build seemingly legitimate identities.
To combat this issue, industries are relying heavily on a combination of strategies embedded in AI-powered platforms. These platforms provide real-time risk scoring and automated decisioning, balancing security needs with user convenience.
One of the key strategies is the use of Behavioral Biometrics and User Behavior Analysis. By tracking how users navigate, fill out forms, and interact during sign-up, suspicious patterns can be identified. Unnatural typing cadence, copy-pasting, or inhumanly fast completion are typical of bots or scripts, helping to flag potential fraudulent activity.
Device and Identity Intelligence is another crucial strategy. Monitoring IP addresses, device fingerprinting, geolocation, and use of proxies/VPNs helps reveal suspicious multiple sign-ups from the same device or location anomalies.
Velocity Checks are also important for detecting spikes in the number of accounts created from single sources or devices in a short time, which is a strong red flag for automated fraud.
Email and Phone Number Analysis is another layer of defense. Flagging disposable or suspiciously structured emails and phone numbers that are reused or linked to known fraud attempts can help prevent fraudulent account openings.
Machine Learning and AI Models are used to analyze large volumes of transaction and sign-up data in real time, allowing for continuous risk scoring and detection of complex fraud patterns, including subtle anomalies in behavior and account activity.
Cross-Referencing External and Proprietary Data is another effective strategy. Combining internal data with credit reports, fraud consortium data, and third-party intelligence improves accuracy in identifying true-name fraud and synthetic identity fraud.
Post-Sign-Up Monitoring is also essential for mitigating long-term risks. Continuously evaluating account activity after creation helps catch dormant or slowly acting fraud accounts.
In the fight against new account fraud, password protection technologies, such as multi-factor authentication and regular password updates, can help minimize account takeovers. It's also important for businesses to be able to spot deepfakes early on, preferably at the onboarding stage.
To provide a comprehensive solution, vendors are combining various solutions, including KYC, Know Your Business, transaction monitoring, geolocation tracking, deepfake detection, device fingerprinting, and fraud scoring, into one platform. This allows companies to adjust checks according to different types of customers.
The rise of deepfakes, created using artificial intelligence, compounds the threat of creating fake identities for fraudulent purposes. As such, it's crucial for businesses to develop a robust Know Your Customer (KYC) process to spot fraudsters using stolen data.
In 2022, the US Federal Trade Commission reported losses of over $8.8 billion due to scams, underscoring the importance of implementing robust fraud prevention measures. These solutions also allow companies to check customers for other types of criminal activity, including money laundering and terrorism financing.
By implementing these strategies, industries can better protect their users and their businesses from the threat of new account fraud.
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