Last Updated on 25 Jan 2024
How to prevent fake account creation while running a growth marketing campaign
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Big growth with the taste of fake accounts fraud
Imagine a big promotion by a popular online business, e.g. a retailer or a fintech app, offering exclusive discounts to attract new customers.
The campaign, aimed at providing exciting deals, generates a significant surge in new accounts, inadvertently creating anopportunity for fake accounts, a.k.a. “new account fraud.”
As excitement grows around the campaign's success, the fraudsters secretly create numerous fake accounts to benefit from the exclusive promotions, showcasing the vulnerability of businesses to "new account fraud”.
What is new account fraud?
New account opening (NAO) fraud, also known as account opening (AO) fraud or fake account, is a form of identity theft where criminals use stolen or synthetic personal information to create unauthorized accounts.
Considering the scale of data leaks happening every day, it is becoming increasingly difficult to differentiate stolen private information from legitimate ones.
Considering the scale of data leaks happening every day, it is becoming increasingly difficult to differentiate stolen private information from legitimate ones.
New account fraud, which is especially common during marketing campaigns that go viral, can result in severe consequences:
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Financial losses:Fraudsters capitalize on the discounts, causing immediate financial losses for the business.•
Skew business performance indicators:This fraud causes a sudden surge of new accounts for fictitious and high-risk users that misleads company's key performance indicators (KPIs).•
Damage to reputation and users’ trust:Legitimate customers, attracted by the campaign, become frustrated as reports of unauthorized transactions and compromised accounts circulate. The business reputation takes a hit, shedding light on the risks of new account fraud that are harder to measure.•
Implement Credit FreezesConsider placing a credit freeze on her accounts to restrict access, preventing fraudsters from opening new accounts in your name.•
Legal implications:The business faces potential legal threats as affected customers demand compensation for unauthorized transactions and seek legal action for their compromised personal information, highlighting the legal ramifications of "new account fraud."
What actions can application security manager do for fraud mitigation
The security manager of this business can take action to mitigate the impact, addressing these challenges associated with "new account fraud":
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Enhanced Security Measures:Additional security measures, such as more robust identity verification during account creation and stricter validation for discount code usage, are implemented to thwart "new account fraud" attempts. But this can easily reduce the effectiveness of a campaign because it gets harder for legitimate users to sign up to.•
Fraud Detection Tools:The business invests in advanced fraud detection tools to identify and block suspicious account activity, bolstering defenses against "new account fraud". In this part, fraud detection tools come to help the business focus on optimizing user acquisition without having to add more steps to the account creation process just to reduce fake accounts.•
Collaboration with Authorities:The business collaborates with law enforcement agencies to investigate and take legal action against the fraudsters involved in new account fraud. This often involves providing evidence that a modern fraud detection tool can help in gathering and reporting.•
Rebuilding Trust:A comprehensive public relations campaign is launched to rebuild trust with customers. This includes emphasizing strengthened security measures and offering additional perks to legitimate customers affected by the impact of account related frauds.
Securing your app and running a successful campaign with AI fraud detection tool
In conclusion, the battle against new account fraud begins with proactive strategies and the right tools in the right place at the right time.
Utilizing AI fraud prevention tools, such as CrossClassify, from the outset can be an automatic and adaptive approach to prevent new account fraud.
Modern fraud detection products, equipped with sophisticated algorithms and real-time monitoring, act as the first line of defense against unauthorized account creations and suspicious activities.
The ultimate security measure is to analyze every user's behavior online to assess the risk and decide what to do on every action.
This approach is called "behavioral biometrics" and it is a lot of hard work to develop and fine-tune but the good news is that it is available as a service.
It gives the business a risk score for every user session with a recommended decision to approve or block a user’s access upon taking every action, such as opening a new account.
By incorporating such preventive measures, companies not only safeguard their finances but also protect their reputation and the trust of their valued customers.
See How Protect Your Platform from Account Opening Fraud
CrossClassify uses AI and continuous behavior monitoring to detect and prevent Fake accounts, protecting your business processes
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Frequently asked questions
Fake accounts are used for scams, spam, promo abuse, data scraping, and laundering money. They degrade platform trust, inflate metrics, and increase fraud risks—especially during account-based transactions.
Account creation fraud involves registering fake or synthetic identities—often using bots, stolen data, or automated scripts—to exploit services or evade detection.
Use a layered approach:
- Device fingerprinting
- Bot detection
- IP intelligence
- Behavioral analytics
- Email/phone verification
It's a security tool that screens new sign-ups, analyzes behavioral and technical signals, and blocks risky or automated registrations before they enter your system. CrossClassify is one such solution designed to stop fraud at onboarding.
Traditional CAPTCHAs frustrate real users. Instead, use passive checks like device intelligence and behavioral profiling—techniques used by CrossClassify to detect fraud silently in the background.
Leading tools include fraud scoring engines, CAPTCHA alternatives, bot detection systems, and AI-powered solutions like CrossClassify that combine them under one API.
Yes. Fraudsters use bots and scripts to mass-register accounts and bypass basic protections. That’s why advanced, adaptive protection—like what CrossClassify offers—is essential.
Fake sign-ups often show abnormal behavior—fast form fills, repeated attempts, or identical device patterns. CrossClassify flags these in real time using behavioral biometrics.
Yes. With CrossClassify, you get a dashboard with risk scores, device profiles, sign-up attempts, and alerts—allowing your team to investigate and act with confidence.
CrossClassify combines device fingerprinting, behavioral analysis, bot mitigation, and trust scoring into one real-time fraud prevention engine—designed to detect and block fake accounts before they cause harm.
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