Online platforms such as marketplaces, gaming sites, fintech apps, referral programs, and online stores are constantly under threat from fraud. Fraudsters keep coming up with newer methods to conduct fraud, and multi-accounting is one of them. Multi-accounting is where a single user creates multiple fake accounts to exploit a system.
In this guide, we’ll explore multi-accounting, how it works, and ways to prevent it. Let’s dive in.
Multi-accounting fraud refers to the practice of a single person or group creating and controlling multiple accounts on a digital platform. These accounts are typically used to manipulate promotions, cheat in games, launder money, evade bans, or gain unfair advantages in systems meant for single-user participation.
For example:
Multi-accounting may seem like a victimless crime, but it can cause severe damage to digital platforms in several ways:
1. Financial Loss: Referral fraud can drain marketing budgets. Fake users redeeming coupons or cashbacks meant for real customers directly impact revenue.
2. Skewed Analytics: Multi-accounts distort user behavior data, making it hard for businesses to measure performance or run accurate user acquisition campaigns.
3. Erosion of Trust: Users lose trust in platforms with fake reviews, rigged games, or manipulated reward systems.
4. Regulatory Risks: Multi-accounting linked to money laundering or identity fraud can expose platforms to legal liabilities.
5. Operational Overhead: More fake accounts mean more transactions, more customer support queries, and higher infrastructure costs, without any real user value.
Fraudsters are sophisticated and often use a combination of techniques to bypass detection:
Detection is the first step toward prevention. Here are some signs that may indicate multi-accounting:
1. Multiple Accounts from the Same IP or Device: Repeated logins or account creations from the same IP/device fingerprint are a common red flag.
2. Unusual Referral Patterns: If a user refers too many accounts in a short time or all referred users have similar behavior, it’s worth investigating.
3. Synchronized Activity: Fake accounts are often controlled centrally. Look for similar actions (logins, purchases, reviews) happening at the same times.
4. Inconsistent User Profiles: If multiple accounts have incomplete or similar profile information, they could be part of a fraud ring.
5. Abuse of Promotions: A small group exploiting multiple first-time-user offers or discounts might be engaging in multi-accounting fraud.
Combating multi-accounting fraud requires a mix of technology, policy, and human oversight. Here are proven strategies to consider:
1. Device Fingerprinting: Use advanced device fingerprinting tools that go beyond IPs to track hardware, screen size, browser type, installed fonts, and more. This helps identify if the same device is being used across accounts.
2. Behavioral Analytics: Track user behavior patterns like click speed, session times, scroll patterns, and navigation paths. Bots or fake users often show repetitive or unnatural behavior.
3. Multi-Factor Authentication (MFA): Requiring users to verify their identity via email, SMS, or authenticator apps makes it harder for fraudsters to create multiple accounts quickly.
4. IP Intelligence: Monitor and restrict access from suspicious IP ranges, such as known VPNs, TOR nodes, or proxy servers.
5. Email and Phone Validation: Block temporary/disposable email providers and enforce mobile number verification. Requiring unique phone numbers helps limit mass registrations.
6. Referral & Promo Rules: Limit the number of rewards a single user can earn, add manual reviews for suspicious referrals, and create cooldown periods between rewards.
7. Stricter Onboarding Practices: To prevent multi-accounting fraud, businesses should employ stricter onboarding practices. Verifying identity documents, bank accounts, and proof of address documents can reduce the number of fraudsters onboarded, which automatically leads to less fraud.
8. AI-Powered Fraud Detection: Leverage machine learning to spot anomalies and patterns that are hard to catch manually. These models can improve over time with new fraud examples.
A key challenge in fraud prevention is not to frustrate legitimate users with overly strict verification steps. For example:
The ideal approach is adaptive authentication: apply more friction only when suspicious activity is detected. For instance, a trusted returning user can log in normally, but a flagged account may need extra steps like photo ID verification.
Conclusion
Multi-accounting fraud is a growing challenge for digital platforms, but it’s not unbeatable. By combining technology like device fingerprinting and AI with smart policies and real-time monitoring, businesses can protect themselves without harming user experience.
Preventing fraud isn’t a one-time fix—it’s an ongoing strategy. As fraudsters evolve, so must your defenses. Investing in robust fraud prevention systems today ensures a safer, fairer, and more profitable platform tomorrow.