A Marketplace's Guide to Eliminating Fake Accounts with Email & Phone Number Scoring

Introduction

Online marketplaces have revolutionized commerce, but their open nature creates a critical vulnerability: fake accounts. These fraudulent accounts are the gateway to a host of problems, from spam and biased reviews to outright financial fraud. For a platform whose entire business model rests on trust between buyers and sellers, fake accounts represent an existential threat, capable of eroding user confidence and permanently damaging brand reputation. The challenge is not just identifying these accounts, but doing so without creating a frustrating experience for legitimate new users.

According to research published by Inc. magazine in 2023, fake online reviews, often stemming from fake accounts, influence an estimated $791 billion in e-commerce spending in the U.S. alone, underscoring the massive economic impact of inauthentic user activity.

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This guide provides a comprehensive roadmap for marketplace operators to move beyond basic verification methods. We will explore how implementing sophisticated tools like email and phone number scoring can proactively identify and neutralize fake accounts at the point of creation. By strengthening the initial signup process, you can build a more secure and trustworthy ecosystem for everyone, from signup to the final sale.

Why Trust and Security Are Critical for Marketplace Success

Unlike a traditional e-commerce store where the business is the only seller, a marketplace is a complex ecosystem. The platform owner is a facilitator, responsible for creating a safe environment where strangers feel comfortable transacting with one another. This multi-sided model, involving buyers, sellers, and the platform itself, creates unique incentives for fraudsters who exploit the inherent trust required to make the system work. A single bad actor can create a ripple effect, causing significant harm.

When a seller is scammed by a fraudulent buyer, they lose revenue and goods. When a buyer is duped by a fake seller account, they lose money and faith in the platform. These negative experiences, when shared, deter new users from joining. The marketplace's reputation is its currency; without it, volume and liquidity dry up as both sides of the transaction lose confidence in the platform's ability to provide a safe trading environment.

At the heart of this challenge is the anonymity that the internet can provide. Fraudsters thrive where they can operate without consequence, using fake identities to perpetrate their schemes. For marketplaces, the battle against fraud begins at the front door: the account creation process. Ensuring that every new user is a legitimate, real person is the first and most critical step in building a foundation of trust.

Effective fraud prevention is therefore not just a technical necessity but a core business strategy. Marketplaces that invest in robust identity verification are not just protecting themselves from loss; they are actively building a more valuable and sustainable business. They are signaling to both buyers and sellers that their platform is a secure place to do business, fostering the loyalty and active participation needed for long-term growth.

This is why proactive measures are essential. Waiting for a user to report a scam is a reactive approach that signals a failure has already occurred. By leveraging advanced verification tools, marketplaces can prevent these failures from happening in the first place, solidifying their reputation as a secure and reliable platform.

The True Cost of Fake Accounts: Hidden Impacts on Your Marketplace

Fake accounts are more than just a nuisance; they are a strategic tool for fraudsters and a significant drain on a marketplace's resources and reputation. The visible damage, such as a single fraudulent transaction, is often just the tip of the iceberg. The hidden costs can be far more substantial and pervasive, affecting everything from your operational efficiency to your market valuation.

One of the most immediate impacts is on your key performance indicators (KPIs). Fake accounts inflate user numbers, leading to misleading data on growth, engagement, and conversion rates. This can cause teams to make poor strategic decisions based on inaccurate information. Imagine launching a marketing campaign in a region where you believe you have a strong user base, only to find you were targeting a network of bots, resulting in wasted ad spend and skewed analytics.

These automated accounts are often used for a variety of disruptive activities that degrade the user experience for everyone. This includes:

• Spamming: Fake accounts can be used to flood legitimate users with unsolicited messages, phishing attempts, or advertisements for off-platform transactions, creating a noisy and untrustworthy environment.
• Review Fraud: Competitors or malicious actors can use fake accounts to "review bomb" a seller with negative ratings or artificially inflate their own ratings, manipulating platform algorithms and misleading genuine buyers.
• Scams: Fraudsters create convincing but fake seller profiles, list non-existent products, and disappear after receiving payment, leaving the marketplace to deal with angry, defrauded customers and costly chargebacks.

Ultimately, the most significant cost of New Account Fraud is the erosion of trust. When legitimate users repeatedly encounter spam, scams, and deceptive reviews, their confidence in the platform wanes. They become less likely to engage, transact, or recommend the marketplace to others. This reputational damage can be difficult to repair and can give competitors who prioritize security a significant advantage.

Managing the fallout from fake accounts also consumes valuable human resources. Support teams get tied up investigating fraud claims, and engineering teams must constantly react to new threats instead of focusing on building new features. By failing to stop fake accounts at the source, a marketplace commits to a costly and unending defensive battle.

Why Traditional Email and SMS Verification Fails Against Modern Fraud

For years, the standard for verifying a new user was simple: send a confirmation link to their email address or a one-time code to their phone. The logic was that if a user could receive it, they must be legitimate. However, fraudsters are adept at overcoming these simple hurdles, making traditional verification methods largely ineffective against even moderately sophisticated attacks. These outdated systems check for possession, not for intent or legitimacy.

The most common weakness is the rise of Disposable Email services. These services allow a user to create a temporary, self-destructing email address in seconds. A fraudster can use one to click a verification link, create an account, run a scam, and then abandon the email address, leaving no trail. Because the email address was technically valid and receivable at the moment of signup, it passes the traditional check with ease.

Similarly, disposable or virtual phone numbers are readily available online. These "burner" numbers can receive SMS verification codes, allowing fraudsters to bypass phone verification checks just as easily as email ones. They can automate this process at scale, creating hundreds or thousands of seemingly legitimate accounts, each tied to a unique but untraceable virtual number. The system sees a successful confirmation and waves the user through, unaware that the number belongs to a bot network, not a genuine customer.

These methods fail because they answer the wrong question. They confirm "Can this person receive a message at this contact point?" when they should be asking, "Is this contact point associated with a real, trustworthy person?" A simple confirmation check cannot distinguish between a person's primary email of ten years and one created ten seconds ago for the sole purpose of abuse.

This gap in security is what fraudsters exploit. They understand that as long as they can receive that initial confirmation, they are free to operate on the platform. Marketplaces that rely solely on these methods are leaving their doors wide open to abuse, unable to differentiate between a high-value future customer and a high-risk fraudster preparing to attack their users.

Advanced Email and Phone Number Scoring: A Data-Driven Fraud Prevention Approach

Instead of a simple pass/fail check, modern fraud prevention uses a more intelligent, data-driven approach: scoring. Email and phone number scoring APIs operate in the background to analyze hundreds of data points associated with an email address or phone number, returning a risk score that predicts the likelihood of fraud. This happens in milliseconds during the signup process, providing a powerful, invisible layer of security.

For email scoring, the analysis goes far beyond just checking if the email address exists. It examines a wide range of signals to determine its quality and legitimacy. Key factors include:

• Domain Reputation: Is the email from a well-known provider like Gmail or from a newly registered, suspicious domain? Has the domain been associated with spam or abuse?
• Syntax and Format: Does the email address follow valid formats? Does it contain patterns common in auto-generated addresses?
• Email Age and History: While not always available, some services can provide insights into how long an email address has been in use, a strong indicator of legitimacy.
• Disposable Provider Detection: The API checks the email's domain against a constantly updated database of thousands of disposable email providers.

Phone number scoring provides a similar level of deep analysis. Instead of just sending a text, it instantly assesses the number itself. The API can determine key attributes that help separate real mobile numbers from virtual ones used by bots. This includes:

• Number Type: Is it a mobile number, a landline, or a VoIP (Voice over IP) number? VoIP numbers are far more commonly used in fraudulent schemes.
• Carrier Information: Identifying the carrier can help spot numbers from providers known to be used for generating virtual numbers in bulk.
• Validity and Connection Status: The system can ping the number to see if it's active and connected to a network without ever placing a call.

By combining these signals, a scoring API generates a simple numerical score, for instance, from 0 to 100, that quantifies the risk. A high score suggests a legitimate user with a long-standing email from a reputable provider, while a low score might indicate a disposable email and a virtual phone number. This allows marketplaces to make automated, risk-based decisions in real-time, long before a fraudster has a chance to act.

Complete Implementation Guide: Integrating Email & Phone Scoring APIs

Integrating email and phone number scoring into your marketplace is a straightforward process that offers immediate security benefits. The entire check happens in the background, adding no friction for good users but creating a powerful barrier for fraudsters. Here's how to implement it in four simple steps.

Step 1: Enhance Your Signup Form

Your existing user registration form is the perfect place to start. You are already collecting an email address and often a phone number. No changes to the user interface are needed. The goal is to analyze the data the user provides at the moment they submit it.

Step 2: Make a Real-Time API Call

When a user clicks "Sign Up," your server should take the email address and phone number they entered and send them to a scoring API. Here's how to integrate Greip's Data Scoring & Validation API:

// Email Scoring API Call
const scoreEmail = async (email) => {
  const response = await fetch(
    `https://greipapi.com/scoring/email?key=YOUR_API_KEY&email=${encodeURIComponent(
      email
    )}`
  );
  return await response.json();
};

// Phone Number Scoring API Call
const scorePhone = async (phone, countryCode = "US") => {
  const response = await fetch(
    `https://greipapi.com/scoring/phone?key=YOUR_API_KEY&phone=${encodeURIComponent(
      phone
    )}&countryCode=${countryCode}`
  );
  return await response.json();
};

// Combined validation during signup
const validateUser = async (email, phone) => {
  try {
    const [emailResult, phoneResult] = await Promise.all([
      scoreEmail(email),
      scorePhone(phone),
    ]);

    return {
      emailScore: emailResult,
      phoneScore: phoneResult,
    };
  } catch (error) {
    console.error("Validation error:", error);
    // Handle API errors gracefully
    return null;
  }
};

Step 3: Analyze the Returned Risk Score

The Greip API responds instantly with detailed JSON objects containing risk scores and analysis. Here are actual response examples:

Email Scoring Response:

{
  "data": {
    "score": 3,
    "reason": "Disposable email address detected",
    "isValid": false,
    "isDisposable": true,
    "isFree": false,
    "isRoleBased": false,
    "isEducational": false,
    "blacklisted": false,
    "domain": {
      "name": "tempmail.com",
      "is_dangerous": true,
      "is_spf": false,
      "is_dmarc": false,
      "is_dkim": false,
      "is_mx": false,
      "is_bimi": false,
      "created_at": "2002-12-11",
      "is_new": false
    },
    "custom_rules_applied": { "total": 0, "rules": [] }
  },
  "status": "success",
  "executionTime": 1,
}

Phone Number Scoring Response:

{
  "data": {
    "isValid": false,
    "carrier": "VoIP Provider",
    "reason": "Virtual number detected",
    "custom_rules_applied": {
      "total": 0,
      "rules": []
    }
  },
  "status": "success",
  "executionTime": 1,
}

Note: Email scores range from 0-3 (0=safe, 1=low-risk, 2=high-risk, 3=too-risky)

Step 4: Create Automated Workflows

Based on the Greip API response, you can create automated rules to handle new signups. Here's a practical implementation:

const processSignup = (emailResult, phoneResult) => {
  const emailScore = emailResult.data.score;
  const phoneValid = phoneResult.data.isValid;
  const isDisposableEmail = emailResult.data.isDisposable;

  // High-risk: Block immediately
  if (emailScore === 3 || isDisposableEmail || !phoneValid) {
    return {
      action: "BLOCK",
      reason: "High-risk profile detected",
      allowSignup: false,
    };
  }

  // Medium-risk: Manual review
  if (emailScore === 2 || emailResult.data.isFree) {
    return {
      action: "REVIEW",
      reason: "Requires manual verification",
      allowSignup: true,
      requiresReview: true,
    };
  }

  // Low-risk: Auto-approve
  if (emailScore <= 1 && phoneValid) {
    return {
      action: "APPROVE",
      reason: "Valid user profile",
      allowSignup: true,
    };
  }
};

This automated system filters out high-risk users instantly while ensuring legitimate customers have a smooth experience. Learn more about preventing fake accounts with these techniques.

By following these steps, you create an intelligent, automated system that filters out bad actors at the point of entry. It's a low-effort, high-impact solution that protects your platform and your users without compromising the signup experience for legitimate customers.

Technical Implementation Flowchart

Flow Explanation:

1. Data Collection: Extract email and phone from signup form
2. Parallel Processing: Simultaneous API calls to Greip services for speed
3. Risk Analysis: Combine multiple signals (score, disposable status, validity)
4. Automated Decision: Route users based on risk profile
5. Action Execution: Block, review, or approve with appropriate messaging

Real-World Case Studies: Stopping Marketplace Fraud with Scoring Technology

To fully appreciate the power of email and phone scoring, it helps to see how it works in practice. Let's consider a few common scenarios that marketplaces face every day and see how scoring provides an effective, real-time solution.

Scenario 1: The Bulk Spammer

A fraudster wants to create 100 seller accounts to spam users with links to a malicious website. They use a script to generate email addresses from a disposable domain like "10minutemail.com" and sign up for accounts.

Without Greip: They simply need to receive confirmation emails to pass basic verification.

With Greip Email Scoring:

// Automated bulk detection
const emailResults = await Promise.all(
  suspiciousEmails.map((email) => scoreEmail(email))
);

// All return: {score: 3, isDisposable: true, isValid: false}
emailResults.forEach((result) => {
  if (result.data.isDisposable) {
    blockAccount(result.email, "Disposable email detected");
  }
});

Scenario 2: The Hit-and-Run Seller Scam

A scammer plans to post a high-value item at a suspiciously low price, collect payments, then disappear. They create accounts using a fresh Gmail address and a $1 VoIP number.

Greip API Analysis:

const emailResult = {
  data: {
    score: 0, // Low-risk score for Gmail
    isFree: true, // But it's a free provider
    isValid: true,
  },
};

const phoneResult = {
  data: {
    isValid: false, // VoIP number flagged
    carrier: "VoIP Provider",
    reason: "Virtual number detected",
  },
};

// Combined risk assessment
const riskLevel = assessCombinedRisk(emailResult, phoneResult);
// Returns: MEDIUM_RISK - requires manual review

Scenario 3: The Metrics Manipulator

A new marketplace is trying to show traction to investors by inflating its user count. The developers write a script to sign up for thousands of accounts using a list of temporary email addresses. A traditional verification system would see these as thousands of new users. An email scoring API, however, would immediately detect the pattern of low-quality, disposable emails and assign them all low scores. These signups can be automatically discarded or placed in a separate "unverified" category, ensuring your growth metrics remain clean and accurate. This allows you to report your true user base with confidence.

In each case, scoring moves the defense from a reactive to a proactive posture. It stops problems at the source, as detailed in this guide on filtering fake users, rather than cleaning up the damage after it's been done. This protects revenue, preserves user trust, and keeps your operational data reliable.

Implementation Challenges & Solutions: Deploying Fraud Prevention Successfully

Integrating any new technology can present challenges, but when it comes to email and phone scoring, most are easily addressed with a thoughtful implementation. By anticipating these potential roadblocks, you can design a system that is both secure and user-friendly.

Challenge: What about legitimate users with low scores?

It's possible for a real user to have a low score. They may have recently switched email providers or be using a valid VoIP number for privacy reasons. A blunt "block all low scores" rule could lead to false positives.

• Solution: Implement a "grey area" in your workflow. Instead of outright blocking users with medium-risk scores, place them in a manual review queue. A quick look by a human can often distinguish a legitimate user from a fraudster. You can also trigger a secondary verification step, like a micro-transaction or a request for additional information, only for this small subset of users. This protects your platform without frustrating good customers.

Challenge: Will API calls slow down the registration process?

User experience is paramount. A slow and clunky signup process will cause users to abandon it, costing you valuable customers. The fear is that an external API call will add noticeable latency.

• Solution: Modern fraud prevention APIs are built for speed. Services like Greip are designed to return responses in milliseconds, not seconds. The scoring process is virtually instantaneous and happens in the background. From the user's perspective, the signup is as fast as it was before. Always choose a provider that guarantees low latency through a service level agreement.

Challenge: Isn't this adding unnecessary friction?

The traditional trade-off in security has always been between safety and convenience. Adding extra steps for users often leads to lower conversion rates.

• Solution: Email and phone scoring are essentially frictionless security measures. Unlike CAPTCHAs or multi-factor authentication, scoring requires no extra input from the user. They simply fill out the signup form as they normally would. The entire security check is invisible to them, especially for the vast majority of legitimate users who will pass with high scores and never know a check even occurred.

By designing your implementation with these solutions in mind, you can build a robust defense against fake accounts while maintaining a seamless and welcoming experience for the genuine buyers and sellers who are the lifeblood of your marketplace.

The Future of Marketplace Security: AI, Machine Learning, and Multi-Layer Defense

The fight against fraud is a continuous evolution, and staying ahead requires looking toward the future of security technology. While email and phone number scoring are powerful tools today, their effectiveness is magnified when combined with other data signals and emerging technologies. Marketplace operators should be aware of these trends to build a defense that is resilient and future-proof.

One of the most significant trends is the fusion of multiple data points for a single, holistic risk assessment. Instead of just looking at an email address, advanced systems combine it with other signals gathered during signup. For instance, you can combine the email risk score with data from Greip's IP Location Intelligence API. If a user signs up with a US-based email and phone number but from an IP address in a high-risk country, the combined risk is much higher than either signal alone.

Artificial intelligence and machine learning are also playing an increasingly important role. These systems can analyze patterns across millions of signups to identify sophisticated fraud rings that might be missed by simple rule-based systems. For example, an AI might detect a network of accounts that all use slightly different email addresses but share a similar browser fingerprint or are connected to the same underlying network (ASN), flagging them as part of a coordinated attack.

Furthermore, the concept of a digital identity is becoming more robust. Instead of just verifying individual contact points, future systems will focus on building a cohesive and trustworthy digital identity for each user over time. This involves passive biometric analysis (how a user types or moves their mouse), device fingerprinting, and behavioral analytics. A user's initial email score is just the starting point of a reputation that evolves as they interact with the platform.

By embracing this multi-layered approach, marketplaces can move from merely blocking bad actors to truly understanding who their users are. This not only enhances security but also opens the door for better user experiences, such as offering trusted users lower-friction pathways for certain transactions. The future of marketplace security lies in this intelligent, data-rich, and holistic view of user identity.

Building Trustworthy Marketplaces: Your Path to Fraud-Free Commerce

For any online marketplace, trust is not a feature; it is the foundation upon which the entire business is built. Fake accounts systematically undermine this trust, creating a toxic environment that drives away legitimate buyers and sellers. While traditional verification methods like email confirmation links and SMS codes are easily bypassed, a modern, data-driven approach offers a powerful and proactive solution. By integrating email and phone number scoring into the registration process, marketplaces can build a formidable, yet invisible, defense against fraud.

This method allows you to distinguish between high-quality users and high-risk fraudsters in milliseconds, without adding any friction to the signup flow. It enables automated workflows that can instantly block obvious threats, flag ambiguous cases for review, and welcome legitimate users without delay. This is not about creating a wall; it's about installing a smart, selective filter at the front door.

We've seen how this technology works, from the technical deep-dive into scoring signals to a step-by-step guide for implementation. We've explored real-world scenarios where scoring defeats common fraud tactics and discussed solutions to potential integration challenges. The path forward is clear: a multi-layered security strategy that starts with robust, intelligent verification at the moment of creation is no longer a luxury, but a necessity for survival and growth.

Ultimately, by investing in tools like a reliable Email Scoring Tool, you are making a direct investment in the long-term health and reputation of your platform. You are protecting your users, preserving the integrity of your data, and building a marketplace that people can rely on. In the competitive digital landscape, the platforms that win will be the ones that prove they are the most trustworthy.

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