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First-Party Fraud

What is First-Party Fraud?

First-party fraud refers to the use of one’s own identity to open an account and/or commit a dishonest act for personal or financial gain. Unlike third-party or synthetic identity fraud, first-party fraud involves no stolen credentials or fabricated identities, making it uniquely difficult to detect using traditional fraud tools.

These bad actors pass identity checks, build initial trust, and then strategically exploit systems through misuse, manipulation, and false claims. For organizations, especially in financial services, buy now pay later (BNPL), telecom, and gaming, first-party fraud is one of the fastest-growing and most operationally burdensome fraud categories, accounting for billions in losses annually.

Common Types of First-Party Fraud

Understanding the tactics employed by first-party fraudsters helps organizations recognize risk signals early and deploy appropriate controls. Common examples include:

  • Bust Out Fraud: A user builds a positive credit history to gain trust, only to suddenly max out credit lines and abandon the account.
  • Chargeback Fraud: Also known as “friendly fraud”, this occurs when a legitimate user disputes a valid transaction to avoid payment.
  • Dispute Abuse (Reg E Fraud): Leveraging Regulation E, bad actors falsely claim unauthorized activity to exploit the 10-day provisional credit window.
  • Goods Lost in Transit (GLIT): The fraudster falsely claims that a shipment never arrived, requesting a refund or replacement.
  • Loan Stacking: Simultaneously applying for multiple loans or BNPL lines across platforms before credit checks catch up.
  • Never Pay / Serial Default: Borrowers use their own verified identity to secure credit or funds with no intention of repaying.
  • De-shopping: Purchasing an item with the intent to use and return it, exploiting generous return policies.
  • Ghost Funding/Check Kiting: Depositing bad checks or invalid ACH transactions to temporarily inflate balances and withdraw funds before the return clears.
  • Better’s remorse: In online gaming and gambling, users place losing bets and later dispute the transaction by falsely claiming account compromise.
  • Government Program Abuse: Individuals provide false information to secure grants, subsidies, or benefits.

How First-Party Fraud Impacts Businesses

The challenge of first-party fraud lies in intent—the same user who was accurately verified at onboarding becomes the bad actor later. This dynamic makes detection complex, especially when institutions lack cross-industry visibility into a user’s behavior elsewhere. Consequences include:

  • Increased operational burden from illegitimate disputes
  • Losses from unrecoverable loans and payments
  • Erosion of trust in automated dispute processes
  • Misclassification of legitimate fraud as customer error

How to Detect and Prevent First-Party Fraud

Stopping first-party fraud requires shifting from static, internal-only data checks to leveraging consortium-powered fraud intelligence. Leading institutions are taking proactive steps by:  

1. Leveraging Purpose-Built First-Party Fraud Solutions  

Generic fraud models often misclassify first-party fraud as low risk because the identity is legitimate. Purpose-built solutions like Socure’s Sigma First-Party Fraud model detect patterns of identity manipulation and dispute (Reg E) abuse across the broader financial ecosystem.

2. Monitoring Behavior Post-Onboarding 

First-party fraud often manifests after account opening. Socure enables real-time monitoring of user behavior to identify when a risk profile changes, empowering institutions to act before losses occur.

3. Detecting Loan Stacking and BNPL Abuse Early

By analyzing application patterns across Socure’s massive consortium (325M+ accounts, 20B+ transactions), Sigma First-Party Fraud identifies identities applying for credit across platforms with suspicious timing or histories of nonpayment.

4. Improving Dispute Investigation Efficiency

With detailed signals on dispute history across institutions, fraud and ops teams can prioritize legitimate disputes, reduce false positives, and manage Reg E compliance with greater confidence and speed.

5. Sharing Intelligence Through Consortium-Based Defense

Socure’s Sigma First-Party Fraud is powered by the largest cross-industry first-party fraud consortium, spanning fintechs, banks, BNPL, gaming, telecome-commerce, and more. This provides unmatched visibility into identities engaging in abusive behavior, even if they’re “new” to your platform.

Socure’s Advantage in First-Party Fraud Prevention

Socure provides the industry’s most comprehensive and accurate defense against first-party fraud by:

  • Offering predictive scores for first-party fraud identity manipulation and the likelihood of dispute abuse
  • Using contextual signals to enhance investigation speed and accuracy
  • Delivering cross-industry visibility through the largest first-party fraud consortium
  • Providing real-time intelligence that can be used at onboarding, transaction, and dispute review

Want to reduce dispute abuse and uncover hidden fraud risks? Learn more about Sigma First-Party Fraud

Frequently Asked Questions

Who commits first-party fraud?

There is no single archetype for a first-party fraudster. The individuals or entities that engage in this type of fraud span a wide range of backgrounds, motives, and tactics. What unites them is a willingness to exploit systems using their own real identity, often appearing legitimate on the surface.

Motivations typically fall into two categories:

  • Opportunism, when a user knowingly takes advantage of a system to avoid paying for goods, services, or loans.
  • Desperation, often tied to financial hardship, job loss, or mounting personal debt.

Tactics include manipulating contact information, abusing chargeback or dispute processes (such as under Regulation E), and exploiting gaps in onboarding, verification, or credit decisioning workflows.

Despite this variability, several broad personas emerge:

  • Everyday Consumers: Some individuals engage in first-party fraud as a one-time decision—filing a false dispute, refusing repayment, or making a purchase with no intent to return. Others repeat these behaviors across multiple platforms, appearing legitimate while building patterns of abuse. Common triggers include financial instability, a perceived lack of consequences, or familiarity with loopholes in dispute processes.
  • Organized Fraud Rings: Criminal networks have evolved to incorporate first-party fraud into coordinated operations. These groups often use real identities—sometimes purchased, manipulated—across multiple institutions to open accounts, stack loans, or file fraudulent claims in volume. Their activity is difficult to trace within a single institution but becomes visible through cross-industry fraud intelligence networks like Socure’s.
  • Insiders: In certain cases, employees within an organization commit first-party fraud by leveraging access to internal systems. This might include inflating applications, bypassing controls, or colluding with external actors. Insider-driven fraud is particularly damaging because it often evades traditional detection models.
Why is First-Party Fraud Hard to Detect?

Because these actors are using their own legitimate identity, they often pass initial KYC and fraud checks. Traditional fraud tools—which focus on detecting stolen or synthetic identities—typically lack the behavioral intelligence needed to spot real identities with intent to commit fraud.

That’s why organizations need advanced capabilities like:

  • Consortium-based behavioral insights to identify repeat abusers across the digital economy
  • Real-time alerts to flag when a known good user starts exhibiting suspicious behavior
  • Predictive scoring for first-party fraud, identity manipulation, and dispute abuse
What is the Difference Between First and Third-Party Fraud?

Fraud isn’t one-size-fits-all. Understanding the distinctions between first, second, and third-party fraud is critical to designing effective risk mitigation strategies, especially as fraud tactics evolve in sophistication.

Here’s a breakdown of the key differences:

  • First-Party Fraud is when a real individual uses their own identity to commit fraud.

Examples:

      • Chargeback fraud: Disputing a legitimate transaction to avoid payment
      • Dispute abuse (Reg E fraud): Exploiting Regulation E’s provisional credit policies
      • Loan stacking: Applying for multiple credit lines across platforms without the intent to repay
      • Goods lost in transit (GLIT): Falsely claiming that a purchase was never received
    • Why it’s hard to detect: The identity is real and will passKYC and credit checks, only to act in bad faith later
  • Third-Party Fraud (Identity Theft) is when a fraudster uses someone else’s identity to open accounts, make purchases, or access services without the victim’s knowledge.

Examples:

      • Phishing or social engineering to gain credentials
      • Credit card fraud using stolen card data
      • Account takeover (ATO) through credential stuffing or SIM swapping
  • Detection approach: Third-party fraud is typically caught by verifying the legitimacy of identity data, addressing mismatches in PII, behavioral anomalies, and device inconsistencies.
Want to protect your business against first-party fraud?

Explore Sigma First-Party Fraud — the industry’s only cross-industry solution designed to detect and stop fraud from real users acting in bad faith.

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