Application Fraud: How to Detect & Prevent It For Your Business

When customers need new credit cards or a loan, they don’t want to plan a visit to a branch to fill out paperwork in triplicate. They’d rather be able to apply for these products conveniently from their phones or laptops. Unfortunately, bad actors, using stolen or fabricated information, are also taking advantage of these conveniences. Criminals are using this fake information to create personas or using bots to launch widespread applications for financial benefits or products without any intention of paying them off. Research conducted by identitytheft.org in 2025 found losses from identity theft-related crimes, including application fraud, are estimated to be at $10.2 billion, according to FBI data.¹

In this article we’ll explore how application fraud works, how it stands apart from other early stage fraud like new account fraud, and why banks and businesses should focus on building digital trust with customers from day one to ensure only trustworthy applicants are approved for financial services and products. 

Key Takeaways

• Fraudsters commit application fraud using forged, manipulated, or synthetic identities to access financial services or resources.
• Identity theft-related losses were valued at $10.2 billion, according to the FBI.
• Consequences of application fraud for banks and businesses can include financial losses, reputational harm, regulatory scrutiny, and increased operational costs.
• Preventing application fraud requires a multii-layered approach that includes behavioral biometrics, shared network intelligence, and real-time data analytics.

What is Application Fraud & How Does It Work

Application fraud is when fraudsters target an organization’s customer onboarding mechanisms by using fake, stolen, or synthetic identities to access financial services, products, or resources. This may include new business or bank accounts, opening credit cards, bank loans, or promotional offers. It can also involve altering application information to dodge an organization’s security protocols.

Here are some of the tactics criminals use to commit application fraud: 

• Bot Attacks: Criminals can use bots to study a bank or business’ application processes. With these insights they can program malicious bots to automatically complete forms, filling out large volumes of applications in very little time and test fabricated data in the application stage.
• Money Mules: Criminals can use witting or unwitting money mules to open bank accounts using their own names and credentials. In some cases, money mules provide fake information to apply for financial services like credit or debit cards. In some cases, money mules open new bank accounts to build legitimacy over time looking for a larger payout in the future.
• Synthetic Identities: Losses from synthetic identity fraud (a key enabler of application fraud) are estimated to reach $23 billion by 2030.² Recent research shows that criminals have mastered GenAI tactics to commit fraud attacks, including voice cloning, phishing, social engineering, and deepfakes. Combined with automated solutions, criminals can create fake identities at a rapid scale targeting vulnerabilities in organizations’ identity verification solutions. 
• Stolen Identities: Multiple data breaches over the years have compromised massive volumes of personal customer data. Criminals can easily access or buy this information or use phishing tactics to gain new information from victims. This stolen information can be used in the application process without the legitimate owner realizing it.

“45% of applications suspected as fraudulent are confirmed to be fraud after manual investigation.” 

– Catarina Godinho, Senior Product Marketing Specialist, Feedzai

4 Crimes Enabled by Application Fraud

Using any or several of these methods, criminals can access and abuse different financial products. Here are some of the most common criminal activities fueled by application fraud.

• Bust Out Fraud: For many criminals, the entire point of gaining access to a service is to exploit its maximum financial potential. Once they open an account, they build a positive payment history to raise their credit line using a fake persona. After this stage, they can max out their credit and disappear without any intention of paying off their debts. 
• Credit Card Fraud: Using fake or synthetic identities, criminals can open credit cards with application fraud. From there, they can max out the card’s balance with purchases and resell the goods. If the card was opened with someone else’ credentials, that person may see serious damage to their credit report.
• Bank Loan Abuse: Some criminals think larger than the plastic cards that fit in a wallet. They apply for bank loans to get large sums of money by providing fake documents or forged income statements. Once the loan is approved, the criminals steal the funds, leaving banks to face the loss.
• Promotional Offer Abuse: The initial enticements banks offer are also top targets for application fraud. Criminals exploit cash-back offers, enrollment bonuses, and other perks designed to attract legitimate customers. Once they receive the benefit, they immediately close the account.

Application Fraud vs. New Account Fraud: Key Differences

While they share similarities in methodology, there are critical differences between application fraud and new account fraud. 

• Application Fraud: Application fraud is the process of applying for services and financial products with fake, doctored, or stolen personal information. Critically, it happens before an account is opened with a bank or business.  The goal is to deceive a bank’s verification system to access these resources. More 
• New Account Fraud: Meanwhile, new account fraud (NAF), happens after a successful application fraud attempt. At this stage, a new financial account has been created using fraudulent methods. Once opened, criminals may use the account to launder money or rack up debts with no intention of paying them back.

How Application Fraud Impacts Businesses

Application fraud is particularly concerning because it’s effectively an opening salvo for additional, serious fraud losses. If executed correctly, it can have a wide-ranging impact on banks, businesses, and customer trust. In other words, it’s the first damaging domino to fall that can result in serious effects. These include: 

• Financial Losses: Banks and businesses suffer direct monetary losses from unpaid debts incurred by the fraudsters. Additionally, organizations will incur more costs as they investigate and mitigate any application fraud incidents. 
• Reputational Damage: When a fraudster successfully commits application fraud using a customer’s data, it reflects poorly on the bank. It indicates that the bank lacks sufficient verification processes that ultimately put the customer in harm’s way and threatens the organization’s public reputation. Worse yet, it may signal to other criminals to launch additional application fraud attacks.
• Regulatory and Compliance Risks: Regulators will also take notice of failures by banks and businesses to catch application fraud. Consequences may include fines, penalties, and investigations for non-compliance with anti-money laundering (AML), Know Your Customer (KYC), and data protection regulations.
• Increased Operational Costs: Addressing application fraud attacks will require considerable investment of human resources, technological investments, and training to resolve the issue.

What to Look Out for in Application Fraud

The challenge for banks and businesses in catching application fraud is that it happens before account opening, leaving banks with little previous data to review to understand the applicant. It’s essential to catch application fraud before criminals or fraudsters can access loans, credit cards, or other financial assets. 

Some key criteria for banks to monitor to detect application fraud include:

• Inconsistent Personal Information: Look for deviations between data outlined in an application (e.g., name, address, date of birth) and information found in public records, credit bureaus, and other trusted databases.
• Unusual Contact Details: Watch for applicants that use Voice over IP (VoIP) phone numbers, disposable emails addresses, or home addresses linked to known fraud accounts, or multiple applicants that share similar details. 
• Document Irregularities: Review financial and income documents for tampering, mismatched fonts, manipulated images, or inconsistencies with government-issued IDs.
• Synthetic Identity Indicators: There are multiple red flags for synthetic identity fraud, including a “thin” or non-existent credit history or a government identification number that doesn’t match an applicant’s age, suggesting a fake persona.
• Rapid Application Speed: A high volume of applications in a short timeframe from a single IP address or device ID, that uses slightly altered information is a red flag that a bot attack is underway at the application stage. Look for signs that information is being copied and pasted, keyboard shortcuts are being used, or that the applicant is too familiar with the form.
• Income and Employment Irregularities: Employment details that cannot be verified, income that seems unrealistic for the applicant’s stated occupation, and other anomalies are warning signs of an application fraud. 

How to Prevent Application Fraud

There is no silver bullet to stopping application fraud. Instead, it takes a multi-layered solution to monitor for application fraud red flags. Ideally, a financial institution’s approach to application fraud prevention should contain these key elements.

• Implement AI and Machine Learning: Use advanced analytics to uncover concerning patterns in application data, leveraging behavioral biometrics and real-time monitoring.
• Sharing Network Insights: Knowledge is a powerful tool in the fight against fraud. Banks and financial institutions can easily share their insights with other organizations without compromising on customer privacy or sharing sensitive data. Collaborate seamlessly and securely with other institutions to catch fraud patterns across the industry.
• Monitor Applicant Behavior: Because application fraud happens before an account is open, there may not be enough data to understand whether a customer’s behavior is normal when compared to similar users. Watch for customers typically engaging with an application page, how quickly forms are filled out, typing speed, and more.
• Use AI for Document and Identity Verification: Criminals are using GenAI to create fake documents to bypass security. It’s important to fight AI fraud with your own AI solutions. Use technology that can identify AI-generated forgeries and cross-check application data with reliable, trustworthy sources.
• Embrace Risk-based Dynamic Authentication: It’s important to be able to assess risks in real time. Use risk-based step-up authentication to request additional information if an applicant demonstrates unusual behavior (e.g., a suspicious IP address, inconsistent data, or an application submitted at an unusual time of day).

How Feedzai Tackles Application Fraud

Feedzai employs an advanced, AI-native platform to proactively combat application fraud, focusing on detecting illicit activities from the very first interaction. Feedzai’s solution combines behavioral biometrics, device fingerprinting, and network signals to build a unique profile of applicants. This shifts fraud detection to the earliest possible stage of the customer lifecycle.  

Feedzai’s approach to application fraud prevention leverages several key components, each contributing to a robust defense:

• Behavioral Biometrics: Feedzai analyzes human-to-tech interactions like keystrokes, mouse movements, and smartphone handling. Profiling these unique behavioral patterns distinguishes genuine applicants from fraudsters using stolen or fake identities.
• Device Intelligence: Feedzai gathers device data (model, OS, resolution, language) to detect anomalies like device type changes, rooted devices, or unrecognized devices, all of which are common fraud indicators.
• Network Intelligence: The solution uses applicant IP data (unusual locations, new ISPs, risky proxy/Tor, and “fast traveler” activity) to detect if multiple applications originate from the same device, IP, or network, crucial for identifying synthetic identity and money mule rings.
• AI-Powered Analysis: The diverse data collected from these sources is encapsulated into a unique profile for each user. Hybrid AI technology continuously analyzes and updates these profiles, comparing current session behavior to established baseline profiles. 
• Continuous Authentication: The solution silently and continuously authenticates activity to ensure the legitimate user remains in control without introducing friction. At the same time, it proactively flags suspicious patterns indicative of synthetic or stolen identity fraud.  

By integrating these robust behavior signals, Feedzai’s solution provides a holistic view of risk, enabling financial institutions to stop fraudulent applications early. This drastically narrows the window for fraudsters, particularly when historical data is limited.

Resources

• Blog: What Is Synthetic Identity Fraud: How to Detect & Prevent Against It?
• Commentary: Feedzai’s Acquisition of Demyst Is a Modern Response to Today’s Fraud
• Solution Sheet: Smarter Fraud Detection with Feedzai IQ
• Solution: Account Takeover Fraud Solution