Application Fraud Detection & Prevention: Examples and Best Practices 

Application fraud is a rapidly evolving threat in the digital economy, with businesses around the world reporting rising losses from identity and account fraud as online onboarding grows more complex. Nearly 60% of companies saw increased fraud losses in 2025, driven by sophisticated attacks that exploit weaknesses at account opening and identity verification.

The impact extends beyond direct financial loss: fraud erodes customer trust, adds operational burden and increases compliance risk for businesses that must balance security with seamless digital experiences. In this article, we’ll explain what application fraud looks like today, highlight real‑world examples and outline practical, low‑friction detection and prevention strategies that modern organizations can adopt.

What Is Application Fraud?

Application fraud occurs when a person provides false or manipulated information during the online application process for a financial product — such as a loan, insurance policy, credit card or bank account — with the intent to deceive before approval. It typically involves tactics like using stolen or synthetic identities, misrepresenting income or employment or submitting altered documents to appear creditworthy or eligible.

This type of fraud thrives in digital environments where fast, frictionless onboarding is the norm. Fintechs, digital banks and insurers are especially vulnerable, as they often prioritize user growth and seamless customer experience.

Without strong application fraud detection and prevention measures in place, businesses risk onboarding high-risk users who default, commit further fraud or trigger compliance breaches. Over time, the cumulative impact can erode revenue, operational efficiency and trust.

Application Fraud vs New Account Fraud

Though often used interchangeably, application fraud and new account fraud are distinct, and understanding the difference is key to effective fraud prevention.

Application fraud refers to the use of false, manipulated or stolen information to apply for a financial product, such as a loan, credit card or insurance policy. The fraud happens before approval, with the intent to mislead a business into granting access to services or credit the applicant wouldn’t otherwise qualify for.

New account fraud, by contrast, begins after the account is successfully opened. Fraudsters use accounts created with fake or stolen identities to carry out malicious activities, ranging from promotional abuse and chargeback fraud to money laundering and mule account operations.

Both attack the early stages of the customer lifecycle; however, application fraud involves gaining entry under false pretenses, while new account fraud exploits access after entry. A robust fraud strategy must account for both and ideally detect risk signals as early as the first form field.

3 Examples of Application Fraud

Application fraudsters are always a problem, but not all of them target the same kinds of companies. Let’s look at three examples to explore the range of attacks you may encounter.

Insurance Application Fraud

Insurance fraud isn’t anything new but the digitization of insurance companies has made them even more of a target for fraudsters, opening more loopholes and allowing schemes to scale more easily.

In this case, fraudsters might:

• Make false or exaggerated claims: For instance, inflate their salary to apply for a mortgage.
  
• Intentionally damage the item to make a claim: This is particularly common with high-end electronics and gadgets.
  
• Lie about who the policy is for: Consider car fronting, for instance: It’s when a policy is taken out by someone on behalf of another driver.

A point to note is that searching the application for inconsistencies is already part of the insurance due diligence process.

The major difference to keep in mind is that with online users, you can easily access interesting new data that wouldn’t otherwise show up on a credit scoring report – such as their digital footprint.

Digital Bank Account Application Fraud

We’ve got a full post on how fraudsters open bank accounts, but it all boils down to creating fake profiles using stolen ID documents.

Their end goal could be to use the account as a bank drop, to exploit a referral promotion, or to launder money.

Neobanks and digital banks are particularly careful not to add too much friction at the onboarding stage, in order to provide a pleasant customer journey – which is exactly why fraudsters can slip through the net.

This may cause problems such as:

• promo and bonus abuse
• KYC and AML fines
• legal issues  
• loan defaults

And, of course, there are all the hidden costs of fighting fraud, such as lost customer service or reputational damage.

Loan Application Fraud

As far as financial products go, loans are probably some of the riskiest to offer. They also offer the highest reward for fraudsters who manage to fool the standard or alternative credit scoring process. 

Fraudsters who target loan companies usually create synthetic IDs. These are identities made up of data from real people (who either willingly lend their IDs or have them stolen). 

The reason these types of ID are so effective at fooling lenders is that they’re designed to target people with non-existent credit history, including the unbanked and underbanked. Fraudsters have been known to stoop as low as using children or deceased people’s IDs in order to fool the credit scoring stage. 

How Does Application Fraud Impact Businesses?

Application fraud can undermine a business from multiple angles. Financial losses are the most visible — from loan defaults and false insurance claims to promo abuse and misuse of services. But the damage rarely ends there.

Fraudulent applications also strain internal resources. Risk, compliance and customer support teams must investigate cases, diverting time from core operations and slowing down legitimate onboarding.

The regulatory consequences can be severe. In sectors governed by strict KYC or AML requirements, failing to catch bad actors early may lead to fines, audits or even reputational warnings from authorities.

And then there’s brand trust. A business associated with repeated fraud incidents risks losing customer confidence and partner credibility. In digital-first industries, where speed is vital and competitors are close, that erosion of trust can directly impact growth.

Ultimately, effective application fraud prevention isn’t just about protecting revenue but also about safeguarding long-term reputation, efficiency and compliance.

How To Prevent Application Fraud

Preventing application fraud starts with gaining deeper insight into who your applicants really are without adding friction or slowing down the onboarding process. Today’s most effective strategies rely on real-time signals that go far beyond traditional identity checks.

Uncover Hidden Risk with Digital Footprint Analysis

Rather than relying solely on static forms or document uploads, digital footprint analysis allows you to evaluate an applicant based on data they provide naturally, such as their email address, phone number or IP address. These signals can reveal whether an email is disposable, if a phone number is tied to a virtual SIM or whether an IP address is masked through a proxy or VPN.

Crucially, you can also assess an individual’s online presence in real time. A complete lack of social and digital activity linked to their credentials may suggest a fabricated identity, while a broad, organic digital footprint often indicates a legitimate user. This layer of context helps you spot high-risk applicants early, before escalating to expensive identity verification steps.

Strengthen Checks with Device and Browser Intelligence

Fraudsters rarely stop at a single attempt. That’s why analyzing how a user connects — not just who they claim to be — can uncover suspicious patterns. Device intelligence combines browser configuration, OS data, cookie hashes and more to create a unique fingerprint of each user.

This allows you to detect connections between seemingly unrelated accounts, flag repeated use of the same device across multiple applications or spot advanced evasion tactics like spoofed browsers. By identifying these signals at the application stage, businesses can block coordinated fraud networks before they take root.

Catch Scaled Attacks with Behavioral Signals

How a user interacts with your application form can be just as telling as the information they provide. Velocity rules help detect unnatural behavior, such as forms filled in milliseconds, rapidly changing IPs or multiple name submissions in quick succession. These are often signs of automated scripts or bot-driven attacks.

Understanding normal versus suspicious user behavior in real time allows your fraud prevention systems to react immediately, without interrupting the journey for legitimate applicants.

Use AI to Stay Ahead of Emerging Threats

Application fraud tactics are constantly evolving. That’s why leading organizations now deploy AI-powered risk scoring tools that adapt based on known fraud patterns. By learning from flagged cases, these systems automatically recommend updated risk rules, identify hidden correlations, and help teams strike the right balance between fraud prevention and user experience.

AI also helps reduce false positives by contextualizing risk — improving accuracy over time while minimizing customer friction. This is particularly powerful in high-volume environments where manual review alone can’t scale.

Why SEON Is Built for Application Fraud Prevention

SEON equips businesses with a powerful, unified view of risk, helping them detect and stop application fraud before it enters the system. By connecting 900+ real-time digital signals, SEON goes beyond surface-level checks to uncover context others miss: from device setup and behavioral patterns to online footprint and identity history.

All of this happens in one streamlined platform, giving fraud and compliance teams a central command center to assess risk, automate decisions and stay in control. Whether you’re focused on reducing KYC costs, accelerating safe onboarding or strengthening AML compliance, SEON brings the clarity and precision today’s digital businesses need.

FAQ