Understanding Synthetic Identity Fraud and How to Prevent It

Financial fraud is evolving, and one of its most sophisticated modern forms is synthetic identity fraud, a scheme that costs financial institutions billions of dollars each year and is growing rapidly. Unlike traditional identity theft, where a real person's credentials are stolen, synthetic identity fraud involves the deliberate construction of entirely new, fictitious identities built from a blend of real and fabricated information. The result is a fraudulent persona credible enough to open accounts, secure credit, and evade detection for months or even years.

Key Takeaways

• Synthetic identity fraud is distinct from traditional identity theft. Rather than stealing an existing person's identity, fraudsters combine real data (such as address or Social Security number) with fabricated details to construct entirely new, fictitious personas that can bypass standard verification systems.
• The threat is growing fast. A combination of widespread data breaches, AI-powered identity generation, remote onboarding, and the inherent difficulty of detection has made synthetic identity fraud one of the fastest-growing forms of financial crime. 
• No real victim means no early warning. Because synthetic identities are not tied to a real person, there is nobody to notice unauthorized activity and raise an alert, allowing fraud to go undetected for months or years, often only coming to light when it is too late to recover losses.
• Multiple industries are at risk. Financial services payments, collections, auto lending), telecommunications, and government agencies all face exposure, with any organization that extends credit or processes high-value transactions being a potential target.
• Detection requires a multi-layered approach. Effective prevention combines advanced identity verification, AI and machine learning-powered anomaly detection, behavioral monitoring, and ongoing account scrutiny; no single control is sufficient on its own.
• The consequences go beyond financial loss. Undetected synthetic identities can be recycled for money laundering, benefits fraud, and other criminal activity, while also exposing organizations to regulatory penalties, lasting reputational damage, and causing long-term harm to real individuals.

What is Synthetic Identity Fraud?

Synthetic identity fraud is a complex form of financial crime in which fraudsters combine real and fictitious personal information to create new identities. Rather than taking over an existing identity, perpetrators will use legitimate data merged with fabricated credentials to create a false persona. Synthetic identity can appear genuine to credit bureaus and other automated systems, which means criminals can open bank accounts, apply for credit, and conduct illicit transactions without immediate detection. Synthetic identities can also appear as new, which helps criminals create thin-file records in credit bureaus that they can then exploit over time. 

Synthetic identity fraud poses critical challenges for banks, fintech firms, and other institutions, as synthetic profiles typically bypass traditional identity verification measures and can elude manual review. Advancements in artificial intelligence and deep learning create an additional challenge, since the process of generating and maintaining synthetic identities has become increasingly easier and more sophisticated.

How Does Synthetic Identity Fraud Work?

Synthetic identity fraud operates through a layered series of tactics, with perpetrators leveraging both traditional and technology-driven methods to construct fraudulent identities:

• Acquire legitimate data: fraudsters often start by purchasing legitimate data elements that have been exposed through breaches, such as Social Security numbers or credit profiles (often those belonging to children, recently deceased people, or individuals with little credit history) to avoid drawing immediate suspicion.
• Combine legitimate and fabricated elements: the real data points are then combined with fabricated or altered details, such as made-up names, addresses, and phone numbers, to create a new identity that can navigate automated verification systems.
• Build a credit profile: once the identity is created, the fraudster may spend months or years building a credit profile to appear legitimate before committing bust-out fraud with high-volume fraudulent charges
• Mass-produce synthetic identities with AI: organized groups of fraudsters may use automated scripts or bots to mass-produce synthetic identities to rapidly open multiple accounts across different financial institutions to increase their chances of success. AI and deepfake technologies also allow criminals to generate highly realistic documents and digital footprints that escape traditional fraud controls.

Why Do Fraudsters Use Synthetic Identities?

Traditionally, credit fraud has been committed through two main methods:

• First-party fraud: with first-party fraud, the perpetrator uses their own identity (sometimes obscured or altered) to carry out fraudulent activities. Although significant losses have resulted from first-party fraud, organizations are typically not targeted multiple times by the same individual. When fraud data is shared among institutions, this further limits offenders’ opportunities across the network.
• Third-party fraud – with third-party fraud, the fraudster assumes the identity of another individual and uses their stolen credentials to commit fraud. While this method makes tracing the criminal more challenging, it is limited as it requires access to unique, authentic identity information. Importantly, since a genuine person is being impacted, there is someone able to notice and report the unauthorized use of their identity.

Determined to circumvent these barriers, fraudsters are now increasingly employing a third tactic: synthetic identity fraud. Because criminals construct wholly new identities by blending real and fabricated details, there is no direct linkage between these synthetic identities and real individuals, which means criminals can generate countless false identities with less risk of a victim detecting the fraud and raising an alert.

Synthetic identities enable fraudsters to dramatically expand and automate their schemes. Once they identify a vulnerable organization, they can rapidly multiply fraudulent applications, industrializing their attacks to maximize financial gain.

Why Is Synthetic Identity Fraud Growing?

Synthetic identity fraud is driven by multiple factors that expose vulnerabilities across the financial ecosystem:

• Data breaches: the frequency and scale of data breaches have led to a widespread availability of personal data on the dark web, which fraudsters can use to Frankenstein synthetic identities
• AI technology advancements: fraudsters use artificial intelligence and deepfake technology to create fake identities and fabricate false supporting documents such as IDs, utility bills, and bank statements
• Remote onboarding: to improve customer experience, financial institutions often prioritize online account openings, which gives fraudsters quick paths to exploit
• Social Security number randomization: in 2011 the Social Security Administration changed how SSNs were assigned and removed the area numbers from the first three digitals. SSNs are now randomized, which makes it harder for fraud detection algorithms to detect anomalies
• Difficult to detect: synthetic identity fraud is also growing because it is hard to stop. The fictitious profiles created by fraudsters are often credible enough to bypass traditional verification controls and there are no real victims to recognize and report unauthorized activity

What Are the Long-Term Risks of Identity Fraud?

Synthetic Identity Fraud Can Masquerade as Bad Debt and Negatively Impact the Collections Process

Synthetic identity fraud presents a particularly insidious problem for collections teams because the fraudster is long gone by the time an account lands in the queue. After months or even years of responsible payment behavior designed to build credit credibility, the fraudster executes a "bust-out", maxing out available credit lines before vanishing entirely. 

The delinquent accounts look like ordinary bad debt, so collectors spend time and resources attempting to reach a debtor who simply doesn't exist. The absence of a genuine debtor means there is no resolution: the account will age through the collections workflow, consuming time and cost, with no repayment at the end. 

Synthetic Identity Fraud Causes Systemic Damage to the Entire Financial Ecosystem and Contributes to Broader Financial Crimes

Synthetic identity fraud introduces enduring risks that can compromise the integrity of entire financial ecosystems. Synthetic identity profiles may persist undetected for years, acting as vehicles for additional forms of criminal activity. For example, fraudsters can leverage dormant synthetic entities to perpetrate money mule schemes, launder illicit proceeds, obtain government benefits fraudulently, or facilitate fraudulent transactions that bypass standard controls.

In addition, these manufactured identities can be recycled or sold among criminal networks, which means their threats are amplified across multiple institutions and sectors. Fraudsters use synthetic accounts as tools to send phishing messages, launder money, set up money mule accounts, and construct complex fraud networks that are extremely difficult to trace

Which Industries Are the Most Impacted by Synthetic Identity Fraud?

Synthetic identity fraud poses major challenges across several sectors, but its impact is more severely felt in industries where access to credit, payment instruments, or high-value transactions is central.

• Financial services, including retail banks, credit unions, and fintech lenders, face some of the highest exposure, as fraudsters exploit automated lending, credit card issuance, and digital onboarding processes to access funds or lines of credit using manufactured profiles
• Payment processors and digital wallets are also primary targets, due to the rapid growth of online transactions and the limited verification required for account creation
• Telecommunications providers, particularly mobile carriers, are also frequent victims. Synthetic identities are used to acquire devices or service contracts that can be resold or used to bolster a fabricated credit history. According to SentiLink’s H2 2025 Fraud Report, the telecom industry is one of the most-impacted sectors, with a mean synthetic identity fraud rate of 2.23% for the second half of 2025. 
• Auto lending and leasing providers are at risk, as fraudsters establish synthetic profiles with strong credit scores to secure vehicles that are then resold or exported
• Government agencies face risks related to synthetic identities being used for fraudulent benefits claims, tax returns, or healthcare services, with detection often made difficult by the lack of data integration and legacy verification systems

How to Detect and Prevent Synthetic Identity Fraud

How to Identity Red Flags and Common Warning Signs

Detecting synthetic identity fraud requires vigilance for a range of telltale signs that can signal fraudulent activity long before losses accrue. Key red flags include:

• Inconsistencies in Social Security Number information: according to SentiLink’s H2 2025 Fraud Report, the strongest signal of synthetic fraud is historical data showing that the applicant has a better-matching SSN than the one listed on the application, meaning the name, date of birth, and other identity elements are more strongly associated with a different SSN. 
• Limited credit history: credit accounts recently opened and very few transactions, especially if the applicant is older
• Sudden change in credit behavior: recent activity spikes or an unusual pattern of rapid account openings in a short time frame
• Address anomaly: high volume of applications coming from a single address, particularly mail drops or commercial addresses
• Re-use of information: same address, date of birth, or name used across multiple applications
• Cross-partner activity data: SentiLink warns that the second-strongest signal of synthetic identity fraud is activity data indicating links between a new application and other high-risk applications.

6 Strategies to Combat Synthetic Identity Fraud

• Use advanced identity verification: since AI has made it easier to create false documents, organizations need to move beyond traditional documents and use advanced identity verification methods such as facial recognition, biometrics, and active liveness checks
• Define rules to identity fraud patterns: use analytics to identify patterns of fraud, such as linked accounts used to pay fake bills for each other or to mimic payroll deposits, phone numbers, names, email addresses being re-used in different applications
• Use link analysis to see where some of the same information is re-used: doing so will allow you to monitor for links between, for example, declined applications for credit risk and new applications where some of the same information is used
• Leverage AI and machine learning: AI-powered fraud detection delivered through FICO^® Enterprise Fraud Solution will automatically detect subtle behavioral patterns and anomalies that indicate synthetic identities
• Ongoing account monitoring: because fraudsters can build a credit history for years, implement long-term monitoring of transactions and behavior to spot inconsistencies even after account opening
• Tag suspicious accounts: once an account is opened and credit extended, the account can be scrutinized more closely and regularly to look for suspicious account activity such as sudden shifts in usage patterns, mailing address changes, or falling into arrears early

FICO's Solutions to Identify and Detection Synthetic Identity Fraud

FICO delivers robust, multi-layered solutions designed to counter synthetic identity fraud throughout the entire customer lifecycle. Leveraging advanced analytics, machine learning, and FICO’s proprietary Responsible AI models, these fraud detection systems identify behavioral anomalies and patterns indicative of synthetic activity, even as fraudsters evolve their tactics.

For example, TELUS, the leading Canadian communications and information technology company with 15.2 million customers, used FICO's fraud detection solution to combat the risk of subscription fraud and ensure better customer experience. Thanks to FICO TELUS implemented a comprehensive fraud detection system to identify and stop fraud before a fraudster can complete an application and leave the store with high value merchandise. 

To learn more about FICO's fraud detection capabilities:

• Download the 2026 Chartis vendor report for Enterprise and Payment Fraud Solutions
• Download our whitepaper to understand the 7-step path to scam prevention and customer protection
• Learn more about strategies to fight first party and synthetic ID fraud 
• Explore FICO^® Enterprise Fraud Solution, Powered by FICO® Platform