Synthetic Identity Fraud: The Elusive Challenge and Effective Detection Methods
Synthetic identity fraud has become a growing concern for the FinTech sector, presenting unique challenges in terms of detection and prevention. Unlike traditional identity theft, which involves stealing someone’s existing identity, synthetic identity fraud involves the creation of a completely new identity using a mix of genuine and false information.
Fraudsters typically start by acquiring a legitimate social security number, often obtained from vulnerable individuals who are unlikely to notice any unusual activity. They then combine this real piece of information with fabricated data, such as names, birth dates, and addresses, to build a synthetic identity that appears legitimate on the surface. This combination of genuine and false data makes it extremely difficult to detect synthetic identities during initial identity checks.
Once a synthetic identity is established, fraudsters can proceed with a technique known as piggybacking. This involves deliberately conducting small transactions and promptly repaying them to create a positive credit history for the synthetic identity. After building a decent credit profile, the fraudster carries out a bust-out scheme, maxing out the credit associated with the synthetic identity and disappearing. Financial institutions are left burdened with the losses, while the fraudsters escape unnoticed.
The attractiveness of synthetic identity fraud lies in its elusive nature. It often goes undetected until the bust-out occurs and is challenging to prosecute due to the lack of a direct, identifiable victim in the traditional sense. This poses serious threats to financial institutions, leading to substantial annual losses. Furthermore, innocent individuals whose information was unknowingly used to create synthetic identities can also be unintentionally involved in the scheme.
The complex nature of synthetic identity fraud makes it a formidable challenge for financial institutions to detect. The use of genuine information, such as a valid social security number, combined with fabricated details, allows synthetic identities to pass initial identity verification checks. Additionally, the current structure of the credit system contributes to the difficulty in identification. The existence of credit files created for synthetic identities, even if initially denied credit, aids fraudsters in establishing a credit history over time.
The fragmentation of data across multiple financial institutions and credit bureaus further complicates the detection process. A synthetic identity may have relationships with various banks and credit card companies, making it challenging to obtain a comprehensive view of suspicious activity without effective information sharing.
Moreover, since synthetic identity fraud lacks a direct victim, traditional fraud detection systems that rely on victim reporting become ineffective. Fraudsters are also becoming more sophisticated, utilizing advanced techniques and data breaches to obtain valid personal information and employing artificial intelligence to create credible synthetic identities, making detection even more challenging.
To combat synthetic identity fraud effectively, financial institutions need to shift from traditional detection methods and adopt comprehensive approaches. This includes leveraging advanced technologies and machine learning algorithms to identify patterns and anomalies indicative of synthetic identity fraud. By implementing these steps, financial institutions can better equip themselves to mitigate the risks of synthetic identity fraud and protect their businesses and customers.
Synthetic identity fraud continues to pose a significant threat to the financial ecosystem, undermining the credibility of financial institutions and causing substantial financial losses. It is crucial for stakeholders to understand the complexities of this type of fraud and take proactive measures to detect and prevent it. With the right tools and strategies, the FinTech industry can tackle the elusive challenge of synthetic identity fraud and ensure a safer and more secure financial environment for all.
