Over the past 20 years, economic downturns, including the Great Recession from 2007-9, have led to an increase in financial crime. One growing issue is synthetic identity fraud, which Forbes predicts could result in losses of up to $5bn by 2024. However, artificial intelligence services are providing their best expertise to overcome such heinous acts. Financial institutions are struggling to combat this complex crime, as they face challenges in identifying, classifying, and overcoming it.
According to a global compliance survey of 800 C-suite and senior compliance decision-makers, synthetic identity fraud is the type of fraud that they are most concerned about in 2023. This concern has surpassed elder fraud and romance scams, which were reported at 25 percent and 22 percent respectively. Regulators and top artificial intelligence solution companies are also becoming increasingly concerned about this issue.
Cyberattackers employ both genuine and counterfeit personal information, such as Social Security numbers, birthdates, addresses, and employment records. This enables them to fabricate false or synthetic identities.
The fastest growing form of identity fraud today is synthetic identity fraud. It involves creating new accounts using a combination of real and fictitious identity data. This allows attackers to gain credit and account privileges undetected by many organizations’ fraud prevention techniques, models, and security stacks.
Synthetic identity fraud is difficult to identify because it can easily trick existing fraud detection. This information is sourced from the Federal Reserve’s report on mitigating synthetic identity fraud in the U.S. payment system.
Synthetic Identity Fraud: The Latest Scam To Watch Out For
Synthetic identity theft is a type of fraud where someone uses your real identity. The most common type is when they open a new credit account in your name. They can also use your credit report and score to apply for new credit or loans. This can harm your credit score and make it difficult to obtain new credit or pay off existing debt.
In addition, synthetic identity theft can be used for criminal purposes such as identity theft, fraud, or tax evasion. Although the thief may not succeed in committing these crimes, they can still obtain your information and cause serious financial harm. It is important to take steps to protect your identity and monitor your credit report regularly.
Synthetic identity fraud is a type of theft in which criminals create fictitious identities by combining real and fake information. Unlike traditional identity theft, where criminals steal an individual’s complete identity, synthetic identity fraud involves the creation of a new identity that does not belong to any real person.
Here’s how synthetic identity fraud typically works:
1. Creation of Synthetic Identities
Fraudsters gather real personal information, such as Social Security numbers, addresses, and names, from various sources. They then combine this information with fictitious data to create synthetic identities that don’t match any existing person.
2. Establishing Credit History
The fraudsters apply for credit cards, loans, or other financial accounts using the synthetic identities. In the early stages, they often target institutions with less stringent identity verification processes, such as subprime lenders or credit unions.
3. Building a Credit Profile
Over time, the fraudsters work to establish a positive credit history for the synthetic identity by making small purchases, paying bills, and maintaining a seemingly responsible financial behavior. This is done to increase the creditworthiness of the synthetic identity and make it more appealing to lenders.
4. “Bust-out” Phase
After the synthetic identity has built a sufficiently high credit score, the fraudsters may attempt to “bust out” by maxing out credit lines or taking out large loans. They may then disappear without repaying the debts, leaving the financial institution or lender to bear the losses.
Underlying Challenges in detecting Synthetic Identity Fraud
Synthetic identity fraud is particularly challenging to detect and combat because the identities being used do not belong to real individuals. The fraudsters intentionally create a blend of real and fake information, making it difficult for institutions to identify the fraudulent activity.
Here are some challenges associated with detecting and preventing synthetic identity fraud:
1. Lack of Identity Verification
Traditional identity verification processes may not be effective in detecting synthetic identity fraud since the synthetic identities are designed to have elements of real information.
2. Time Delay in Fraud Detection
Fraudsters may spend months or even years building credit profiles for synthetic identities before engaging in fraudulent activities. This delay makes it harder for institutions to recognize suspicious behavior.
3. Data Fragmentation
The use of multiple sources of personal information to create synthetic identities can make it difficult to identify fraudulent activity. The legitimate components of the identity may match real individuals, further complicating the detection process.
4. Collusion and Layering
Fraudsters often employ complex techniques such as colluding with other individuals or layering multiple transactions to further obfuscate their activities and avoid detection.
How to Combat Synthetic Identity Fraud
The challenge of reducing false positives that harm real customers while detecting synthetic identities that defraud a business is a complex one. Various identity-based artificial intelligence (AI) providers are tackling this issue differently, but all rely on decades of data to train models and assign trust scores by a transaction.
The objective is to improve the performance of supervised machine learning algorithms in detecting anomalies that may not be apparent through existing fraud detection methods. This is achieved by incorporating unsupervised machine learning, which explores data for new patterns.
The integration of both supervised and unsupervised machine learning in the same AI platform is what sets the most advanced vendors apart in this market.
Top vendors in this field include Experian, Ikata, Kount, LexisNexis Risk Solutions, Telesign, and others.
To combat synthetic identity fraud, financial institutions and artificial intelligence services and solutions can employ the following measures:
1. Strengthen Identity Verification:
Implement more robust identity verification processes that go beyond basic personal information, such as biometric authentication, multi-factor authentication, and document verification.
2. Analyze Behavioral Patterns
Monitor and analyze transactional behavior, spending patterns, and credit history to identify inconsistencies or suspicious activities associated with synthetic identities.
3. Collaboration and Data Sharing
Enhance information sharing among financial institutions, credit bureaus, and law enforcement agencies to detect patterns of synthetic identity fraud and identify potential fraudsters.
4. Advanced Analytics and AI
Leverage advanced analytics and artificial intelligence technologies to detect anomalies and patterns that indicate synthetic identity fraud. By analyzing large amounts of data, machine learning algorithms can detect suspicious behaviors and enhance fraud detection.
5. Regularly Review and Update Fraud Prevention Strategies
Stay updated with the latest fraud techniques and adopt proactive measures to strengthen fraud prevention strategies. Regularly reviewing and improving fraud detection systems can help stay ahead of emerging threats.
Overall, combating synthetic identity fraud requires a multi-layered approach that combines strong identity verification, advanced analytics, collaboration, and ongoing vigilance to protect individuals and financial institutions from this evolving form of fraud.
The Importance Of AML Solutions In Combating Synthetic Identity Theft
Synthetic identity theft is a growing problem that can be difficult to detect and prevent. The act of fraud involves the fabrication of an identity using a mixture of genuine and falsified information. It is often used to open fraudulent accounts or obtain credit in the name of the fake identity.
AML solutions can help combat synthetic identity theft by providing advanced analytics and monitoring capabilities that can detect suspicious activity and identify potential fraudsters. These solutions can also help financial institutions comply with regulatory requirements and reduce their risk of financial losses. By implementing AML solutions, financial institutions can better protect their customers and their business from the damaging effects of synthetic identity theft.
Traditional fraud and compliance solutions operate reactively, only responding after a crime has occurred. However, to effectively combat synthetic ID fraud, proactive tools are necessary without compromising the customer experience. Due to the similarity in behavior between synthetic and legitimate accounts, fraud detection software with inadequate KYC components may not detect any suspicious activity.
Therefore, it is crucial for artificial intelligence software development company
to prioritize the implementation of advanced customer screening and transaction monitoring solutions that incorporate artificial intelligence to detect and track changes in customer behavior in real-time.
The industry needs a clear, cohesive direction to combat the threat of synthetic identity fraud. To increase prevention and detection rates, collaboration among the fraud landscape is essential. This involves tracking trends and sharing data. Awareness of this issue is growing.
Final Thoughts
The issue of synthetic identity fraud remains unsolved and is expected to worsen. To address this, proactive measures must be taken until government agencies improve their ability to catch these criminals. In the future, artificial intelligence may aid in detecting synthetic identities. The adoption of blockchain technology by more individuals will help reduce the prevalence of synthetic identities. Stricter regulation surrounding the creation and use of these identities will make it more challenging for criminals to succeed.
