Synthetic fraud to Impact the Industry

In an era defined by digital connectivity and technological advancements, the realm of cyberspace has always become a challenge. As the world increasingly relies on digital platforms for communication, commerce, and information sharing, the specter of cybercrime has risen in tandem, casting a shadow on the promise of the digital age.

Synthetic identity fraud is a growing threat in the US. Traditional methods of fraud detection are falling short and failing to catch it. These types of Fraud are catching like fire and becoming the fastest growing financial crime.

All credits goes to the emerging technologies like AI, ML, combining with big data analytics and high-performance computing applications that can process larger volumes of data from various sources and data sets i.e. Structured, Unstructured and Semi-structured. AI/ML technology can achieve higher scalability by processing large scale data types containing media data, image data and object data to spot trends and patterns across disparate data sets.

Synthetic frauds fueled by “Frankenstein Identities” is the hardest to detect and quickly accounting for the highest percentage of fraud losses, primarily involving credit cards and unsecured lending portfolios.

The criminals combine fake and real information, such as Social Security Numbers and names, to create a new identity. It allows the criminal to steal money from creditors including credit card companies who extend credit based on the fake identity. These types of frauds are quite different from traditional identity theft.

Large pay-outs and the ability to go undetected for so long are some of the reasons synthetic identity fraud is so attractive to fraudsters and crime rings. It’s expert-level fraud is carried out by some of the most sophisticated identity thieves.

Secondly, Synthetic identity fraud could trigger need for more sophisticated biometric security systems. Fraudsters are creating false written or audio messages to bypass various security measures and access banking or account information.

Moving on, the Financial institutions can predict and capture “ Synthetic Fraud” Scammers early in the process by applying accelerated deep learning and statistical machine learning technologies.

Dr. Deepak Kumar Sahu, President & CEO, VARINDIA