Although the current focus of the system is on detecting credit card transaction fraud, Nvidia has indicated that it can be adapted for various other types of financial crimes, such as new account fraud and money laundering. This flexibility may attract financial institutions that are considering the integration of their fraud detection systems.
The platform facilitates a shift for financial organizations from traditional computing frameworks to enhanced computing with the Nvidia AI Enterprise software platform and Nvidia GPU instances—specialized processors built for handling parallel processing tasks.
“As artificial intelligence models become larger, more complex, and diverse, it’s crucial for businesses across various sectors, including financial services, to tap into computing solutions that are both cost-effective and energy-efficient,” states Patangia.
“Standard data science workflows often lack the necessary computational acceleration to manage the substantial amounts of data needed to effectively combat fraud, especially as losses in the industry continue to grow,” he notes. “Utilizing the RAPIDS Accelerator for Apache Spark could enable payment companies to decrease data processing times and trim their processing expenses.”
Don’t forget to check out the latest issue of FinTech Magazine and register for our global conference series – FinTech LIVE 2024
FinTech Magazine is part of the BizClik family.