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New NVIDIA AI workflow detects fraudulent credit card transactions

Global financial losses due to credit card transaction fraud will reach $43 billion by 2026 viewIt works.

To solve this problem, NVIDIA’s new AI workflow running on Amazon Web Services (AWS) uses accelerated data processing and advanced algorithms to significantly improve AI performance for detecting and preventing credit card transaction fraud.

recent Money20/20 Launched at a fintech conference Workflowhelps financial institutions analyze user behavior to identify subtle patterns and anomalies in transaction data, improving accuracy and reducing false positives over traditional methods.

Users NVIDIA AI Enterprise Accelerate and streamline your fraud detection workflow by leveraging our software platform and NVIDIA GPU instances.

Overall, companies that have adopted machine learning tools and strategies Up to 40% improvement in fraud detection accuracyThis allows you to identify fraudsters more quickly and minimize damage.

Major financial institutions, such as American Express and Capital One, have established their own AI-based solutionis developing.

NVIDIA’s new workflow accelerates data processing, model training, and inference, all integrated into one easy-to-use software.

In particular, this workflow can be adapted to apply to a variety of use cases, such as new account fraud, account takeover, and money laundering, as well as credit card transaction fraud.

Accelerated Fraud Detection Computing

As AI models become increasingly complex and diverse, energy-efficient and cost-effective computing technologies are becoming increasingly important to many industries, including financial services.

Existing data science pipelines are ill-equipped to handle the massive amounts of data needed to combat the rapidly increasing number of fraud losses. Now the payment company NVIDIA RAPIDS Accelerator for Apache SparkYou can shorten data processing time and reduce costs.

To efficiently manage large datasets and run complex AI models in real time, financial institutions rely on NVIDIA’s AI and accelerated computing We are actively introducing the platform.

Libraries like XGBoost, which have been widely used for fraud detection for a long time, are based on gradient boosted decision trees, a type of machine learning algorithm.

NVIDIA’s new AI workflow is graph neural network(GNN) Using embedding as an additional feature NVIDIA RAPIDS We further enhance XGBoost using a suite of AI libraries, which reduces false positives.

GNN embeddings are input to XGBoost to create and train a model, and then NVIDIA Morpheus Runtime Core library and NVIDIA Triton Inference ServerOrchestrated to perform real-time inference tasks.

NVIDIA Morpheus The framework securely scans and classifies all incoming data, tagging it with patterns and flagging potentially suspicious activity. NVIDIA Triton Inference Server simplifies inference for deploying any type of AI model in production while optimizing throughput, latency, and utilization.

NVIDIA Morpheus, RAPIDS, and Triton inference servers are available on NVIDIA AI Enterprise.

Introducing AI Leading financial services company

Major financial institutions in North AmericaThey are actively using AI technology to combat the increasing damage from online and mobile fraud.

American Express has been using AI-based fraud detection technology since 2010 to monitor every customer transaction in real time, determining fraud within milliseconds. The company is leveraging the NVIDIA AI platform to increase detection accuracy.

Europe’s digital bank bunqgenerative AI and large language modelcombine to enhance fraud and money laundering detection, and model training speeds are improved by more than 100x thanks to NVIDIA’s accelerated computing.

BNYIn March, the bank’s first DGX H100 Systemclass NVIDIA DGX SuperPODintroduced a solution optimized for fraud detection and other use cases.

System integrators and cloud service providers are also integrating NVIDIA AI workflows to enhance the security of financial services apps and protect customers’ assets and identities.

Fraud Detection NVIDIA AI WorkflowTake a look at fraud detection with GNNenforcedoing Read this NVIDIA technology blog on how.

At Money 20/20 in Las VegasNVIDIA AI Pavilion with AWSsecond by visiting AI for Fraud DetectiontoLearn more about .

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