Fraud prevention is a crucial aspect in many industries, from banking and finance to e-commerce and insurance. With the ever-evolving techniques of fraudsters, it has become imperative for organizations to constantly update their fraud detection models. Preventing fraud in real time has been, until now, an unreachable goal. The legacy approach uses stale data and too many cutoffs, resulting in less than ideal results.

Hopsworks will demonstrate a machine learning driven approach and an end-to-end solution that provides accurate real-time results at extreme scale and that incorporates graph features, pipeline management, alerting & workflow, and visualization.

Utilizing Hopsworks' feature store and vector database, alongside its support for scalable model training on GPUs and scale-out model serving with KServe, organizations can build and deploy cutting-edge fraud detection and prevention models. In addition, Hopsworks addresses the challenge of slow model saving and loading by utilizing HopsFS, which enables high-speed access to large volumes of data stored in object storage to help companies evolve their models to get ahead of fraud and stop it at the door.

Join us as we walk through the entire life cycle of building and deploying fraud detection models using Hopsworks and open-source foundation models. With its robust capabilities, Hopsworks offers a seamless and efficient platform for organizations to combat fraud and safeguard their operations. So join us and learn how Hopsworks can help your organization stay ahead of fraudsters in the constantly evolving landscape of fraud detection and prevention.