Webinar: Enhance financial services applications with machine learning

Financial services organizations are looking to find new ways to leverage their data to make better decisions and get a step ahead of the competition. Active analytics offer banks, insurers, asset managers, and others the ability to dynamically analyze data at scale and augment human insight with powerful predictive models and machine learning. In this webinar we’ll explore how Kinetica and RAPIDS, NVIDIA’s GPU-accelerated data science libraries, enable financial services organizations to more accurately model, value and manage assets, at scale, to gain an edge and increase profits.


  • How Kinetica abstracts away the complexity of combining analytics and machine learning in a single platform
  • Kinetica’s ability to analyze a variety of fast moving, complex financial data sources to deliver real-time answers
  • An example of a mortgage analysis application leveraging RAPIDS trained models and Kinetica
Major financial institutions like Citibank rely on Kinetica to power mission critical applications.



Saif Ahmed – Product Owner-Machine Learning, Kinetica

saif-ahmedSaif is an accomplished quantitative developer, machine learning practitioner, and senior executive with two decades of experience in management consulting, quantitative hedge funds, and AI software startups. He has held a number of senior roles and serviced clients across the US, Europe, the Middle East and Asia. Saif is currently applying his experience at Kinetica, leading ML Product Engineering efforts for a next-generation Machine Learning product line with database adjacency.