Rapidly deploy data into value-at-risk models to keep up with emerging risks and threats.
Enable rapid conversion from external source systems and achieve a fully configurable and industrialized conversion capability.
Bring a more transparent approach to model risk management through automated documentation and integrated data visualization.
Combine financial services industry data models with the cloud to enable high governance standards with low development overhead.
Take a quantitative view into sustainability and ensure companies are accountable for their actions.
Adopt a more agile approach to risk management by unifying data and AI in the Lakehouse.
Use geospatial data to better understand customer spending behaviors in terms of both who they are and how they bank.
Automate transaction enrichment to better understand your customers’ behaviors and drive hyper-personalization.
Modernize fraud-prevention strategies to reduce operational costs and increase customer trust.