Financial services firms are under pressure to transform. As data volumes grow across their organizations, some firms are turning to real-time and predictive analytics projects that can address the customer experience, regulatory compliance and risk management, and cybersecurity and fraud detection. Yet many companies find themselves with disparate, siloed data volumes that aren’t easily migrated or integrated, and a number of organizational, technical and financial barriers to operationalizing AI & ML. During this presentation, we will share how many financial services firms have accelerated their journey towards becoming data driven by leveraging a distributed unified analytics platform and in-database ML to give analysts and data scientists access to all of their data, and reduce the effort and time required to successfully deploy AI & ML models in production.