How Deutsche Bank industrialized AI and machine learning
Deutsche Bank is one of the world’s largest financial institutions, with operations in 58 countries. It’s a universal bank with a rich heritage and operations across private and commercial banking, corporate and investment banking (CIB), and asset management (DWS).
As an early adopter of data science, machine learning, and AI, the group-wide analytics function is trailblazing new ways to drive revenues, lower costs, and reduce risk across all areas of the group. John Allen shares how his team combines commercial offerings from vendors such as Cloudera and Red Hat with open source technologies such as Python and Kafka to revolutionize legacy processes and transform the way the bank uses technology to drive innovation. Discover how they have industrialized data science and advanced analytics across the group, embracing both experts and “citizen data scientists,” and helped Deutsche Bank become a leading data technology pioneer.
John Allen is the head of group-wide data analytics function at Deutsche Bank, supporting both business and infrastructure teams. The function uses data science and advanced big data analytics technology across a variety of use cases including revenue generation, cost avoidance, and risk reduction. John is responsible for a range of services for the business including analytics strategy, research and development, shared big data technology platforms, and agile, customer centric, project delivery.
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