The agenda for the 2020 Chief Data Officer Exchange for Financial Services is still being finalised. You can request your copy of the 2020 agenda for when it is released by contacting us on firstname.lastname@example.org or by calling +44 (0) 207 368 9484. Alternatively, please fill out the form below to read the 2019 agenda to see the type of sessions in store for 2020.
Ahead of the Chief Data Officer Exchange for Financial Services, we asked one of our trusted solution providers, Stibo Systems to walk us through why they choose to return to the Exchange year upon year. They provide us with a high-level overview of their business and proceeded to walk us through the 4 stages that took place prior to the CDO FS Exchange: The Challenge, The Process, The Result, and The Conclusion. This explains the value they derived from the Exchange and therefore why they chose to come back.
Ahead of the CDO Exchange FS we surveyed Data leaders from leading Financial Services organisations to discover their greatest challenges and where their investment priorities lie for the near future.
Dun & Bradstreet commissioned a survey of business leaders in the UK and the US to understand how their data management strategies have evolved in the last decade, the challenges they still encounter, and their plans to transform by 2030.
Learn how Unum successfully matched and appended their data to identify cross-sell opportunities and achieve a broader view of their overall market.
Enterprise-class organisations across all industries are looking to embrace artificial intelligence (AI). They are beginning to recognise the game-changing and transformative benefits they can attain with AI—and they need to arm their data science teams with the tools and data to drive innovation and business value with machine learning (ML) and deep learning (DL). Data science teams want to leverage their preferred frameworks (TensorFlow, PyTorch, Theano, Caffe2, etc.); learning algorithms (decision trees, Naive Bayes, random forest, XGBoost, etc.); and applications and tools (Jupyter notebooks, RStudio Server, AutoML, H2O.ai, Dataiku, etc.) to develop their models—from data selection and training, to model deployment.
Download the Big Data Challeges & Opportunities for Insurance, Retail and Investment Banking eBook ahead of the Chief Data Officer Exchange, Financial Services.