Table Discussions - Your time, your topic

Date:

Wednesday, June 16, 2021

Time:

2:00 pm

Summary:

Choose the topic that is relevant to you. In this session we offer focused topics to dig in deeper into specific content segments. So this is the perfect opportunity to share your story, your specific question and get first hand advice from your peers and experts.  All attendees can participate in the roundtable of their choice and it’s a camera on event.

Other Roundtable Topics will be announced soon

Analytics & AI Governance (Frank Poerschmann)

Discussion between experts on the rising demand for actively managing and governing AI & Analytics activities, as i.e. managing model portfolios, continuous evaluation of the value of analytics solutions and their adaption, how to scale limited resources and manage the interface between business, data science, data management and IT. Participants shall exchange personal learnings and questions around frameworks, best practices as well as personal experiences on challenges and solutions.

Machine learning and transparency: Why and How? (Tom Alby)

With more and more advanced algorithms entering the data labs of the finance industry, some stakeholders feel uncomfortable with the lack of transparency that some algorithms offer. Regulatory authorities may even demand that the internals of a model are disclosed, e.g. to understand whether risks such as discrimination exists. In this table discussion, we want to discuss experiences and approaches to this challenge.

Driving a Data-Driven Mindset Across the Enterprise (Nora Reich)

Advanced analytics solutions imply significant value for a company but also high complexity. Crucial success factors are corporate values and norms that include a comprehensive understanding for the contribution of data-driven work for sustainable company development. However, we often see intuitive instead of data-driven decision marking, lack of understanding for data potentials, spotlight on near-term solutions, etc. Let’s talk about how we can enhance data literacy and understanding.

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