Speaker

Michelle Gervais

Michelle Gervais

Head of Data Science, Standard Bank Group

Michelle is currently serving as Head of Data Science for Standard Bank Group. Her role involves delivering data products across the Bank, standard-setting for data science (machine learning and artificial intelligence) initiatives, and management of the Data Science Centre of Excellence. Michelle also chairs the Standard Bank Data Science Guild, which pulls together practitioners across the organisation to facilitate model governance and knowledge sharing. As part of the founding team for TYME Capital, Michelle served as Head of Product and Data Monetisation, assisting the fintech start-up in building data-driven mobile banking solutions across Africa. Having recently been granted a banking license, TYME is now successfully launching a stand-alone bank in South Africa. During her tenure at Deloitte Consulting, Michelle founded the Customer Insights practice area in South Africa, which combined the Strategy and Analytics divisions to advise clients on driving customer experience and developing new products using operational data.

Michelle Gervais will be speaking on the following topic:

10:50
Case study: Banking Productionising Machine Learning: Standards that future-proof your organisation

Despite today's interest in data science solutions, Gartner's 2018 CIO survey revealed that only 4% of companies have deployed AI solutions within their organisations. With so many companies investing in AI, why is the actual implementation rate so low? How can you ensure that your team is one of the 4%?

In this presentation, we will unpack:

  • Why leaving models in SIT is a bad idea…but why so many companies do
  • Steps to achieving the productionisation ideal
  • The importance of platform health to your productionised models
  • What good governance looks like—including a triage checklist to solving your worst governance gaps
  • Lessons learnt from mobilising the data science practice across Africa's largest bank

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