model development - Events - Global Risk Community2024-03-29T08:28:42Zhttps://globalriskcommunity.com/events/feed/tag/model+development2nd Annual Development, Implementation and Management of ML Modelshttps://globalriskcommunity.com/events/2nd-annual-development-implementation-and-management-of-ml-models2024-04-22T04:00:00.000Z2024-04-22T04:00:00.000ZRia Kiayiahttps://globalriskcommunity.com/members/RiaKiayia<p><a href="https://globalriskcommunity.com/events/list/on/2024-04-22">Apr 22, 2024</a> to <a href="https://globalriskcommunity.com/events/list/on/2024-04-24">Apr 24, 2024</a></p><p>Location: New York, NY</p><p>Created by: <a href='/members/RiaKiayia'>Ria Kiayia</a></p><div><img src="https://storage.ning.com/topology/rest/1.0/file/get/12367254258?profile=RESIZE_400x&width=400"></div><div><p><em>Adjust your development and management of ML models practices to mitigate emerging risks, ensure regulatory compliance and stay competitive in the era of generative AI</em></p><p>The GFMI <a href="https://www.marcusevans.com/conferences/mlmodeldevelopment?utm_source=media+partner&utm_medium=grc+event+listing&utm_campaign=cmu342+-+grc&utm_id=cmu342">2<sup>nd</sup> Annual Development, Implementation and Management of ML Models</a> conference taking place on April 22-24, 2024 in New York, will showcase best practices for developing and managing Machine Learning (ML) models to maximize business value. The event will present best use cases of Natural Language Processing (NLP) and technologies that harness the potential of ChatGPT and generative AI. It will also assess the lessons learned by financial institutions that have successfully implemented these technologies, achieving a high ROI.</p><p><strong>Attending This Premier marcus evans Conference Will Enable You to:</strong></p><ul><li><strong>Harness</strong> the potential of ChatGPT to maximize business value.</li><li><strong>Assess</strong> the best use cases of NLP technologies to extract valuable insights from unstructured financial data.</li><li><strong>Gain</strong> the update from the Regulators to ensure compliance of ML Model development, implementation and management practice.</li><li><strong>Combine</strong> traditional and alternative data sets for the best business decisions.</li><li><strong>Address</strong> data bias and fairness challenges in ML Models through proactive approaches.</li><li><strong>Advance</strong> current model risk frameworks to accommodate ML models and minimize their risk.</li></ul><p><strong>Best Practices and Case Studies from:</strong></p><ul><li><strong>Wayne B. Shoumaker</strong>, SVP, Quantitative Analytics Manager, Model Risk Management, <strong>Wells Fargo</strong></li><li><strong>Hua Julia Li</strong>, Senior Vice President, Global Head of Model Risk Management,<strong> State Street</strong></li><li><strong>Harikrishna Mallepalli</strong>, Senior Vice President, <strong>Citi</strong></li><li><strong>Xiaoling (Sean) Yu</strong>, Head of Financial Crimes Modeling & Analytics,<strong> KeyBank</strong></li><li><strong>Imir Arifi</strong>, Head of Methodologies & Models in the Americas, <strong>UBS</strong></li><li><strong>Carlos Rodriguez</strong>, Director - Model Validation, AI & ML,<strong> Ally</strong></li></ul><p>For more information please contact Ria Kiayia, Digital Media and PR Marketing Executive at <u><a href="mailto:riak@global-fmi.com">riak@global-fmi.com</a></u> or visit the event website: <a href="https://bit.ly/3Q7AvwV">https://bit.ly/3Q7AvwV</a></p></div>