Webinars and Events

The speed with which Generative AI is being embraced and rushed into production by enterprises is head-spinning, and the end of the calendar year was ripe with headlines of “AI Gone Wrong”. This means the time to safeguard AI was yesterday. Join ModelOp’s VP of Product, Dave Trier, for a live webinar in which he’ll discuss three real world situations that stress the urgency for Enterprise AI governance from enterprise AI gone wrong. Dave will analyze current events in which enterprises failed to balance AI risk and reward and share AI Governance insights that he’s collected from conversations with over one hundred Fortune 500 executives over the past year.

This event, convening a community of AI, governance, risk, compliance, data, and security leaders from Fortune 500 companies and leading universities, will explore trends, strategies, and best practices on how to approach and implement AI Governance while navigating the challenges and opportunities related to generative AI

With the massive publicity of the recently launched ChatGPT, Artificial Intelligence (AI) has been elevated to Board-level initiatives. While AI offers tremendous potential, it can also introduce significant business risks if not used and governed properly. Watch this impactful webinar where Liming Brotcke (Senior Director of Data Science at Ally Bank) and Dave Trier (VP of Product for ModelOp) give practical advice on how to get started in implementing a modern model governance framework in the Age of AI.

Digital disruption is part of your workflow now and adapting your approach to handling model risk in light of the speed this brings is imperative. In this panel discussion, Banking industry insiders share their strategies for managing this, and still maintaining control and quality.

The growth in AI adoption is accompanied with a parallel growth in regulations targeted at minimizing the risk inherent in AI. Many financial institutions have risk management processes and teams; however, the processes are typically manual and require highly trained model validators, which are in short supply. Because of this, Model Risk teams are unable to keep pace with the growing number of new models, in conjunction with the substantial backlog of existing model validations, re-validations, and annual reviews. This presentation provides real life experiences about how to solve this growing pain.

Presented by ModelOp CTO Jim Olsen Scaling AI for an enterprise means more than more data, more compute, bigger speeds and feeds. Enterprise Architects need to accommodate multiple DSML tools, data systems and serving environments. In addition to the migration to cloud or multi-cloud, the dockerization journey, the increasing use of 3rd party AI models and 4th party AI. How do you implement enterprise standards for Operations and Governance, without stifling innovation and adding complexity?