BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//hacksw/handcal//NONSGML v1.0//EN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260413T181704Z
DESCRIPTION:Click for Latest Location Information: http://dgiq2024east.data
 versity.net/sessionPop.cfm?confid=162&proposalid=15523\nFINRA plays a criti
 cal role in ensuring the integrity of the financial markets through writing
  and enforcing rules and by examining firms for compliance with those rules
 . This is done to provide investors protection and to promote confiden
 ce in the US markets.  \n\nWith rapid increase in AI adoption, Model G
 overnance becomes a challenge. Data scientists spend a significant amount o
 f time wrangling data, getting Machine learning models into production and 
 monitoring and troubleshooting them. By adopting actionable monitoring with
  automated Governance workflows, we achieve model operations resiliency hav
 ing model governance compliance at scale.\n\nWe built and operationalized F
 INRA’s Model life cycle workflows to automatically monitor model perf
 ormance, governance compliance, and operational processes. These governance
  workflows are orchestrated to have process controls in place, including re
 mediation through notifications and automated alerts, regardless of th
 e type of model or where it is deployed. This results in reliable, com
 pliant, and scalable models. This approach has led to operational resilienc
 y (ensuring business, risk and regulatory controls are adhered to) and full
  auditability of models to mitigate risk of models in production. \n\n
 During this presentation, we will cover the following topics:\n\n
 Who is FINRA?\n	What is ML Model Governance?\n	\n
 Key Pillars in Governance\n		Orchestration of Governance\n
 Risk Management\n	\n	\n
 Scaling and Operationalizing Model Governance Automation\n	\n
 End-to-end Model Governance\n		Governance Process Enforcement\n
 Production Governance Controls\n	\n	\n	Observability and Monitoring\n	\n
 Model Monitoring\n		\n
 Operations, Risk, Quality, and Process monitoring.\n		\n		\n
 \n	\n	Operational Reliability for Model Governance:\n	\n
  Actionable and Outcome-Driven Insights, Continuous Improvem
 ent, Data-Driven Decisions,  Promoting Automation and E
 nhanced Resiliency\n	\n	\n\n
DTSTART:20241211T120000
SUMMARY:Jumpstart Model Governance at Scale to Have Full Value of Enterpris
 e ML Investments
DTEND:20241211T124459
LOCATION: See Description
END:VEVENT
END:VCALENDAR