Financial crime model tuning is evolving beyond traditional rule and threshold adjustments as organizations explore automation, advanced analytics, machine learning, and AI.
In this webinar, presenters will explore how these technologies require enhancement to established tuning practices, support rule-based and data-driven detection systems, and inform approaches to model testing and monitoring. They also will address data quality, explainability, validation, governance, and human oversight considerations associated with machine-learning and AI-driven systems.
After attending this session, you should be able to:
Prerequisites: None
Program level: Overview
Advance preparation: None
Delivery method: Webinar (group internet based)
Field of study: Information technology
This session is recommended for 1.0 hour of CPE credit.
Note: All participants MUST be logged into the webinar INDIVIDUALLY to receive CPE credit. CPE credit will only be granted in the name of the individual logged into the LIVE presentation. Crowe is unable to grant CPE credit for groups viewing the webinar or for viewing on-demand recordings of the webinar.
There is no registration fee for participating in this webinar; therefore, there is no cancellation fee.
AI risk and governance leaders, anti-money laundering officers, board members, Bank Secrecy Act officers, chief audit executives, chief compliance officers, chief risk officers, compliance executives, general counsel, internal audit directors, internal audit professionals, risk executives, financial intelligence unit managers, financial intelligence unit analysts, and model risk managers
For additional information, please contact Jon Losey.