AI and the Evolution of Financial Crime Model Tuning
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 recording, presenters 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 address data quality, explainability, validation, governance, and human oversight considerations associated with machine-learning and AI-driven systems.
After watching this webinar recording, you should be able to:
- Differentiate among traditional rule-based tuning, automation-assisted tuning, machine-learning enhancements, and AI-driven financial crime model tuning
- Identify practical opportunities to use AI, advanced analytics, and automation to improve threshold setting, segmentation, testing, performance analysis, and monitoring
- Evaluate the data quality, explainability, validation, governance, and human-oversight considerations associated with tuning machine-learning and AI-driven systems
Note: Only attendees of the live webinar are eligible for CPE or CLE credit for qualifying webinars. If you view the webinar recording on this page you may not be eligible for CPE or CLE. For questions about CPE, contact [email protected].
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