Generative AI in Risk and Compliance Webinar

Seize the AI advantage! The AI skills you will need to succeed in Risk & Compliance.

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Adrian Resag

Academic Director

Adrian Resag, Academic Director at OCEG, specializes in GRC, AI governance, and ISO standards. With a background in leading international teams, he has been teaching, authoring certifications, and advancing professional skills in audit, compliance, and ethics since 2005.

Key Learnings

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Real-time monitoring allows continuous tracking and verification of data, such as monitoring stock prices at frequent intervals. This process supports faster decision-making, identifies anomalies promptly, and ensures operational efficiency in dynamic environments such as finance and compliance. It highlights the role of automation in reducing manual effort while maintaining accuracy and timeliness in monitoring tasks. Advanced analytics-based organizations have a better competence in responding to the dynamics of the market. It enables the company's strategy to shift proactively due to trends and predictions, ensuring the firm is ahead of every changing environment. This includes emerging industry trends, changing consumers' preferences, or even some disturbing changes.

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AI data analytics spans four types i.e. descriptive, diagnostic, predictive, and prescriptive. Each offers unique insights, from summarizing data trends and identifying past issues to forecasting future scenarios and suggesting actionable strategies. Prescriptive analytics is the next level of data-driven decision-making, providing clear and actionable recommendations. Rather than simply predicting future outcomes, prescriptive analytics translate predictions into actionable steps that organizations can take to improve performance and efficiency. It simplifies decision-making and removes guesswork, keeping it focused on strategies with measurable results.

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