Why you should not miss this Executive Briefing

This course equips insurance executives with a comprehensive understanding of how generative AI can transform the industry. Participants will gain foundational knowledge of generative AI, explore its applications, and learn strategies for implementing large language models (LLMs). By the end of the course, participants will be prepared to leverage generative AI in key areas such as underwriting, claims processing, fraud detection, and customer engagement.

Key outcomes of the Executive Briefing:

• Strategic Understanding of AI in Insurance: Acquire a clear overview of how generative AI transforms key functions like underwriting, claims processing, fraud detection, and customer engagement
• Informed Decision-Making: Learn to evaluate AI opportunities, prioritize use cases, and integrate AI solutions effectively while addressing ethical and regulatory considerations
• Actionable Case Study Insights: Draw inspiration from real-world examples to envision and execute impactful AI implementations tailored to your own organizations

Agenda:

1. Introduction to Generative AI (key concepts, difference with traditional AI models)

2. Applications of Generative AI in Insurance

     • Fraud Detection: Identifies fraudulent patterns in claims data and highlights anomalies.

     • Case Study: An insurance app in China uses AI to flag suspicious claims and improve efficiency.

     • Underwriting: Analyzes vast datasets to enhance risk assessment and decision-making.

     • Case Study: A U.S. insurer leverages AI to reduce processing time and improve accuracy.

     • Customer Service: AI-driven chatbots provide real-time assistance for policy inquiries and claims filing.

     • Case Study: In China, AI-powered bots handle claims and offer instant responses.

3. Risk Management and Predictive Analytics

     • Predictive Analytics: Forecasts potential risks using customer data and market trends.

     • Case Study: A German insurer uses AI for risk modeling, enabling better decision-making.

     • Claims Processing: Automates claims handling, reducing manual effort.

     • Case Study: A French insurer employs AI for claims automation and fraud detection.

     • Stress Testing: Simulates various scenarios to test the resilience of insurance portfolios.

4. Implementing Generative AI in Insurance

     • Defining an operational model.

     • Infrastructure requirements for deploying AI.

     • Risk management strategies for AI implementation.

     • Case Study: In Singapore, insurers successfully implement AI for underwriting and claims automation.

5. Ethical Considerations and Future Trends

     • Addressing ethical concerns: bias, fairness, and transparency.

     • Future trends in AI and their impact on the insurance industry.

     • Case Study: In Italy, AI is used for personalized policies while maintaining ethical transparency.

6. Conclusion and Next Steps

Bonus: All participants will receive an official Participation Certificate from Qorus, adding value to their professional credentials.

Target Audience:

C-level executives and senior-level managers in the insurance sector. This course is designed to provide strategic insights and operational guidance on implementing generative AI for enhanced efficiency and decision-making.

Platform:

Microsoft Teams

Pricing:

Qorus members: €750 per participant
Non-members: €1125 per participant
(Briefing reserved for Financial Institutions)

Note: A special discount of 25% is applied in case of registration before 31 January 2025

For registration or more information, please send an email to: 
olga@qorusglobal.com