2018-人工智能对（再）保险业的影响（英文版）-9mb

Summary of "The Impact of Artificial Intelligence on the (Re)Insurance Sector"

Core Content

This document explores the transformative impact of Artificial Intelligence (AI) on the (re)insurance industry, focusing on both the challenges and opportunities it presents. It is based on insights from various industry leaders and experts, including Denis Kessler, Chairman & CEO of SCOR, Nicolas Miallhe, Co-founder and President of The Future Society at Harvard Kennedy School, Jennifer Coleman, Senior Risk Manager at SCOR, and Laurent Alexandre, CEO of DNA Vision.

The document outlines how AI, driven by big data, cloud computing, and machine learning, is reshaping the insurance landscape. It emphasizes that while AI offers significant potential in terms of efficiency, risk modeling, and customer experience, it also introduces new risks that must be managed.

Main Points

1. AI's Impact on the Insurance Industry

• AI is fundamentally changing how risks are assessed, managed, and insured.
• It enables ex-ante predictability and ex-post monitoring, leading to a shift in how risks are observed, carried, and settled.
• This change affects both the supply and demand sides of the insurance market.

2. Threefold Impact of AI

• Rethinking the basics of insurance: AI can reduce information asymmetry by providing comprehensive and real-time data.
• Redefining distribution and product innovation: AI supports personalized customer experiences, digital financial advice, and enhanced product development.
• Transforming the risk universe: AI improves fraud detection and risk modeling but also introduces new types of risk, such as cyber-risk and algorithmic errors.

3. Key Applications of AI in (Re)Insurance

• Underwriting: Automated and augmented underwriting processes can improve efficiency and accuracy.
• Claims Processing: Robo-claims analyzers and adjusters can automate analysis, settlement, and fraud detection.
• Risk Management: AI enhances the ability to identify and model emerging risks, and to monitor and respond to them in real time.

4. Challenges and Risks

• AI introduces new intrinsic risks, such as errors in algorithmic decision-making and cyber-attacks targeting AI systems.
• There is a need to understand and manage the ethical and regulatory implications of AI in insurance.
• The black box nature of AI systems requires transparency and training for professionals to understand and work with AI effectively.

5. The Role of AI in the Future of Insurance

• AI is not a replacement for human judgment, innovation, and accountability, but a tool to enhance these aspects.
• The insurance industry must adapt to the digital revolution and integrate AI into its processes and business models.
• The human touch remains essential, as AI cannot fully replicate the nuanced, intuitive, and relational aspects of insurance.

Key Information

AI's Technological Foundations

• AI is at the intersection of big data, cloud computing, and machine learning.
• Deep learning is a critical component, using complex statistical models and multiple layers of processing to emulate human cognitive functions.
• The Turing test is a benchmark for evaluating AI's ability to mimic human behavior.

AI's Impact on Risk Management

• AI can improve risk profiling, fraud detection, and underwriting accuracy.
• It allows for real-time monitoring of risks, which is a significant shift from traditional static risk assessment methods.
• AI introduces new cyber-risks, both unintentional (e.g., bugs) and intentional (e.g., attacks), which must be addressed.

Strategic Implications for (Re)Insurers

• (Re)insurers must embrace AI and invest in it to stay competitive.
• A "think big, start small" approach is recommended for gradual integration.
• Collaboration between AI systems and human professionals is crucial for future success.
• Industry-wide projects and shared standards are necessary to ensure interoperability and avoid fragmentation.

The Human Element

• AI does not replace humans, but complements them.
• The combination of analytical and artistic skills is vital in reinsurance.
• Judgment, creativity, and accountability remain uniquely human attributes.

Conclusion

AI is set to become a cornerstone of the (re)insurance industry, enabling greater efficiency, better risk modeling, and enhanced customer experiences. However, its integration requires careful management of new risks, ethical considerations, and a shift in professional skill sets. The industry must move from fear to investment, and from resistance to collaboration, to fully harness the potential of AI.

The document concludes that while AI may lead to a winner-takes-all market dynamic, the human element in insurance will remain irreplaceable, especially in areas requiring judgment, creativity, and trust-building. The future of (re)insurance lies in the synergy between AI and human expertise.