保险业2030_人工智能对未来保险业的影响（英文版）_10页_950kb

Insurance 2030 – The Impact of AI on the Future of Insurance

Core Content

This document outlines the transformative impact of artificial intelligence (AI) and related technologies on the insurance industry by 2030. It highlights the shift from traditional models to more data-driven, automated, and personalized approaches across all aspects of the industry, including distribution, underwriting, pricing, and claims processing. The report also provides guidance on how insurance carriers can prepare for these changes.

Main Viewpoints

1. AI and Machine Learning (ML)

• AI enables machines to mimic human cognitive functions like learning, perception, problem solving, and reasoning.
• ML is a key approach to achieving AI, using data to make predictions and decisions.
• Deep learning (DL), a subset of ML, allows algorithms to model high-level data abstractions and is crucial for processing complex data streams.

2. Data Explosion from Connected Devices

• The number of connected devices is expected to reach one trillion by 2025, creating vast amounts of data.
• This data will allow carriers to better understand client behavior, leading to more personalized products, real-time pricing, and tailored insurance solutions.
• Examples include wearable devices for health data, IoT in homes for safety monitoring, and telematics for auto insurance.

3. Advances in Cognitive Technologies

• Deep learning technologies, such as convolutional neural networks, will evolve to handle diverse applications.
• These technologies will be used to process large and complex data streams from active insurance products tied to individual behavior.
• They will enable real-time risk assessment and dynamic product offerings.

4. The State of Insurance in 2030

• AI will significantly impact all parts of the insurance value chain, including distribution, underwriting, pricing, and claims.
• Distribution will become faster, with AI-generated risk profiles allowing for near-instant policy purchases.
• Underwriting and Pricing will be largely automated, with AI models analyzing internal and external data to provide real-time, personalized pricing.
• Claims will be processed more efficiently, with automation and IoT reducing processing times and increasing accuracy. Human involvement will focus on complex or unusual claims and risk monitoring.

Key Information

Technological Innovations

• Usage-Based Insurance (UBI) will become the norm, with products tailored to individual behavior.
• Smart contracts powered by blockchain will streamline payments and reduce customer acquisition costs.
• Autonomous vehicles, drones, and IoT devices will enable real-time data collection and risk assessment.

Changes in the Role of Agents

• Insurance agents will transition from traditional roles to process facilitators and product educators.
• They will use AI tools like smart assistants and bots to enhance productivity and provide personalized customer interactions.

Regulatory and Ethical Considerations

• Regulators will require transparency in AI models, similar to current regression-based coefficient methods.
• Sensitive data like health and genetic information may be restricted to prevent antiselection and ensure ethical use.

Strategic Recommendations for Insurers

• Invest in AI-related technologies: Board members and customer experience teams should lead efforts to understand AI's potential and implications.
• Develop a strategic plan: A multiyear transformation plan is necessary, covering operations, talent, and technology.
• Create a comprehensive data strategy: Both internal and external data must be managed effectively, with a focus on cost-efficient access and integration.
• Build the right talent and technology infrastructure: Organizations need to invest in skilled professionals and modern IT systems to support AI adoption.

Conclusion

The insurance industry is set for a major transformation by 2030, driven by AI and related technologies. Carriers that embrace these changes, invest in data and talent, and develop strategic, customer-centric approaches will be well-positioned to thrive in the new economic and technological landscape. The key to success lies in viewing AI as an opportunity rather than a threat, and in adapting to a future where insurance is more predictive, personalized, and automated.