2018年-数据局_中国信通院：区块链让城市治理更智慧_12页_862kb

报告摘要

Summary of "Customer Experience of the Future"

Core Content

This document explores the role of Intelligent Virtual Assistants (IVAs) and chatbots in transforming customer experience (CX) in the insurance industry. It emphasizes how these technologies can enhance communication, streamline processes, and improve efficiency while aligning with broader digital strategies.

Main Points

What are IVAs and Chatbots?

Intelligent Virtual Assistants (IVAs): Advanced AI-driven systems that simulate human communication (text or voice) and automate common customer inquiries and service requests.
Chatbots: Powered by AI and natural language processing (NLP), they enable automated, two-way communication via web and mobile interfaces.
Integration: IVAs are integrated with back-end systems such as CRM platforms, allowing them to access account details, policy documents, and other data for efficient and personalized service.

Key Benefits of IVAs

Increased Efficiency: Automate repetitive tasks and FAQs, reducing human workload and improving customer service speed.
Enhanced Customer Experience: Offer personalized, intuitive, and convenient interactions across multiple channels.
Intelligent Upselling and Cross-Selling: Leverage AI, machine learning, and data insights to identify and pursue sales opportunities.
Stronger Risk Management: Reduce human errors, provide auditable trails, and support advanced authentication procedures.

Use Cases in Insurance

Policy Upgrades: Simplify the process for customers to update their policies with additional coverage.
Roadside Assistance: Enable faster and more efficient access to assistance for stranded policyholders.
Self-Service Administration: Automate routine tasks such as updating addresses or managing claims.
Application and Renewal Processes: Streamline initial steps in application and renewal by automating data collection and processing.

Technology Behind IVAs

Natural Language Processing (NLP): Enables understanding and responding to customer queries.
Natural Language Understanding (NLU): Enhances the ability to interpret user intent.
Artificial Intelligence (AI) and Machine Learning: Improve the sophistication and adaptability of IVAs.
Robotic Process Automation (RPA): Automates back-end processes for faster and more accurate service delivery.

Key Information

Market Trends

Consumer Adoption: 90% of consumers prefer messaging for business communication.
Company Adoption: 80% of companies plan to use chatbots by 2020.
Digital Transformation: By 2020, customer experience is expected to surpass price and product as the key competitive differentiator.

Implementation Strategy

Three Phases:
1. Business Case Development: Research and data analysis to identify value and align with business strategy.
2. Planning: Designing IVA blueprints, communication flows, and technical architecture.
3. Implementation: Development, testing, and post-launch tracking for continuous improvement.

Quick Wins and Strategic Opportunities

Quick Wins: Use cases with high business value, low complexity, and minimal technical requirements (e.g., policy upgrades, self-service tasks).
Strategic Opportunities: Advanced use cases with high business and technical demands (e.g., integration with IoT, telematics).

Conclusion

IVAs are a critical component of the future of customer experience in the insurance industry.
They offer a flexible, scalable, and cost-effective solution for improving CX, increasing revenue, and reducing operational risks.
A well-planned implementation strategy is essential to ensure success and maximize ROI.

Figures and Data

Figure 1: Highlights IVAs' ability to both share information and complete transactions.
Figure 2: Demonstrates the benefits of combining IVAs with other digital technologies.
Figure 3: Shows the importance of a robust governance framework for risk management.
Figure 4: Illustrates the maturity levels of IVAs based on technical capabilities.
Figure 5: Depicts the range of IVA deployment opportunities for insurers.