科技如何重塑保险资管？中国人寿（海外）魏晓鹏，最新发声

Core Viewpoint - The core viewpoint of the article emphasizes the transformative role of technology, particularly AI, in reshaping insurance asset management, focusing on enhancing decision-making stability rather than aggressive investment strategies [2][6]. Group 1: Evolution of Insurance Asset Allocation - The evolution of insurance asset allocation has transitioned from reliance on experience and single yield targets to a multi-objective balancing phase centered on duration, yield, and liquidity [4]. - Currently, the complexity of the environment, including rising geopolitical risks and new accounting standards, necessitates a shift from "what assets to select" to finding "explainable, verifiable, and executable optimal solutions" under multiple constraints [5]. Group 2: Value of Technology in Investment - The primary value of technology in insurance asset management is to make investment decisions more robust rather than more aggressive [7]. - A systematic strategic asset allocation framework has been implemented by the company, focusing on value and profit, exploring AI applications in scenario-based asset allocation [7]. - An example of cross-asset allocation demonstrated that an algorithm reduced capital risk indicators by 15% while maintaining expected surplus, integrating liabilities, capital, returns, and risks into a unified decision-making methodology [7]. Group 3: AI's Role in Insurance Asset Management - AI's role is not to replace decision-makers but to amplify system capabilities, starting from three fundamental aspects rather than market prediction [9]. - The first aspect is the structured processing of high-dimensional data, enabling the identification of structural relationships among thousands of assets and numerous constraints [10]. - The second aspect involves scenario generation and portfolio simulation, allowing for the creation of more realistic potential paths compared to traditional assumptions [10]. - The third aspect is human-machine collaborative decision support, where AI provides decision spaces, risk boundaries, and trade-offs, with final decisions made by the investment decision committee [10]. Group 4: Challenges in AI Application - The true challenge in the technological transformation of insurance asset management lies not in the availability of AI but in whether the organization possesses a compatible decision-making mechanism and culture [12]. - Collaboration among research, risk control, actuarial, and IT departments in a common language is essential, as is management's acceptance of using systems to constrain personal judgment [13]. - Although technology cannot provide direct answers, it helps in approaching long-term optimal solutions amidst uncertainty, maintaining the mission of serving the real economy and social development responsibly [13].