AIGC赋能金融产品营销的技术逻辑与应用场景

Technological Logic and Application Scenarios: How AIGC Empowers Financial Product Marketing

摘要: 生成式人工智能(AIGC)正重塑金融产品营销生态，驱动传统金融营销向智能化、精准化维度迭代升级。依托海量训练数据支撑的机器学习模型、深度学习技术、先进算法及强大算力，AIGC能够为金融产品营销的智能化决策提供核心支撑，助力金融机构构建精准客户画像，识别不同场景下客户的潜在需求，进而实现金融产品营销内容的创意生成与精准推荐。在实践层面，AIGC可嵌入金融产品营销全流程，在智能化金融产品设计辅助、投资者教育内容加工、金融产品营销文案自动生成、金融广告创意设计、金融产品精准推送、智能化营销客服与情感化投顾服务等领域发挥赋能作用，为金融行业营销效率提升与客户体验优化提供新路径。与此同时，AIGC应用亦面临模型偏见、数据隐私泄露、算法歧视等技术、合规与伦理风险，需通过全生命周期技术治理、“隐私保护 + 政策响应”合规闭环及“伦理准则 + 多方监督”体系实现风险防控。

Abstract: Generative Artificial Intelligence (AIGC) is transforming the financial product marketing landscape by driving the evolution of traditional financial marketing toward intelligent and precision-oriented approaches. Leveraging massive training data, machine learning models, deep learning technologies, advanced algorithms, and powerful computational capabilities, AIGC provides core support for intelligent decision-making in financial product marketing. It enables financial institutions to develop accurate customer profiles, identify latent consumer needs across various scenarios, and ultimately achieve creative content generation and precise recommendation of financial products. In practice, AIGC can be embedded throughout the entire financial product marketing process, empowering areas such as intelligent product design support, investor education content processing, automated marketing copy generation, creative financial advertisement design, targeted product promotion, intelligent marketing customer service, and emotionally aware investment advisory. This provides new pathways for enhancing marketing efficiency and improving customer experience in the financial industry. At the same time, the application of AIGC also faces technical, compliance, and ethical risks, including model bias, data privacy leakage, and algorithmic discrimination. These risks require comprehensive risk management measures, such as full-lifecycle technical governance, a compliance framework integrating privacy protection and policy responsiveness, and a multi-stakeholder oversight system guided by ethical principles.