In today's increasingly digital interactions, robust Identity Verification (IDV) is crucial for security and trust. Artificial Intelligence (AI) is transforming IDV, enhancing accuracy and fraud detection. This paper introduces ``Zero to One,'' a holistic conceptual framework for developing AI-powered IDV products. This paper outlines the foundational problem and research objectives that necessitate a new framework for IDV in the age of AI. It details the evolution of identity verification and the current regulatory landscape to contextualize the need for a robust conceptual model. The core of the paper is the presentation of the ``Zero to One'' framework itself, dissecting its four essential components: Document Verification, Biometric Verification, Risk Assessment, and Orchestration. The paper concludes by discussing the implications of this conceptual model and suggesting future research directions focused on the framework's further development and application. The framework addresses security, privacy, UX, and regulatory compliance, offering a structured approach to building effective IDV solutions. Successful IDV platforms require a balanced conceptual understanding of verification methods, risk management, and operational scalability, with AI as a key enabler. This paper presents the ``Zero to One'' framework as a refined conceptual model, detailing verification layers, and AI's transformative role in shaping next-generation IDV products.

本研究针对当前数字互动中身份验证流程存在的问题，提出了“零到一”这一全新的概念框架，以支持基于人工智能的身份验证产品的开发。该框架的核心在于四个基本组成部分：文档验证、生物识别验证、风险评估和协调，为推动更有效的身份验证解决方案提供了结构化的方法。研究表明，该框架在安全性、隐私和合规性方面具有重要意义，并为未来研究指明方向。

零到一身份验证：一个基于人工智能的身份验证概念模型