大数据下人工智能证据链对电商跨境风险规避

Artificial Intelligence Evidence Chain for E-Commerce Cross-Border Risk Aversion under Big Data

摘要: 电商跨境需要面临着多主体、长链条的交易环境，既往以单点信息为主的风控模式很难形成具备可追溯和可自证的闭环证据，导致风险规避越发被动且低效。若企业只是依靠单纯的规则引擎、孤立化的模型将很难规避电商跨境中的诸多风险，也难以在争议场景中提供具备充足法律效力的自证材料。基于此，文章以大数据为基本底座，探索人工智能(AI)证据链对电商跨境风险规避的价值、策略与具体的实施路径，以期利用AI证据链为电商跨境风险的有效管控和规避提供工具支持，确保电商跨境交易的安全与可靠。

Abstract: E-commerce cross-border needs to face a multi-agent and long chain trading environment. The previous risk control mode based on single point information is difficult to form a traceable and self verifiable closed-loop evidence, resulting in more passive and inefficient risk aversion. If enterprises only rely on a simple rule engine and isolated model, it will be difficult to avoid many risks in cross-border e-commerce, and it will also be difficult to provide self certification materials with sufficient legal effect in controversial scenes. Based on this, this paper explores the value, strategy and specific implementation path of artificial intelligence (AI) evidence chain for e-commerce cross-border risk avoidance based on big data, in order to provide tool support for effective control and avoidance of e-commerce cross-border risk by using AI evidence chain, and ensure the safety and reliability of e-commerce cross-border transactions.