论文标题
在海关欺诈检测中通过域适应的知识共享
Knowledge Sharing via Domain Adaptation in Customs Fraud Detection
论文作者
论文摘要
了解不断变化的流量对于风险管理至关重要。传统上，全世界的海关办公室一直依靠当地资源来积累知识并检测税收欺诈。这自然会构成基础设施薄弱的国家成为潜在非法行业的税收天堂。当前的论文提出了DAS，这是一个存储库平台，旨在促进跨多国家海关管理部门之间的知识共享以互相支持。我们提出了一种域适应方法，可以在保护当地贸易信息的同时共享有关欺诈作为原型的可转让知识。已经使用了超过800万个进口声明的数据来测试该新系统的可行性，这表明参与国家的借助共享知识的帮助可能会使欺诈检测高达2-11倍。我们讨论对大量税收潜力的影响，并加强针对非法交易的政策。
Knowledge of the changing traffic is critical in risk management. Customs offices worldwide have traditionally relied on local resources to accumulate knowledge and detect tax fraud. This naturally poses countries with weak infrastructure to become tax havens of potentially illicit trades. The current paper proposes DAS, a memory bank platform to facilitate knowledge sharing across multi-national customs administrations to support each other. We propose a domain adaptation method to share transferable knowledge of frauds as prototypes while safeguarding the local trade information. Data encompassing over 8 million import declarations have been used to test the feasibility of this new system, which shows that participating countries may benefit up to 2-11 times in fraud detection with the help of shared knowledge. We discuss implications for substantial tax revenue potential and strengthened policy against illicit trades.
