Purpose

This paper advocates the use of graph database platforms to investigate networks of illicit companies identified in money laundering schemes. It explains the setup of the data structure to investigate a network of illicit companies identified in cases of money laundering schemes and presents its key application in practice. Grounded in the technology acceptance model (TAM), this paper aims to present key operationalisations and theoretical considerations for effectively driving and facilitating its wider adoption among a range of stakeholders focused on anti-money laundering solutions.

Design/methodology/approach

This paper explores the benefits of adopting graph databases and critiques their limitations by drawing on primary data collection processes that have been undertaken to derive a network topology. Such representation on a graph database platform provides the opportunity to uncover hidden relationships critical for combatting illicit activities such as money laundering.

Findings

The move to adopt a graph database for storing information related to corporate entities will aid investigators, journalists and other stakeholders in the identification of hidden links among entities to deter activities of corruption and money laundering.

Research limitations/implications

This paper does not display the nodal data as it is framed as a background to how graph databases can be used in practice.

Originality/value

To the best of the authors’ knowledge, no studies in the past have considered companies from multiple cases in the same graph network and attempted to investigate the links between them. The advocation for such an approach has significant implications for future studies.

中文翻译：

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使用图数据库平台打击洗钱：提倡大规模采用

目的

本文提倡使用图形数据库平台来调查洗钱计划中发现的非法公司网络。它解释了数据结构的设置，以调查在洗钱计划案件中发现的非法公司网络，并介绍了其在实践中的关键应用。本文以技术接受模型 (TAM) 为基础，旨在介绍有效推动和促进其在专注于反洗钱解决方案的一系列利益相关者中更广泛采用的关键操作和理论考虑。

设计/方法/方法

本文探讨了采用图形数据库的好处，并通过利用为推导网络拓扑而进行的主要数据收集过程来批评它们的局限性。图数据库平台上的这种表示提供了发现隐藏关系的机会，这些关系对于打击洗钱等非法活动至关重要。

发现

采用图形数据库存储与公司实体相关的信息的举措将有助于调查人员、记者和其他利益相关者识别实体之间的隐藏链接，以阻止腐败和洗钱活动。

研究限制/影响

本文不显示节点数据，因为它是作为如何在实践中使用图形数据库的背景。

原创性/价值

据作者所知，过去没有研究考虑过同一图网络中来自多个案例的公司，并试图调查它们之间的联系。提倡这种方法对未来的研究具有重要意义。