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The purpose of this paper is to develop, describe and validate a machine learning model for prioritising which financial transactions should be manually investigated for potential money laundering. The model is applied to a large data set from Norway’s largest bank, DNB.

A supervised machine learning model is trained by using three types of historic data: “normal” legal transactions; those flagged as suspicious by the bank’s internal alert system; and potential money laundering cases reported to the authorities. The model is trained to predict the probability that a new transaction should be reported, using information such as background information about the sender/receiver, their earlier behaviour and their transaction history.

The paper demonstrates that the common approach of not using non-reported alerts (i.e. transactions that are investigated but not reported) in the training of the model can lead to sub-optimal results. The same applies to the use of normal (un-investigated) transactions. Our developed method outperforms the bank’s current approach in terms of a fair measure of performance.

This research study is one of very few published anti-money laundering (AML) models for suspicious transactions that have been applied to a realistically sized data set. The paper also presents a new performance measure specifically tailored to compare the proposed method to the bank’s existing AML system.

In 2019, FIU-the Netherlands celebrated its 25th anniversary. This study takes the occasion to reflect on the role of the FIU in financial surveillance and to describe its core practices of collecting, analysing and disseminating financial intelligence.

Because FIU practices are often secret and its transaction data classified as state secrets, the FIU’s daily operational activities remain obscure. Drawing on interviews, public reports and an online training course, this study encircles secrecy and offers a fine-grained analysis of the FIU's core activities.

The article finds that the FIU plays a pivotal role in financial surveillance because it can operate at various intersections. An FIU operates at the intersection of finance and security, in between the public and private sector and at the national and international domain. This pivotal role makes the FIU indispensable in the surveillance of payment systems and spending behavior.

The article poses that the desirability and effectiveness of financial surveillance has to date not received sufficient consideration, while it affects (the privacy of) anyone with a bank account. The article asks: is it ethically justifiable that transaction information is declared suspect, investigated, and shared nationally and internationally, without the individual or entity concerned officially being notified and legally named a suspect?

This case-study is not only relevant for the study of finance/security, AML/CFT and financial surveillance, but also to policy makers and the broader public who merit an understanding of how their financial behaviour is being surveilled.

Current models of transaction credit in the e-commerce network face many problems, such as the one-sided measurement, low accuracy and insufficient anti-aggression solutions. This paper aims to address these problems by studying the transaction credit problem in the crowd transaction network.

This study divides the transaction credit into two parts, direct transaction credit and recommended transaction credit, and it proposes a model based on the crowd transaction network. The direct transaction credit comprehensively includes various factors influencing the transaction credit, including transaction evaluation, transaction time, transaction status, transaction amount and transaction times. The recommendation transaction credit introduces two types of recommendation nodes and constructs the recommendation credibility for each type. This paper also proposes a “buyer + circle of friends” method to store and update the transaction credit data.

The simulation results show that this model is superior with high accuracy and anti-aggression.

The direct transaction credit improves the accuracy of the transaction credit data. The recommendation transaction credit strengthens the anti-aggression of the transaction credit data. In addition, the “buyer + circle of friends” method fully uses the computing of the storage ability of the internet, and it also solves the failure problem of using a single node.

Blockchain technology was developed to synchronize the data and transactions over the supply chain network and connected nodes. This paper aims to show how blockchain technology can enhance flexibility and agility in supply chain operations. The integration of blockchain and other recently developed technology can help deal with supply chain uncertainties and other challenges being faced by the industry.

Through an extensive literature review of existing research papers and conversation with supply chain managers, barriers and challenges in the supply chain were identified. Some elements were researched of blockchain technology that can be used to resolve some challenges. Blockchain technology and other technologies integration is developed for implementation in supply chain for better visibility and efficiency of supply chain.

The challenges in the supply chain are categorized, and the solution is given through the integration of blockchain and other technologies like Internet of Things and artificial intelligence. The integration shows the execution of tasks through blockchain and various technologies in supply chain.

Blockchain in supply chain is finding its strong place in India when compared to developing nations. There is a need for technology experts, supply chain managers and consumers to understand blockchain’s importance. Challenges faced by industries to use blockchain may be analyzed further with real-life industry case studies.

This research helps enterprises in successful execution of smart technologies in their supply chains. This research helps enterprises in successful execution of smart technologies in their supply chains. Managers and practitioners may use the models developed in real-time implementation. The technologies are described in detail to help the practitioners select the best suitable for their organization.

Digital supply chains are finding the way in industries due to lean and efficient nature. It is beneficial to use the smart technologies to make supply chain green and sustainable.

The implementation of the digital supply chain and its challenges are discussed in the research paper. This will work as a platform for research in the area of technologies for supply chain.

Blockchain technology is provoking significant disruptions, thereby affecting supply chain management. This study endeavoured to advance research regarding blockchain-based supply chain traceability by identifying the opportunities and limitations that accompany the adoption of public blockchains. Therefore, the purpose of the study is to contribute to contemporary supply chain research by an assessment of blockchain technology and its linkages to traceability.

This paper is conceptual. The authors summarised the relevant literature on the concepts of supply chain traceability, conceptualised key elements exclusive to the public blockchain and highlighted opportunities and limitations in implementing traceability using blockchains.

Incompatibilities were identified between general traceability and the public blockchain. However, when embracing the blockchain's privacy model, the blockchains can support information exchange in supply chains where vulnerability towards third parties, the confidentiality of information, or the privacy of participants are concerns. Furthermore, the public blockchain can support areas of supply chains where institutional interest is lacking.

This is one of the first papers in an international supply chain management journal to critically analyse the intersection of specific blockchain characteristics and supply chain traceability requirements. The authors thereby add to the discussion of designs for a disintermediated, peer-to-peer models and guide researchers and practitioners alike in exploring the application of disruptive change from blockchain technologies. By setting focus on the privacy model, the paper identifies the potential application and future research approaches to exploit the elementary strength of the blockchain.

The blockchain technology provides a way to record transactions that is designed to be highly secure, transparent, trustable, traceable, auditable and tamper-proof. And, the internet of things (IoT) technology provides the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction, which is able to link computing devices and digitized machines, things, objects, animals and people that are provided with digital unique identifiers (UIDs). This paper aims to explore the combined application of blockchain and IoT-based technologies, especially on the intellectual property protection area.

In this paper, the authors propose a high-level architecture design of blockchain and IoT-based intellectual property protection system, which can help to process three types of intellectual property: (1) patents, copyrights, trademarks etc.; (2) industrial design, trade dress, craft works, trade secrets etc.; and (3) plant variety rights, geographical indications, etc.

Using blockchain peer-to-peer network and IoT devices, the proposed method can help people to establish a trusted, self-organized, open and ecological intellectual property protection system.

To the best of the authors’ knowledge, this is the first work that applied blockchain and IoT technologies on traditional intellectual property protection and trade ecosystem.

The purpose of this study is to explore what design principles need to be considered in Enterprise Resource Planning (ERP) systems for humanitarian organizations (HOs) to enable agile, adaptive and aligned (Triple-A) humanitarian supply chain capabilities and digitize humanitarian operations.

This study follows an embedded case study approach with a humanitarian medical relief organization, Médecins Sans Frontières (MSF), which engaged in a multiyear ERP design at its humanitarian field missions.

This research shows that ERP systems for humanitarian organizations should be designed as unique systems addressing humanitarian organizations' challenges and unique missions, their value generation processes, and resource base in an effort to improve organizational performance. This study presents 12 general design principles that are unique for humanitarian organizations. These design principles provide a high-level structure of guidance under which specific requirements can be further defined and engineered to achieve success.

The results of this study are based on a single case study limiting generalizability. However, the case study was analyzed and presented as an embedded case study with five autonomous subunits using different business processes and following different adoption and implementation approaches. Therefore, the findings are derived based on considerable variance reflective of humanitarian organizations beyond MSF.

This study recognizes that HOs have unique routines that standard commercial ERP packages do not address easily at the field level. The primary contribution of this research is a set of design principles that consider these unique routines and guide ERP development in practice. National and international HOs that are planning to implement information systems, private companies that are trading partners of HOs as well as vendors of ERP systems that are looking for new opportunities would all benefit from this research.

This study fills the gap in the humanitarian literature regarding the design of ERP systems for humanitarian organizations that enable Triple–A supply chain capabilities and it advances the knowledge of the challenges of ERP design by HOs in the context of humanitarian operations.

The review examines the existing literature on blockchain-based small and medium enterprise (SME) finance and highlights its trend, themes, opportunities and challenges. Based on these factors, the authors create a framework for the existing literature on blockchain-based SME financing and lay down future research paths.

The review follows a systematic approach. It includes 53 articles encompassing multiple dimensions of blockchain-based SME finance, including peer-to-peer lending platforms, supply chain finance (SCF), decentralized lending protocols and tokenization of assets. The review critically evaluates these approaches' theoretical underpinnings, empirical evidence and practical implementations.

The review demonstrates that blockchain-based SME finance holds significant promise in addressing the credit gap by leveraging blockchain technology's decentralized and transparent nature. Benefits identified include reduced information asymmetry, improved access to financing, enhanced credit assessment processes and increased financial inclusion. However, the literature acknowledges several challenges and limitations, such as regulatory uncertainties, scalability issues, operational complexities and potential security risks.

The article contributes to the growing knowledge of blockchain-based SME finance by synthesizing and evaluating the existing literature. It also provides a framework for the existing literature in the area and future research paths. The study offers insights for researchers, policymakers and practitioners seeking to understand the potential of blockchain technology in filling the SME credit gap and fostering economic development through improved access to finance for SMEs.

Data has become a factor of production. This occurs when history enters the era of big data, in which technologies such as artificial intelligence, cloud computing and blockchain are used to collect, manipulate, mine and process data. Data is a special product of labor, a sub-derivative of other production factors.

The data factor has a dual attribute: being physical (technical) and social. The social attribute of the data factor can not only materialize the technical attribute but also amplify it. In other words, the data has a multiplication effect on the allocation efficiency of other production factors. The social attribute of the data is brought out via the technical attribute as the medium. From a technical perspective, this medium is strongly adhesive, and after being bonded with other factors of production, it will only lead to a physical reaction and not change the nature of other factors.

However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

Therefore, to get a scientific understanding of the dual attribute and its interaction effects on the data factor, it is necessary to take the following steps. We should promote institutional design that amplifies the positive externality, with a focus on facilitating public data sharing and improving the value of commercial data development. Also, we need to strengthen institutional arrangements that prevent and control the negative externality by emphasizing data supervision based on data types and levels as well as the rule of law.