Part II Trade Finance Technology, 12 Will Blockchain Transform Trade Finance?

The administration of cross-border trade remains dominated by complex, old-fashioned, hybrid human-computer-paper systems long after disruptive innovations have transformed commerce in many other domains. Interest in blockchain is driven by the desire to cut through the ‘Gordian knot’ of complex, fragmented, anachronistic legacy trade-finance systems now in use. Blockchain advocates believe it is superior to the legacy database technologies currently in use in all important transaction-processing systems and designed to work within hierarchically networked computer systems controlled by large organisations. These advocates appear unaware, however, of the wide range of practical functions performed by different elements of existing trade finance systems, and are thus proposing alternatives that cannot perform all the functions of the systems they propose to replace. This kind of mismatch between real-world business requirements and the theoretical advantages of blockchain alternatives goes a long way to explain the failure of any blockchain projects to achieve widespread success in the market. Incremental efforts to transform trade finance in light of actual stakeholder requirements are both less vulnerable to speculative bubbles and more likely to meet the actual requirements of the many, diverse participants in global trade-finance systems today.

An Applicability of Blockchain Model in Business use Case - A Technical Approach

Business network brings many organizations close together to achieve their desired goals and profit from it. People from different organizations may or may not know each other but still can be part of a business network. A major challenge with these business networks is how to provide trust among people and data security. Blockchain is another means through which many organizations in the current digital age are overcoming these problems with ease. Blockchains have also changed the way the business transactions with clients take place. Blockchain is a decentralized distributed ledger in a peer to peer network which can be public or private, and it enables individuals or companies to collaborate with each other to achieve trust and transparency between business and its clients. Many implementations of blockchain technology are widely available today. Each of them have their own strengths for a specific application domain. They can fundamentally alter electronic communications with a potential to affect all sorts of transaction processing systems. However, there are still many challenges of blockchain technology waiting to be solved such as scalability and adoptability. In this paper, we provide the knowledge on Blockchain technology and we present the applicability of blockchain in the business models and also discuss the relevant use cases for Banking and Supply Chain models.

Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook

The rise of digital payments has caused consequential changes in the financial crime landscape. As a result, traditional fraud detection approaches such as rule-based systems have largely become ineffective. Artificial intelligence (AI) and machine learning solutions using graph computing principles have gained significant interest in recent years. Graph-based techniques provide unique solution opportunities for financial crime detection. However, implementing such solutions at industrial-scale in real-time financial transaction processing systems has brought numerous application challenges to light. In this paper, we discuss the implementation difficulties current and next-generation graph solutions face. Furthermore, financial crime and digital payments trends indicate emerging challenges in the continued effectiveness of the detection techniques. We analyze the threat landscape and argue that it provides key insights for developing graph-based solutions.

The Rise of NoSQL Systems

Transaction processing systems are primarily based on the relational model of data and offer the advantages of decades of research and experience in enforcing data quality through integrity constraints, allowing concurrent access and supporting recoverability. From a performance standpoint, they offer joins-based query optimization and data structures to promote fast reads and writes, but are usually vertically scalable from a hardware standpoint. NoSQL (Not Only SQL) systems follow different data representation formats than relations, such as key-value pairs, graphs, documents or column-families. They offer a flexible data representation format as well as horizontal hardware scalability so that Big Data can be processed in real time. In this review article, we review recent research on each type of system, and then discuss how teaching of NoSQL may be incorporated into traditional undergraduate database courses in information systems curricula.

Optimization of the Use of Transaction Processing Systems in Minimarkets

The use of information technology in supporting the effectiveness of company operations is very important. This study aims to determine the optimization of the use of Transaction Processing Systems in minimarkets in the city of Padang. Sampling uses accidental sampling of the owner/manager and operator in the Minimarket. The analytical method used in this study is a descriptive analysis. The results showed that 85.6% of 97 minimarkets in Padang had used transaction processing systems in support of sales activities and services to consumers. The use of computer-based transaction processing systems had resulted in shopping receipts to reduce the level of error in calculating shopping values. Information about prices and changes made by updating the database and changing labels on the product manually. Limited cooperation with banks is only 49% of minimarket providing payment facilities by debit/credit card. An interesting finding from this study is that there is a gap between the use of transaction processing systems for sales and inventory. Only 8% of minimarkets obtain information on the amount of inventory through a transaction processing system. The ordering of goods, only 10% are planned through the information system. This gap will affect the minimarket financial reports. For making this report only 14.4% of the minimarkets were able to obtain this information from the system. From the overall analysis, it can be concluded that the level of utilization of information systems for operational effectiveness is still relatively low. Keywords: Transaction Processing System, Sales, Inventory, Financial Report

Pengembangan Arsitektur Data Sistem Informasi Pondok Pesantren

Data management is very necessary in an institution to facilitate data processing. One of them is Islamic education institutions or Islamic boarding schools that have developed nformation systems for Islamic boarding school. In building a boarding school information system, applications and data are needed. Data architecture obtained from a hierarchy of information systems consisting of executive information systems, management informations systems, and transaction processing systems. Architecture design of information systems for Islamic boarding school is done by building an ERD (Entity Relationship Diagram) from a collection of data needed on boarding school information systems. ERD is a database building model by describing relations between database entities.

Design and Application of a Containerized Hybrid Transaction Processing and Data Analysis Framework

This article describes how rapidly growing data volumes require systems that have the ability to handle massive heterogeneous unstructured data sets. However, most existing mature transaction processing systems are built upon relational databases with structured data. In this article, the authors design a hybrid development framework, to offer greater scalability and flexibility of data analysis and reporting, while keeping maximum compatibility and links to the legacy platforms on which transaction business logics run. Data, service and user interfaces are implemented as a toolset stack, for developing applications with functionalities of information retrieval, data processing, analyzing and visualizing. A use case of healthcare data integration is presented as an example, where information is collected and aggregated from diverse sources. The workflow and simulation of data processing and visualization are also discussed, to validate the effectiveness of the proposed framework.