Transaction Processing Research Articles

Supply chain fraud prediction with machine learning and artificial intelligence

As businesses undergo digital transformation, supply chain fraud poses an increasing threat, necessitating more sophisticated detection and prevention methods. This paper explores the application of machine learning (ML) and artificial intelligence (AI) in detecting and preventing supply chain fraud. The research design involves analyzing a dataset of supply chain operations and employing various ML algorithms to detect consumer-based fraud within the supply chain, which occurs when consumers partake in deceptive practices during the order process of e-commerce transactions. We analyzed 180,000 transactions from an international company recorded between 2015 and 2018. This study emphasises the necessity of human oversight in interpreting the results generated by these technologies. The implications of supply chain fraud on financial stability, legal standing, and reputation are discussed, along with the potential for ML technology to identify irregularities indicative of fraud. Descriptive findings highlight the prevalence of fraudulent transactions in specific payment types. The AI sequential and the CatBoost classifiers were the top-performing algorithms across all performance metrics. The top features to detect unusual orders are delivery status, payment type, and late delivery risks. The discussion emphasises the promising predictive capabilities of the ML and AI models and their implications for detecting supply chain fraud.

Exploring Improvement of Business Performance of Transaction Processing System in Retail Sector

Exploring Improvement of Business Performance of Transaction Processing System in Retail Sector

Multi-microgrid Energy Management Based on Finite Horizon Twin Delayed Deep Deterministic Policy Gradient

Background: With the increasing integration of renewable energies into smart microgrids, the parameter space of the microgrid system model has increased dramatically, leading to critical computational challenges in achieving the dispatch strategy. Objective: Additionally, in remote areas, connecting renewable energy resources to the national grid is unavailable due to the high costs. Consequently, we have introduced microgrids as a viable alternative solution. Microgrids are small-scale distributed power grids that rely on renewable energy sources and generators to balance the load demand. The aim of this paper is to improve the reliability of microgrids by integrating machine learning techniques into their control. This technology ensures that all loads in the microgrid are met through energy trading. Methods: This algorithm utilizes reinforcement learning as the control mechanism for the trading process. We have established a set of trading rules that facilitate energy trades among three microgrids. We designate one of these three microgrids as the primary microgrid, while the other two function as trading microgrids. Firstly, a deep reinforcement learning algorithm (FH-TD3) is developed as a solution. Subsequently, the performances obtained in the three regions are compared with those derived from traditional algorithms. Finally, the effectiveness of the proposed energy management strategy was validated through simulations. Results: FH-TD3 has shown superior performance to DDPG in three different microgrid experiments, with the FH-TD3 algorithm consistently exhibiting shorter iteration times compared to the DDPG algorithm. Conclusion: The research shows that the algorithm realizes the balance of the power without the loss of the power grid, and realizes the profit in the transaction process.

NeuChain+: A Sharding Permissioned Blockchain System with Ordering-Free Consensus

Permissioned blockchains are widely used in scenarios such as digital assets, supply chains, government services, and Web 3.0, but their development is hindered by low throughput and scalability. Blockchain sharding addresses these issues by dividing the ledger into disjoint shards that can be processed concurrently. However, since cross-shard transactions require the collaboration of multiple shards, blockchain sharding needs a commit protocol to ensure the atomicity of executing these transactions, significantly impacting system performance. To this end, by exploiting the characteristics of deterministic ordering, we propose a cross-shard transaction processing protocol called cross-reserve, which eliminates this costly cross-shard coordination while providing the same consistency and atomicity guarantee. Based on the ordering-free execute–validate (EV) architecture, we implemented a blockchain prototype called NeuChain+, which further reduces the cross-shard transaction processing overhead using the pipelined read sets transmission. Experimental results show that NeuChain+ is scalable and outperforms state-of-the-art blockchain systems with 1.7–75.3× throughput under the SmallBank workload.

A survey on hybrid transactional and analytical processing

To provide applications with the ability to analyze fresh data and eliminate the time-consuming ETL workflow, hybrid transactional and analytical (HTAP) systems have been developed to serve online transaction processing and online analytical processing workloads in a single system. In recent years, HTAP systems have attracted considerable interest from both academia and industry. Several new architectures and technologies have been proposed. This paper provides a comprehensive overview of these HTAP systems. We review recently published papers and technical reports in this field and broadly classify existing HTAP systems into two categories based on their data formats: monolithic and hybrid HTAP. We further classify hybrid HTAP into four sub-categories based on their storage architecture: row-oriented, column-oriented, separated, and hybrid. Based on such a taxonomy, we outline each stream’s design challenges and performance issues (e.g., the contradictory format demand for monolithic HTAP). We then discuss potential solutions and their trade-offs by reviewing noteworthy research findings. Finally, we summarize emerging HTAP applications, benchmarks, future trends, and open problems.

Thematic Analysis of Consumer Processes When Experiencing E-Money Transactions

This study delves into the intricate processes of consumer transactions within e-money (or e-wallet) applications, across the pre-, during-, and post-transaction phases. Through in-depth interviews conducted with experts who concurrently serve as active users of e-money platforms, utilizing a qualitative research methodology and thematic analysis facilitated by the advanced Computer Assisted Qualitative Data Analysis Software (CAQDAS), particularly Atlas.ti, version 22, the research identifies three interconnected themes inherent in the e-money consumer transaction process: pre-transaction considerations, the actual transaction experience, and post-transaction reflections. A crucial aspect highlighted in this investigation is the discerning approach adopted by e-money consumers, who engage in thorough background research on various Electronic Money Institutions (EMIs) to strategically select the most suitable provider. Additionally, the study draws attention to innovative features, such as a 'shake to get a reward' incentive, implemented by some EMIs, which enhance the overall user experience. The overarching aim of this research is to contribute significantly to the understanding of e-money consumer protection issues by unravelling the processes inherent in digital transactions. The findings not only shed light on the nuanced dynamics of e-money transactions but also provide crucial insights into consumer behaviours and preferences at each phase of the transaction process. Ultimately, this research serves as a valuable foundation for ongoing discussions aimed at enhancing consumer protection in the evolving landscape of digital financial interactions.

The role of the ISO 20022 messaging standard in improving payment transactions utilising participants’ data

This paper critically evaluates the prospective influence of ISO 20022, a widely recognised communications standard, on payment services. ISO 20022 provides a standardised and extendable framework aimed at improving efficiency, interoperability, and customer experience in the financial sector. The paper examines how ISO 20022 application can drive revolutionary improvements in payment processing, speeding up transaction processes, and increasing data richness. It also emphasises the importance of taking a balanced approach to ISO 20022 adoption, taking into account both the benefits and obstacles. While ISO 20022 offers enormous opportunity for modernising payment services, organisations must overcome a number of challenges, including technological improvements, data migration and regulatory compliance, to fully realise its promise. By accepting ISO 20022 and addressing its related obstacles, stakeholders can realise the revolutionary benefits of this standard, paving the way for a more efficient and interoperable payment environment.

Fast Commitment for Geo-Distributed Transactions via Decentralized Co-Coordinators

In a geo-distributed database, data shards and their respective replicas are deployed in distinct datacenters across multiple regions, enabling regional-level disaster recovery and the ability to serve global users locally. However, transaction processing in geo-distributed databases requires multiple cross-region communications, especially during the commit phase, which can significantly impact system performance. To optimize the performance of geo-distributed transactions, we propose Decentralized Two-phase Commit (D2PC), a new transaction commit protocol aiming to minimize the negative impact of cross-region communication. In D2PC, we employ multiple co-coordinators that perform commit coordination in parallel. Each co-coordinator is responsible for collecting 2PC votes and making a PreCommit decision in its local region. This approach allows for the concurrent invocation of multiple cross-region network round trips, and each region can end its concurrency control locally before replication is complete, thus significantly reducing the chances of blocking and enhancing system concurrency. Moreover, we propose the bypass leader replication reply method, leveraging decentralized co-coordinators to bypass the leader for message transmission, thereby reducing the commit latency. Experimental results have demonstrated that D2PC can reduce commit latency by 43% and improve throughput by up to 2.43 × compared to the geo-distributed transaction processing methods based on 2PC.

Save the Bank: Centralized Digital Bank — Centralization and Digitalization as Strategic Imperatives

This thesis explores the transformation of traditional banks into centralized digital banking systems as a strategic response to the burgeoning challenges posed by decentralized finance (DeFi) technologies such as blockchain and cryptocurrencies. As these technologies disrupt traditional financial paradigms, offering more direct, efficient, and transparent financial services, traditional banks face increasing pressure to adapt and evolve. This work argues for the necessity and feasibility of centralized digital banking as a comprehensive countermeasure to DeFi. Through a detailed examination of current banking challenges, including inefficiencies in customer service, transaction processing, and compliance, the thesis proposes a model of banking that leverages centralization and digitalization to address these issues. The proposed model not only enhances operational efficiency and customer engagement but also fortifies the banks’ competitive edge in a digital economy. Furthermore, the thesis discusses the long-term implications of such transformations, predicting that centralized digital banks will not only coexist with DeFi platforms but may also lead the financial services industry by adopting innovative technologies that drive customer satisfaction and operational excellence. Recommendations are provided for both banks and policymakers to foster an environment conducive to the development of robust, secure, and customer-focused digital banking services. In summary, this thesis affirms that centralized digital banking is not merely a defensive strategy against the rise of DeFi but a forward-looking approach that will define the future of banking.

HybridChain: Fast, Accurate, and Secure Transaction Processing With Distributed Learning

HybridChain: Fast, Accurate, and Secure Transaction Processing With Distributed Learning

Being your ‘authentic self’: A key to success in the buyer–supplier relationship in indirect procurement

Early in a career as a procurement professional, practitioners are focused on the goals of the company and how to achieve their own career goals as they traverse the buyer–supplier relationships, obtaining the company’s needed goods and services. For practitioners in the indirect categories, the sheer number of suppliers that must be interacted with is sometimes daunting. Finding the keys to building successful buyer–supplier relationships is often reduced to a formulaic transactional process. To be truly successful, you must become well versed in how your own personal traits become key in building relationships with suppliers. Suppliers that provide goods and services, considered indirect purchases, are not always transactional relationships. While these suppliers do not provide raw materials for your company’s production, they supply the infrastructure that supports the whole company and helps bring those finished products or services to market. With that in mind, it is integral to the success of your company that you have good relationships with these suppliers, built on the foundation of trust. In building that trust, the practitioner must become comfortable with the aspects of transparency, integrity and being their authentic self when working with the representatives of their suppliers. While there are risks and pitfalls that must be kept in mind, the personal traits that you present to your suppliers could very well be the key to your success or failure in your role as a procurement professional.

SolsDB: Solve the Ethereum’s bottleneck caused by storage engine

Ethereum’s block synchronization process interacts with the storage engine in two parts: waiting for state data to be read while processing transactions and waiting to write data after processing is complete. Presently, Ethereum utilizes the LSM-tree-based storage engine that not only falls short of meeting Ethereum’s read performance requirements but also presents additional mismatches. In this paper, we propose the single-level ordered log structure database (SolsDB), which fully utilizes state data features to satisfy the workload requirements of Ethereum block synchronization process and suggest novel interactions to deliver state data features to the storage engine. The write feature of state data is utilized to store state data in blocks and the file is globally ordered, which avoids write amplification caused by compaction. By delivering the read feature, the Parser module is crafted to parse the query key, enabling direct file location without the need for level-by-level querying, thus addressing the issue of read amplification. Extensive experiments are conducted to validate the performance of SolsDB. Compared with LevelDB, SolsDB improves read performance by up to 4.7x, reduces read tail latency by 68.7% to 83.3%, and reduces the write amplification factor by 49.1% to 76.1%.

Application Analysis of Criminal Sanctions for Embezzlement of Tax Fees Deposits for Land and Building Rights (BPHTB) Acquisition Committed by Notaries - PPAT

In practice, Notary or PPAT often act as intermediaries for depositing the Acquisition of Rights over Land and Buildings Tax BPHTB payments to facilitate the transaction process. However, it is regrettable that some individuals serving as Notaries occasionally abuse their power and authority regarding BPHTB payments. The type of research conducted in this paper is Doctrinal. The results of the discussion indicate that the responsibility of a Notary should be to carry out their duties and authority properly and firmly, without violating the rules governing their position. The conclusion drawn from this analysis is that a Notary is responsible for the assistance provided in the BPHTB payment process for clients, and not for exploiting the money for personal interests. Such actions can cause losses to clients and the state. The legal consequences for Notaries who abuse their authority include criminal sanctions and the obligation to compensate clients who suffer losses due to their actions.

LEGAL PROTECTION FOR USER STUDENTS E-MONEY AS A NON-CASH PAYMENT TOOL IN THE ISLAMIC BOARDING SCHOOL ENVIRONMENT

Electronic money, or what is known as e-money according to the Bank Indonesia Regulation Number 20/6/PBI/2018 concerning Electronic Money, is a faster transaction process when compared to cash because there is no need for online authorization, signature or PIN, and balance e-money can be filled in from various means provided by the publisher. This research evaluates the legal protection for students who use e-money as a non-cash payment in the Islamic boarding school environment.

Optimizing Student Information Management: A Holistic Examination of Implementation Strategies

This study explores the implementation of a Student Information and Accounting System (SIAS) at Benguet State University with the aim of enhancing academic efficiency. A thorough analysis evaluates the impact of SIAS on educational processes, records management, and transaction processing, focusing on assessing its effectiveness in improving administrative and academic operations, streamlining student information management, and enhancing overall academic performance. The findings underscore the importance of transitioning to such a system to boost efficiency, reduce errors, and improve student services. Recommendations include integrating SIAS with the university's website, implementing security measures, and conducting regular evaluations to align the system with evolving institutional needs. This abstract underscore the significance of adopting an online Student Information System for improved management and service delivery at Benguet State University.

Cashier App Revolutionizes Internal Controls in Global Enterprises

This study evaluates the effectiveness of cashier application-based cash receipt systems as internal controls in small-scale enterprises, focusing on Lugo Coffee House in Tulungagung, Indonesia. Through qualitative analysis of interviews, observations, and document reviews, the study examines the functionality and integration of internal controls within these systems. Findings indicate that while the systems demonstrate efficiency in transaction processing and record-keeping, deficiencies such as the absence of task segregation pose potential risks. Nonetheless, the overall sufficiency of these systems in mitigating financial risks is affirmed. The study highlights the importance of optimizing cashier application-based systems to enhance financial management practices and minimize risks associated with cash transactions in similar organizational contexts. Highlights: 1. Assessing cashier app systems in small enterprises.2. Identifying internal control strengths and weaknesses.3. Optimizing financial management to minimize risks. Keywords: Cashier application, Internal controls, Small-scale enterprises, Financial management, Risk mitigation.

A Critical Analysis of Machine Learning Techniques for Online Transaction Security

The widespread adoption of Unified Payments Interface (UPI) as the preferred digital transaction method has led to a sharp increase in fraudulent activities, presenting a considerable challenge to the security and reliability of online payments.Top of Form To address this pressing concern, our project focuses on developing a sophisticated fraud detection system tailored specifically for UPI transactions. We utilize Convolutional Neural Networks (CNNs), an advanced deep learning architecture, to intricately capture the sequence of operations involved in UPI transaction processing. Through extensive data collection and preprocessing, we curate a diverse dataset comprising various transaction types, amounts, and temporal patterns, ensuring comprehensive coverage of transaction behaviour. The CNN is meticulously trained on this dataset, leveraging its innate ability to discern subtle patterns and dependencies within transaction sequences. Notably, our approach emphasizes the importance of minimizing false positives to prevent genuine transactions from being erroneously flagged as fraudulent. In real-time, incoming UPI transactions are subjected to scrutiny by the trained CNN, which evaluates their conformity to learned normal behaviour patterns. Transactions exhibiting deviations indicative of potential fraud are promptly flagged for further investigation, thus enabling proactive mitigation of fraudulent activities. Most importantly, our study contains a comprehensive comparative analysis that compares the efficacy of conventional machine learning methods such as Support Vector Machines (SVM), Random Forests, and Logistic Regression with CNN-based fraud detection. Through meticulous evaluation, we demonstrate the superior efficacy of CNNs in detecting fraudulent UPI transactions, owing to their inherent capacity to capture intricate spatial and temporal dependencies. Our findings underscore the transformative potential of deep learning techniques in bolstering the security and resilience of digital payment ecosystems, thereby safeguarding users and fostering trust in online transactions.

Financial Technology Services, Government Regulations and Financial Inclusion of Small-Scale Fish Farmers in Homa Bay County, Kenya

This study explored the impact of FinTech and Government Policies on Financial Inclusion for small-scale fish farmers in Homa Bay County, Kenya. The study focused on how access to finance has been widened through agency banking, mobile money and online banking services among these people who had low incomes or were marginalized. The research also examined whether government regulations affect the relationship between fintech channels and financial inclusion. The study was underpinned by Innovation Diffusion Theory, Financial Intermediation Theory, Technology Acceptance Theory and Public Interest Regulation Theory. This study employed causal research design with a sample size of 495 small scale fish farmers using stratified random sampling technique that yielded 144 respondents. Data analysis involved multiple regression, correlation analysis and diagnostic tests that utilized SPSS 26.0 for data analysis. The results showed that agency banking; mobile money services and online banking together explained 58.1% of variation in financial inclusion among the farmers indicated by R squared of 0.581.The findings revealed that Agency Banking had significant effect on financial inclusion (β = .231, p = .001 < .05), as well as Mobile Money Services (β = .196, p = .019 < .05) and Online Banking Services (β = .410, p = .000 < .05). Therefore, the study concludes that Agency Banking; Mobile Money and Online Banking play important role in enhancing financial autonomy among small scale fish farming communities through increased access to bank accounts, secured transactions processes and agent incomes respectively. In view of the findings, the study recommends that financial institutions together with fintech companies should invest in platforms which are user-friendly safe secure meant for use by small holder dairy farmers themselves. Keywords: Agency banking, Mobile money services, Online banking services, Government regulations, Financial technology services, Financial inclusion

SMART LOCK SYSTEM USING IOT AND SOLANA BLOCKCHAIN

This project explores the integration of Solana blockchain technology with smart locking systems to revolutionize access control and security. Leveraging the decentralized and immutable nature of the Solana blockchain, the intelligent system provides a powerful platform to manage access permissions and monitor lock transactions in real-time. With integrated management and remote control, users can grant or revoke access from any mobile or web application. The scalability and efficiency of the Solana blockchain enable the system to process large volumes of transactions without sacrificing performance, making it suitable for widespread use in the field, workplace, and office. Overall, the integration of the Solana blockchain into smart registration systems represents a significant advance in access control, providing a secure, transparent and user-friendly solution to the problems of the digital age. This project presents the design and implementation of a smart lock system empowered by Solana blockchain technology, aimed at enhancing security, transparency, and efficiency in access control. Leveraging a distributed ledger framework, the system facilitates decentralized access management, allowing users to remotely authorize and monitor door access through a user-friendly mobile/web interface. The integration of Solana blockchain ensures immutability and transparency in access permissions, while also offering scalability and low-latency transaction processing capabilities. Hardware components, including smart lock mechanisms and gateway devices, are seamlessly integrated with software modules such as firmware, gateway software, and blockchain integration layers to enable secure communication and interoperability. Robust security measures, including encryption protocols and cryptographic algorithms, safeguard data integrity and privacy. Through meticulous testing, deployment, and documentation processes, this project delivers a reliable and future-ready smart lock solution poised to redefine access management paradigms in various settings, from residential homes to commercial establishments. Key Words: Solana, Smart locking systems, Security, Blockchain, Immutability

The Influence of Digital Payment Systems on Financial Performance: A Study of Maheshwari Sales and Services

In today's company environment, digital payment solutions are critical to improving customer experience and optimizing financial operations. This study uses a mixed-methods approach, combining quantitative and qualitative data to provide a thorough analysis. To assess customer and employee satisfaction and operational changes, Maheshwari Sales and Services conducts surveys and interviews. Financial information is reviewed to determine the influence on cash flow management. Preliminary data indicate that the use of digital payment systems has enhanced customer satisfaction due to the convenience and speed of transactions. Furthermore, these technologies have helped to improve cash flow management by eliminating the time lag between sales and fund availability. Additionally, operational efficiency has improved, with significant savings in transaction processing times and administrative overheads. The analysis reveals that Maheshwari Sales and Services' financial and operational success is heavily reliant on digital payment methods. The findings of this study can be used to influence strategic decisions about the organization's future integration and optimization of digital payment technologies.