Payment History Research Articles

Designing a machine learning-based lending model to enhance access to capital for small and medium enterprises

This paper presents the design of a machine learning-based lending model aimed at enhancing access to capital for Small and Medium Enterprises (SMEs). SMEs play a crucial role in driving economic growth, yet they often face significant barriers in securing funding due to traditional credit assessment methods that rely heavily on financial history and collateral. By leveraging machine learning (ML) algorithms, this proposed model incorporates diverse data sources, including financial statements, market trends, customer behavior, and non-traditional data such as social media activity and payment histories, to better assess creditworthiness. The model utilizes supervised learning techniques, such as decision trees, random forests, and neural networks, to analyze this diverse data and identify patterns that traditional models may overlook. Additionally, it integrates real-time data processing to continuously update credit profiles, allowing for more dynamic and responsive lending decisions. The primary aim is to improve the accuracy of risk assessment, reduce default rates, and ultimately facilitate more inclusive lending practices for SMEs. One of the core advantages of the ML-based model is its ability to offer personalized lending terms and products by identifying the unique characteristics and risk factors of each SME. This approach not only improves access to capital for underbanked businesses but also ensures that lenders can manage risk more effectively. The paper also discusses the potential ethical considerations, such as ensuring data privacy and avoiding biases in algorithmic decision-making, which are critical for the responsible implementation of such a system. In conclusion, this machine learning-based lending model presents an innovative solution to the long-standing challenges SMEs face in accessing capital. By harnessing the power of data analytics and advanced algorithms, it paves the way for more equitable and efficient lending processes, supporting the growth and sustainability of SMEs. Keywords: Machine Learning, Lending Model, Access To Capital, Small And Medium Enterprises, Risk Assessment, Creditworthiness, Financial Inclusion, Data Privacy, Algorithmic Decision-Making, Supervised Learning.

Biometric based payment system

The increasing need for secure and convenient payment methods has fueled the exploration of biometric authentication systems. This paper presents a Biometric Based Payment System designed to streamline transactions while prioritizing security. The system employs a fingerprint sensor (R307) to ensure robust user identification, complemented by a 4x4 keypad for versatile input and an I2C OLED display for clear feedback. At its core, the system leverages an ESP32 microcontroller and robust SHA-256 encryption to protect sensitive information during storage and transmission. Transaction data resides in a centralized MySQL database on an Apache server, and users manage payment history through a web interface. The system emphasizes security and ease of use, with the potential for future exploration of multi-factor authentication, offline capabilities, and blockchain integration to further enhance its robustness

Development of Android App on Scheduling Payments and Financial Management of Workers in Construction Industry

Abstract: A innovation centralized platform designed specifically for labour payment to efficiently manage project management, labour payments and generate detailed financial reports. Mobile computing offers helps to construction workers improve efficiency and minimize the paper works. However, the uptake of the technology is quite low in the industry, with little research on key constraint factors and the priority needs of the construction workforce. In recent year mobile applications have become increasingly popular years and is expected to continue like that as all the tech is moving towards mobile. However, unfortunately, in the face of accelerating user demand, businesses are not validating that their apps are safe, secure and they are more dragged by the speed-to-market pressure as well as the need to maintain a high level of user experience. As the application contains all the payment information tedious writing work can be avoided on site. Just set the payment in the application and are free to go. Extensive time and effort are spent on inspecting and documenting of payments. Managing large number of projects with various subcontractors will be difficult. If the hard copy is lost, entire data set cannot be taken back. In financial updates client also face same problem, to get clients according to their requirements. To bridge this gap and to develop better connection between client, engineers and subcontractors, we need a platform. Project cost based on labour payments and payments pending can be accessed easily. Maintain a history of project payments, weekly payments balance payments tracker

Blockchain for real estate provenance: an infrastructural step toward secure transactions in real estate E-Business

In the rapidly evolving digital era, the growing trend of conducting real estate e-business transactions through online platforms has led to escalated challenges in ensuring transactional security and trust. These challenges underscore the importance of balancing transparency with data privacy and enhancing accountability in this field. As an extension of our previously published work (Abualhamayl AJ, Almalki MA, Al-Doghman F, Alyoubi AA, Hussain FK (2023) Towards fractional NFTs for joint ownership and provenance in real estate. In: 2023 IEEE international conference on e-business engineering (ICEBE), p. 143–8. 10.1109/ICEBE59045.2023.00022.), this paper introduces the Global Real Estate Platform (GREP), a novel hybrid blockchain system that utilizes real estate provenance to establish a secure and trustworthy environment for real estate e-business, specifically focusing on two key challenges: ensuring data authenticity and effectively managing access rights. Integral to GREP's design is the involvement of government entities, which is essential for maintaining the required balance between transparency, privacy, and high levels of accountability. This proposed framework is explained conceptually and demonstrated practically, offering an innovative perspective on the integration of hybrid blockchain technology in the real estate system. Furthermore, our research encompasses a detailed implementation, using various tools, and an in-depth examination of three use cases. This combined analysis effectively demonstrates GREP's efficacy in addressing the targeted challenges in the field. While acknowledging the system's limitations, including challenges in user adoption and performance variability under different network conditions, our findings open new avenues for further exploration, such as landlords' payment histories and utility bills, and using blockchain as a secondary user identifier. These features collectively highlight the transformative potential of blockchain technology in real estate e-business.

Decoding CIBIL: Understanding the Structure and Strategies for Improvement

This research paper delves into the intricate dynamics of credit scoring systems, particularly focusing on understanding the structure of CIBIL scores and delineating strategies for improving creditworthiness. Drawing upon theoretical frameworks from financial economics and regulatory economics, the study elucidates key factors influencing credit scores, including payment history, credit utilization, credit type, and duration. Through a mixed-methods approach encompassing secondary data analysis from the official websites of TransUnion CIBIL India and Bajaj Finance Limited, as well as qualitative exploration through thematic analysis, the research uncovers actionable insights for individuals seeking to enhance their credit profiles.By bridging theoretical insights with empirical findings, this study contributes to the literature on credit management and equips individuals with knowledge essential for navigating the complexities of credit assessment and improving financial resilience

Islamic Economic Analysis Reviewing Top Up Transparency Practices and Effective Flat Installment Systems in Banking

The background of the writing is because there are customers who are stuck with the facilities provided by the bank, namely top up (addition of loans) and Effective Flat Installments which it is not known what exactly the two facilities are. by the bank first, the customer will receive a new schedule and a new loan limit. Of course, the bank will choose the criteria for customers who will be given top up facilities, namely the history of installment payments is relatively smooth, this is precisely the root of the problem that many customers experience who do not understand about top ups and an effective flat installment system. Lack of transparency about what will be done by the customer in the future imposed by the bank to the customer so that the customer bears a lot of losses caused by the top up and the effective flat installment system. This research is a qualitative research with an evaluative-normative approach. The purpose of this study was to determine the extent to which the transparency applied by the banking sector for top-up loans, as well as the application of the flat installment system was effectively implemented. application of the principle of transparency in implementing Bank Indonesia regulations and how the practice of transparency is viewed from the Islamic economy.

Perancangan Aplikasi Mobile Sistem Informasi Akademik Mahasiswa Sebagai Salah Satu Tahapan Metode DevOps

The student service information system is important for processing information at an educational institution. IST AKPRIND campus has implemented information services using mobile devices. In student information services, there is some information about lectures, such as study result cards, course schedules, student profiles, and student attendance. However, there are still areas for improvement in application, such as the lack of academic features in the service. The solutions in this study in the form of additions, improvements, and updates include adding a dynamic announcement feature, improving the payment history feature, improving the scan feature on self-presence, adding features to display the cumulative assessment index, semester credit units taken, active student status and updating the display design. The DevOps approach is used by the system development method because it can reduce the time between software creation and operation without sacrificing software quality. This study aims to apply the DevOps method design phase to the development of student service applications. The following stage of development is built upon the outcomes of this design.

DIGITAL TRANSFORMATION IN THE BANKING BUSINESS

In the article examines the theoretical essence of digital transformation and digitalization of banks. The characteristic features of the implementation of digital services in the banking system are considered. The prerequisites for accelerating the development of digitalization of the banking business have been determined. The main positive consequences of the digitalization of the banking system (quick execution of payments and transfers, receiving information about account status and payment history 24/7; saving time visiting bank branches, access to information about credit or deposit accounts, etc.) and obstacles on its way are highlighted development (low digital literacy of the population, financial inability of some consumers of services and products to purchase the necessary gadgets for remote resource management). 
 The characteristics of digital stable convenient banking services (blockchain, crowdfunding, cloud banking, open banking, sharing) are considered in detail. It has been established that the new financial and digital paradigm is already an integral part of the rapidly changing environment and a tool for meeting the demanding needs of both consumers of banking services and banks themselves. The new financial and digital paradigm is already an integral part of the rapidly changing environment and an important tool for meeting the needs of both consumers of banking services and banks themselves.

Web-Based Student Payment Administration Information System Using The Waterfall Method

This research aims to develop an Information System that can assist the school admin in providing the validation process for tuition payments, speed of access, and completeness in providing information. This research aims to overcome administrative challenges that often occur in schools, such as errors in recording payments, late payments, and the difficulty of tracking payment history to save time and effort previously spent processing payments manually. The research method used is the Waterfall method. This application will make it easier for the finance department to record student tuition payments method was chosen because of its deep capabilities and describes a flow or stages that run like a waterfall from one stage to the next. This approach relies heavily on good initial planning because changes made in the early stages may be difficult or expensive to implement in later stages. Based on the results of system design and black box testing, it can run well, and user responses also provide very good responses, with 94% of respondents giving very good responses and 0% saying good and quite good. Based on these findings is hoped that it can be used more efficiently and also ensure data security and can store the results of the data that has been processed.

The value of utility payment history in predicting first-time homelessness.

Homelessness is a costly and traumatic condition that affects hundreds of thousands of people each year in the U.S. alone. Most homeless programs focus on assisting people experiencing homelessness, but research has shown that predicting and preventing homelessness can be a more cost-effective solution. Of the few studies focused on predicting homelessness, most focus on people already seeking assistance; however, these methods necessarily cannot identify those not actively seeking assistance. Providing aid before conditions become dire may better prevent homelessness. Few methods exist to predict homelessness on the general population, and these methods use health and criminal history information, much of which may not be available or timely. We hypothesize that recent financial health information based on utility payment history is useful in predicting homelessness. In particular, we demonstrate the value of utility customer billing records to predict homelessness using logistic regression models based on this data. The performance of these models is comparable to other studies, suggesting such an approach could be productionalized due to the ubiquity and timeliness of this type of data. Our results suggest that utility billing records would have value for screening a broad section of the general population to identify those at risk of homelessness.

Newly subscribed! Effects of e-mail newsletters on news-reading habit and subscriber retention during onboarding: evidence from clickstream and subscription data

ABSTRACT Despite the increasing popularity of e-mail newsletters, there have been few studies that examine the effects of signing up for e-mail newsletters among news subscribers, especially its role in enhancing news reading behaviors and subscriber retention for new subscribers. This study investigates how e-mail newsletter sign-ups influence news-reading habits and subscriber retention during onboarding. Using single-source data that combine clickstream data from news sites, e-mail newsletter sign-up records, and payment histories of 16,284 new digital news subscribers across four major markets in the U.S. this study finds that signing up for e-mail newsletters improves news reading habits and digital news subscription duration, with an additive effect of the number of e-mail newsletters signed up for. Regarding the retention mechanism, signing up for e-mail newsletters contributes to retention by helping new subscribers read more frequently and intensely (measures of reading habit), which in turn positively affects subscriber retention.

Factors Affecting the Bidding Decision in Sustainable Construction

The environmental harms that the construction industry has caused are significantly detrimental and apparent. These harms include the emittance of a substantial amount of carbon dioxide and inducing ground and water contamination. Fortunately, these adverse environmental impacts can be minimized and counteracted by carrying out sustainable construction projects. As sustainable construction projects gain more popularity and are increasingly in demand, it is crucial for those who will execute these projects to be knowledgeable about the nature of sustainable construction projects and be able to determine whether to bid for these projects. The bidding decision is one of the critical decisions that contractors have to make due to the complexity and uncertainty surrounding this choice. Given the above challenge, this research aims to identify the most significant factors that affect the bidding decision in sustainable construction. The methodology adopted in this research is a mix of qualitative and quantitative analysis. An extensive literature review was first conducted to determine the bidding decision factors. After that, a survey was distributed to United Arab Emirates (UAE) construction professionals, where they were asked to rank the significance of the 40 extracted factors. The weighted average approach was then used to prioritize the most significant factors of the bidding decision in sustainable construction. The results showed that the top 10 ranking factors were as follows: client’s financial capabilities, client’s payment history, client’s reputation, project risks, contractor’s financial capabilities, project complexity, experience in similar projects, project type, contractor’s access to technologies required to execute sustainable projects, and material availability. The findings of this research can benefit contractors and subcontractors by increasing their understanding of the major factors affecting the bidding decision in sustainable construction. Contractors armed with such invaluable information will be better equipped to reach more effective better bidding decisions.

Design a Web-based Education Development Contribution Payment Application at SDIT Tahfidz Bintangku

Improving services to facilitate the management and monitoring of billing and payment of SPP (Education Development Contribution) in educational institutions must get serious attention because the quality of educational institutions is greatly influenced by the availability of adequate payment management. The research method used in application development uses the waterfall method. The application developed is web-based using the Laravel 9 framework with a combination of design with boostrap so that it is more responsive and uses the Mysql database. The results of the developed application are able to assist the treasurer and student guardians in managing, provide convenience for students and parents in making payments online, reduce the need to queue at physical payment counters, save time and energy, make it easier for treasurers and parents to track payment history, can verify transactions that have been made and ensure that no payment transactions are left behind, make it easier for schools to manage financial recording processes and payment processing to be more organized and controlled quickly.

Markov Analysis in Commitment Prediction of Insurance Customer to Minimizing Customer Attrition

Trust and commitment are the important things for insurance customer to continue doing business with insurance company. Customer commitment can be seen from payment history, whether customer doing payment on time or late. This research using Markov Analysis to predict customer commitment using data of insurance premium payment history from each period, identify customer profile, and analyze the type of insurance purchased. This research shows there are three steps of customer who vulnerable to terminate the insurance contract with company. Insurance company could use the result to minimize customer attrition level with several ways like review the applicant profile before make insurance contract, recommends which type of insurance will fit to applicant, and monitor customer who late to do premium payment for two consecutive periods. This research also propose Customer Relationship Management (CRM) strategy to handle customer who match with the three steps of terminating the insurance contract with providing special treatment and service to prevent discontinuance of insurance contract.

Analisa Penerapan Metode Naïve Bayes Dalam Memprediksi Kelayakan Calon Nasabah Dalam Melakukan Pinjaman

Financing through loans is common in the financial world, but the loan approval process requires careful assessment to minimize credit risk that may arise. In this study, we propose the application of the Naïve Bayes method as a tool to predict the eligibility of prospective customers in making loans. This research uses historical datasets from banks that include credit information, payment history, and customer profiles. The analysis process begins with data pre-processing to clean and address missing or incomplete data. Next, the extraction of relevant features and selection of variables are carried out to build a prediction model. The Naïve Bayes method was chosen because of its simple and fast nature in classifying data. This model makes use of the assumption of feature independence, which is useful when feature dimensions are high. In the training phase, the Naïve Bayes model will learn from historical datasets to recognize good and bad customer eligibility patterns. The results of this analysis show that the Naïve Bayes method has succeeded in predicting the eligibility of prospective customers with a satisfactory level of accuracy. In addition, the model is able to identify key factors that affect loan eligibility, such as credit history, income, and financial dependents. This study contributes to finance by presenting predictive tools that can help financial institutions make more informed and efficient decisions regarding loan approvals. However, we also acknowledge that the Naïve Bayes method has limitations, such as the assumption of feature independence, which must be considered in the interpretation of prediction results.

Tax Management System for Local Government Unit with SMS Notification

This study aimed to design and develop a Tax Management System for Local Government Unit with SMS Notification and evaluate the degree of acceptability and performance efficiency in the perception of the respondents. It is a computer-based information system aimed at providing information of the tax payers and their payment history in fast and easy manner. Developmental and descriptive research design was employed in this study. A system prototype was developed to implement the core functionalities as required by the target users to meet design specification. This study was conducted at the Treasurer Office in the Municipality of Estancia, Iloilo with a total of 50 respondents. When respondents were asked as to the degree of acceptability of the developed system in terms of security, it yielded a response of strongly agree. In terms of confidentiality, the developed system was described as strongly agree. The result showed that the performance efficiency of the developed system in terms of time behavior was also described as strongly agree. In terms of responsiveness, the developed system was also described as strongly agree. From the results stated above, this simply showed that the respondents were very much contented with the security, confidentiality, and efficiency of the developed system.

ОПЫТ ОРГАНИЗАЦИИ СИСТЕМЫ ФИНАНСИРОВАНИЯ «ДИВИДЕНДНЫХ АРИСТОКРАТОВ» ПРЕДПРИЯТИЯ НЕМАТЕРИАЛЬНОЙ СФЕРЫ

The article discusses the experience of large corporations related to “dividend aristocrats”, namely, those with a long history of annual dividend payments, stable financial statements, and capable of being potential investors in the process of reproducing the Russian economy. The presented study examines the experience of organizing a financing system on the example of an enterprise in the non-material sphere, a representative of the telecommunications industry, which is a “dividend aristocrat” – PAO MTS. In the course of the study of the company, its characteristics are considered, the structure of its capital and the main financial indicators are analyzed. Based on the results of the study, a conclusion is made about the significant contribution of “dividend aristocrats” to replenishing the budget, as well as the need to concentrate resources within our country for the development of our economy and industry in the face of an unprecedented number of sanctions imposed on our country.

A robust framework for handling health care information based on machine learning and big data engineering techniques

ABSTRACT Confidentiality and security breaches remain significant concerns for electronic healthcare systems even though many relevant rules, principles, and compliance standards are in place to protect health information. It is now essential to use strategies revolving around big data to enhance the dependability of healthcare delivery due to the ever-increasing number of data generated within the healthcare sector. Even though big data processing methods and platforms have been incorporated into the data management designs for medical systems, these designs have trouble addressing urgent situations. Today, it is difficult to predict how big data and ML will affect the healthcare sectors. As a result, a clinical healthcare data warehouse environment utilizing big data analytics and ML is provided in this analysis. Quick digital access to all types of vital data, including patient histories, scan records, insurance claims, and payment history, is guaranteed by healthcare data warehouse systems. This clinical healthcare data warehouse environment can improve an individual's quality of care and monitor the patient's health status in real-time by using ML algorithms and Big data analytics. The effectiveness of the ML technique's performance is measured in terms of accuracy, specificity, sensitivity, precision, recall and Receiver Operating Characteristics (RoC).

Sistem Informasi Pembayaran Tagihan Layanan Internet Berbasis Website di PT Indonesia Comnets Plus

Internet technology is currently developing rapidly, the need for internet in the community in the current era of the COVID-19 pandemic is increasing because studying and working can be done at home. By utilizing technology, processing customer bill payment data will be faster because of the ease of use. To support the implementation of this inseparable development of Information and Technology, a website-based internet bill payment system was created with the aim of making it easier for customers to make payments and check payment history and provide convenience for the field of collection in checking accounts receivable data so that they can be followed up in accordance with standard operating procedures. applicable. So that customers feel comfortable because they don't need to be constantly reminded regarding missed payments. The design of the internet service bill payment system is described by Data Flow Diagrams (DFD) and Entity Relationship Diagrams (ERD). The design of the system prototype uses the PHP programming language and the PostgreSQL database. From this study, it was found that the website-based internet bill payment system was running well. In appearance, the website is responsive to many browsers. Meanwhile, in terms of functionality, the system can perform the functions of each feature.

A brief history of cross-border payments

This paper discusses key moments in the evolution of cross-border payments, from the early beginnings of money through coins, notes and bills of exchange, all the way up to the modern era, to provide a brief history of the last 4,000 years of cross-border payments.