Financial Applications Research Articles

Determining factors in the adoption of fintech of sharia in Indonesia: analysis of the effect of utaut2, Es-qual, and religiosity

This research examines the antecedents of actional desires towards using Islamic financial application among Indonesian customers. The objectives of the study empirically tested the expanded unified theory of acceptance and use of application (UTAUT2), ES-QUAL and religiosity as independent variables to explain the adoption of Islamic financial application in Indonesia. The method was quantitative. The 200 data are analyzed using the Partial least squares (PLS). The research results show that Effort Expectancy (EE), Social Influence (SI), Hedonic Motivation (HM), Esqual (ESQ), and Religiosity (RE) have a positive effect on Desire to Use Islamic Financial Application (IB). Furthermore, the Desire to Use Islamic Financial Application (IB) positively affects the Use Action of Islamic Financial Application (UB). In addition, only gender (GE) can weaken the influence of hedonic motivation and habit on the Desire to Use Islamic financial application. The influence actional desires to use Islamic financial application because of the lack of research in this domain in Indonesia, especially considering the context of religiosity and combining the concepts of UTAUT2 and ESQUAL. This research contributes to the service quality literature by identifying E-SQ and confirming its effectiveness in FinTech adoption. This can also enhance to the development of understanding financial concepts.

Harnessing machine learning for enhanced quantitative financial strategies: Applications and case studies

Machine learning algorithms have long been an essential tool for quantitative finance, as they play an important role in the asset pricing, portfolio optimisation and financial risk management. This work discusses how to apply Random Forest, Support Vector Machine (SVM), and Neural Networks to further develop and enhance the quantitative investment research. With automatic feature selection, reconstruction of high-dimensional data and resist against over-fitting, Random Forest has been an efficient ensemble approach with remarkable prediction performance. For this reason, Random Forest is leveraged for the stock price prediction. SVM, particularly known for its robustness in high-dimensional classification task, has a non-linear optimisation ability that can be employed to capture the inherent non-linear dependencies in options prices. Neural Networks, as a learning approach capable of discovering complex relationships, is employed for the portfolio optimisation, with a promise for further improving the risk-adjusted portfolio return. The work is conducted through practical case studies to simulate how Random Forest, SVM and Neural Networks enable us to further improve the financial performance, and to illustrate its advantage, disadvantage and practical application in quantitative finance.

Security design: A review

Security design, which broadly speaking deals with the issue of designing optimal contractual mechanisms for overcoming various frictions between agents, is the subject of an extensive literature. This paper presents a review of recent work on security design and is organized around the applications of security design in various fields of finance starting with classic corporate finance applications such as capital structure and corporate governance, financial intermediation applications such as securitization and contingent capital, the interaction of market and security design, as well as emerging applications such as fintech, sustainable finance and healthcare finance. Future research is also discussed.

The Role of Financial Data Processing and Application in Strengthening National Financial Supervision

This study focuses on the role of financial data processing and application in strengthening national financial supervision. It begins by discussing the background and significance, purpose and methods of studying this topic in the digital age. The theoretical foundations of financial data processing and application are introduced in detail, including the concept and characteristics of financial data, related theories of data processing and application, and the objectives and principles of financial supervision. The current status and challenges of financial data utilization in national financial supervision are analyzed. The multifaceted role of financial data processing and application in strengthening financial supervision is explored in depth, such as improving the transparency of fiscal fund use, accurately identifying problems and risks, optimizing budget management, and improving the performance evaluation system. Strategies for using financial data analysis to strengthen budget management and performance evaluation are proposed, including establishing and improving financial data collection and management systems, using data analysis tools for budget management, and building data analysis models for performance evaluation. The importance of financial data in maintaining national financial security and stability is emphasized, including preventing financial risks and ensuring sustainable fiscal development. Experiences, lessons, and insights are summarized and enlightened through the analysis of successful and problematic cases. Finally, the study is concluded with an outlook on the future application of financial data in financial supervision, including aspects such as technological development, system construction, talent cultivation, and data sharing.

Extrapolation and Generative Algorithms for Three Applications in Finance

Extrapolation and Generative Algorithms for Three Applications in Finance

API integration in FinTech: Challenges and best practices

API integration is a cornerstone of innovation in the FinTech sector, enabling seamless connectivity between disparate financial systems, enhancing service delivery, and fostering the development of new financial products. This review explores the challenges and best practices associated with API integration in FinTech, emphasizing the importance of effective strategies for overcoming integration obstacles and achieving successful outcomes. APIs (Application Programming Interfaces) facilitate the exchange of data and functionality between financial applications, such as payment systems, banking platforms, and financial data aggregators. However, integrating these APIs presents several challenges, including compatibility issues, security concerns, and regulatory compliance. Ensuring that APIs are compatible with various systems and standards is essential for smooth integration. Security is another critical concern, as financial data is highly sensitive and requires robust protection against breaches and unauthorized access. Compliance with financial regulations, such as GDPR and PSD2, adds an additional layer of complexity to API integration. To address these challenges, best practices in API integration include adopting standardized protocols and frameworks to enhance compatibility and interoperability. Implementing comprehensive security measures, such as encryption, authentication, and authorization, is crucial to safeguarding data and maintaining trust. Additionally, establishing clear documentation and version control practices helps ensure that APIs are easy to use and integrate while accommodating future updates and changes. Effective API management also involves continuous monitoring and testing to identify and resolve issues promptly. Leveraging API management platforms can streamline the integration process by providing tools for monitoring performance, managing security, and facilitating communication between systems. Collaboration between development teams, IT departments, and business stakeholders is essential for aligning technical and business requirements and ensuring that integration goals are met. In conclusion, while API integration in FinTech presents various challenges, adhering to best practices and leveraging appropriate tools can facilitate successful integration. By addressing compatibility, security, and compliance issues, FinTech organizations can enhance their service offerings, drive innovation, and improve operational efficiency. Keywords: API Integration, Fintech, Compatibility, Security, Regulatory Compliance, Standardized Protocols, Encryption, Authentication, API Management, Performance Monitoring.

An optimal estimation approach in stratified random sampling utilizing two auxiliary attributes with application in agricultural, demography, finance, and education sectors

In the contemporary era of information technology, copious amounts of data are ubiquitous, generated across various sectors on a daily basis. Analyzing every unit of data is impractical due to constraints such as limited resources in terms of time, labor, and cost. In such scenarios, survey sampling becomes a recommended approach for extracting information about population parameters. The primary goal of this study is to devise an estimation method for acquiring information about population parameters. We propose an optimal estimator for an improved estimation of the population mean in stratified random sampling by leveraging the information from two auxiliary attributes. The proposed estimator's bias, mean squared error (MSE), and minimum mean squared error are determined up to the first-order approximation. It is demonstrated that, under the derived conditions, the proposed estimator theoretically outperforms existing estimators. Four population are utilized to evaluate both the performance and applicability of the proposed estimator. The percentage relative efficiency (PRE) of proposed estimator for all the populations is 178.389, 142.881, 181.383, and 152.679 respectively. The suggested estimator superior to existing estimators, as demonstrated by the numerical examples.

PENGARUH PENERAPAN SISTEM INFORMASI AKUNTANSI DAN LITERASI KEUANGAN TERHADAP KINERJA UMKM

This research aims to examine the influence of accounting information system and financial literacy have an effect on the performance of MSME users of OASSE the point of sale financial application. This research uses sensus technique with quantitative approach method. The data collection method is primary data obtained from distributing questionnaires to 45 respondents who are MSME owners that use OASSE the point of sale financial application. The data analysis technique used multiple linear regression analysis with SPSS program. The results showed that (1) Accounting information system has a positife effect on the performance of MSME users of OASSE the point of sale financial application (2) Financila literacy has a positife effect on on the performance of MSME users of OASSE the point of sale financial application.

On the pricing of vulnerable Parisian options

Parisian options, serving as substitutes for barrier options, are frequently embedded in complex financial derivatives. Despite the considerable mathematical challenges in pricing, their significant applications in finance and insurance have generated extensive studies in the literature. However, the impact of counterparty risk has not been taken into account so far. To address this gap, we develop a closed-form pricing framework for vulnerable Parisian options. Utilizing the Laplace transform and measure-change technique, we derive closed-form pricing formulas of Parisian options incorporating counterparty credit risk. Finally, we conduct numerical analyses to verify our pricing formulas’ accuracy and efficiency.

Gamified Investing: An Analysis of Investment Behaviour of Retail Investors Using Financial Applications

Gamified Investing: An Analysis of Investment Behaviour of Retail Investors Using Financial Applications

REVOLUTIONIZING USER EXPERIENCE: ARCHITECTURAL INNOVATIONS IN OVO PAYMENT APPLICATION

In the era of digital transformation, mobile-based payment applications have become an important element in everyday life, changing the way transactions and managing finances. Online payment applications provide significant benefits by making financial transactions easier without cash, providing flexibility in choosing brands, and supporting the progress of fintech businesses and startups in the digital financial sector. Lippo Group, through OVO, presents innovation in electronic money payment systems. OVO's rapid growth lies not only in the ease of financial transactions, but also in its mobile application which is designed to provide a better user experience. This research analyzes architectural innovation in the OVO mobile application, aiming to revolutionize the user experience and increase OVO's competitiveness in the mobile payments industry. Using descriptive qualitative methods, this research utilizes user cards, storyboards, and customer journeys to analyze the implementation of Microservices Architecture and Load Balancing. The results show that this innovation provides significant benefits, improving the system's scalability, reliability and maintenance efficiency. Using Load Balancing is effective in solving balance problems and customer service response. This research provides in-depth insight into the evolution of financial applications in Indonesia.

User Acceptance of Blockchain Technology in Financial Applications: Information Security, Technology Awareness and Privacy Aspects

Blockchain technology is now an advanced and innovative database technology and the attributes of blockchains are apparent in a variety of industries, especially in the financial industry. One of the most famous blockchain use cases, cryptocurrencies, has provoked much interest in social network users and customers. According to CoinMarketCap’s information, the global crypto market capitalization has reached around USD 2.37 T and there are around 9975 different cryptocurrencies available in the market. Despite the fact that academia and industry have paid much attention towards the blockchain direction, there is not much research on the factors that influence customer acceptability. This paper studies blockchains from a different angle, probing the factors prompting customers to use financial applications that utilize blockchain technology. We established the model and sorted the individual factors of perceived information security, technology awareness and privacy and found that users’ acceptance is significantly affected by information security and technology awareness, while privacy does not significantly influence users. According to the findings, we provide useful insights for application developers, conclude by presenting the limitations of the research and provide guidelines for future research.

Challenges encountered by SMMEs in accessing bank credit: a case of Vhembe District Municipality

Policymakers and scholars universally accept and recognize the influence of small, macro, and medium enterprises (SMMEs) on stimulating economic growth and job creation. To succeed and prosper, SMMEs need to establish a sound financial management function; therefore, it is vital to investigate the financial challenges these firms are experiencing. The objective of this paper was, to investigate possible challenges that SMMEs experience when applying for credit from banks. The study sought to answer the main research question - ‘What challenges are encountered by SMMEs when applying for credit from banks? The study adopted a qualitative research methodology. The population used in this research was derived from SMMEs and banking officials in the Vhembe District Municipality area. Stratified random sampling was used to select a sample of 10 research participants. An interview guide was used to gather data from the participants; the data was analyzed using Atlas.ti. The results indicated that most SMMEs in the Vhembe district are not adequately supported, especially in the areas of financial resources, as well as in financial literacy skills and expertise. Specifically, this study identified that the credit application challenges faced by SMMEs are related to - lack of collateral security, lack of financial application education, complex bank credit access regulations, non-satisfaction of banks’ qualifying criteria, as well as stringent credit system, and documentation requirements.

Green Finance as an Innovative Solution for Transforming the Tourism Industry: A Bibliometric Study

Green finance has an important role in supporting sustainable tourism development while still considering economic, social, and environmental impacts. The urgency of this research lies in green finance which is an innovative solution in funding environmentally friendly projects so that it becomes a great opportunity to encourage the transformation of the tourism industry towards sustainable practices. This research aims to map trends and green finance research networks that play a role in supporting sustainable tourism development. Data analysis was carried out using bibliometric methods sourced from the Scopus database. The results obtained were in the form of a dataset consisting of 654 documents and processed using Rstudio and Biblioshiny. The results show that there has been a significant increase in publications in 2020-2023. It can also be seen that there is a connection between the application of green finance in realizing sustainable development. This is an opportunity to apply to the tourism industry. Apart from that, it was also found that there was a concentration on this research topic in China. It is hoped that the findings of this research will produce a better understanding of trends and research networks in green finance and can contribute to the development of appropriate policies and strategies for sustainable tourism development.

Research on the Current Situation and Problems of the Use of Digital Inclusive Finance

This study aims to investigate the use of digital inclusive finance among college students in Guangzhou and its influencing factors. Through the questionnaire survey and data analysis, the popularity, willingness to use, and barriers to the use of digital inclusive finance among college students are found, and the reasons behind them are analysed and discussed, which provide references and suggestions for promoting the application of digital inclusive finance among the college student population.

An Example of Using Advanced Excel Applications Within the Scope of Financial Mathematics Calculations: Modelling of Calculations Related to Annuities in Microsoft Excel Program

Financial mathematics applications, form the mathematical basis for rational financial decisions within the scope of financial management. Carrying out financial management in line with the scientific rules is of vital importance for businesses to sustain their existence and carry out their activities effectively and efficiently. In this context, the ability to carry out financial management rationally is only based on the correct determination of the mathematical datas (etc. time value of money) that forms the basis for decisions. The use of technology in this area is very important and technology level in this area has evolved from financial calculators to computer programs and MS. Excel program is perhaps the most important application tool in this field according to its mathematical calculation capacity and capability. In this regard, the study reveals how to perform complex calculations regarding the present and future values of different annuity types in Excel. The calculation of all variables related to annuity calculations and the mathematical relationships between variables are discussed separately according to different annuity types is examined with a model which developed in Excel program within the scope of the purpose of the study. The study will provide guidance to academics related to the field and professionals working in the field of financial management by combining theoretical knowledge and practical applications.

VALIDATION OF THE PSYCHOSOCIAL BACKGROUND OF A FINANCIAL MANAGEMENT APP PROTOTYPE FOR STREET VENDORS.

This study aimed to validate the psychosocial antecedents related to the intention to use and the actual use of a financial management application prototype designed for market vendors. To achieve this objective, the Unified Theory of Acceptance and Use of Technology (UTAUT) was used as the theoretical framework. The prototype allowed users to create cash flows instantly, recording income and expenses categorized by date, category, and amount. For validation, a survey was conducted, which was pre-tested using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. The results indicated that the constructs did not show sufficient discrimination, with overlap among them, making it impossible to continue the research and highlighting the importance of pre-tests in data validation. This study suggests that the adoption of technology in financial management by market vendors requires more attention and recommends that future research consider the cross-cultural adaptation of data collection instruments for this specific audience.

The Role of FPGAs in Modern Option Pricing Techniques: A Survey

In financial computation, Field Programmable Gate Arrays (FPGAs) have emerged as a transformative technology, particularly in the domain of option pricing. This study presents the impact of Field Programmable Gate Arrays (FPGAs) on computational methods in finance, with an emphasis on option pricing. Our review examined 99 selected studies from an initial pool of 131, revealing how FPGAs substantially enhance both the speed and energy efficiency of various financial models, particularly Black–Scholes and Monte Carlo simulations. Notably, the performance gains—ranging from 270- to 5400-times faster than conventional CPU implementations—are highly dependent on the specific option pricing model employed. These findings illustrate FPGAs’ capability to efficiently process complex financial computations while consuming less energy. Despite these benefits, this paper highlights persistent challenges in FPGA design optimization and programming complexity. This study not only emphasises the potential of FPGAs to further innovate financial computing but also outlines the critical areas for future research to overcome existing barriers and fully leverage FPGA technology in future financial applications.

Last passage times for generalized drawdown processes with applications

In recent years, there has been a significant amount of work dedicated to the study of the generalized drawdown process with its extensive applications in insurance and finance. While existing studies have primarily focused on analyzing the associated first passage times, which signal early warnings, the investigation of last passage times should not be overlooked. Last passage times involve knowledge of the future and can thus offer additional insights. This paper aims to fill this gap in the literature by studying the last passage times for the generalized drawdown process with an independent exponential killing and discussing their applications to insurance risk. Our analysis focuses on the Lévy insurance risk processes, for which we derive the Laplace transforms for these random times. Additionally, we obtain new results on the joint distribution of the duration of the drawdown and the surplus level at killing. As applications, we implement our results in the loss-carry-forward tax and dividend models and investigate the valuation of an European digital drawdown option. Detailed numerical examples are presented for illustrative purposes.

Analysis of The Effectiveness of the BukuWarung Application as a Financial Management Tool for MSMEs

Effective financial management is crucial for business success, especially amid the Industry 5.0 revolution, which has transformed production, management, and human-machine interactions. This era has introduced advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), robotics, and additive manufacturing into production environments, leading to significant changes in accounting practices. In Indonesia, SMEs, traditionally reliant on manual record-keeping, are encouraged to adopt digital applications to remain current. Consequently, various financial management applications have emerged, including BukuWarung, designed to streamline transaction recording and enhance financial management efficiency. This research aims to assess the effectiveness of BukuWarung as a financial management tool for SMEs. Utilizing a qualitative and descriptive approach, the study involved SMEs at SWK Lidah Wetan that use BukuWarung. Primary data were gathered through observation, interviews, and field documentation. Findings reveal that BukuWarung significantly aids SME financial management, particularly in billing, bookkeeping, cashier operations, inventory management, and transaction scheduling. Future research should explore the utilization of specific features within BukuWarung and their effects on SME financial management.