Financial Services Research Articles

The Role of AI in Data Engineering and Integration in Cloud Computing

This article presents a comprehensive analysis of the transformative role of Artificial Intelligence (AI) in revolutionizing data engineering and integration processes within cloud computing environments. The article examines the implementation of AI-driven solutions across multiple dimensions, including automated pipeline generation, intelligent schema matching, anomaly detection, and real-time data integration. Through a mixed-methods approach incorporating both quantitative and qualitative analyses, the article demonstrates significant improvements in data processing efficiency, with organizations achieving up to 67% reduction in processing time and 89% enhancement in accuracy. The article encompasses case studies from financial services, healthcare, and e-commerce sectors, providing concrete evidence of practical applications and scalability. Key findings reveal that AI-powered systems substantially outperform traditional approaches in cost efficiency, scalability, and data quality management, while simultaneously reducing operational overhead. The article also addresses implementation challenges, including legacy system integration and initial deployment complexities, offering strategic insights for organizations pursuing AI integration in their data engineering workflows. These article contribute to the broader understanding of how AI technologies can be effectively leveraged to address the growing challenges of data management in cloud computing environments, while providing a framework for future developments in this rapidly evolving field.

The Influence of Foundational Bases of Internet-Only Banks on Consumer Attitudes and Usage Intentions: Focused on the Moderating Effect of Involvement, Usage Purpose, and Construal Level

This study investigates how the foundational bases of internet-only banks shape consumer attitudes and intentions to use these services. Specifically, it examines how consumer attitudes and usage intentions toward internet-only banks are moderated by factors such as involvement, purpose of use, and construal level. This research contrasts consumer attitudes based on the foundational bases of internet-only banks (ICT-driven vs. bank-driven) and analyzes whether involvement (high vs. low) and usage purpose (deposit vs. loan) have moderating effects on these attitudes. Furthermore, it explores whether construal level (low vs. high) moderates usage intentions depending on the bank’s foundational base (ICT-driven vs. bank-driven). For empirical analysis, two types of surveys representing ICT-driven and bank-driven internet-only banks were administered to a sample of 360 participants, including university students, graduate students, and the general public in Daegu and Gyeongbuk. Key Findings: 1) Consumer attitudes were significantly more favorable toward ICT-driven internet-only banks compared to bank-driven counterparts. 2) High involvement correlated with more positive attitudes toward ICT-driven internet-only banks, whereas low involvement correlated with more favorable attitudes toward bank-driven banks. 3) For usage purpose, consumers with a loan-oriented purpose demonstrated a stronger positive attitude toward ICT-driven internet-only banks, while, counter to the hypothesis, deposit-oriented consumers also showed a preference for ICT-driven banks. 4) Regarding construal level, lower construal levels were associated with stronger usage intentions for ICT-driven internet-only banks. Unexpectedly, high construal levels also displayed elevated usage intentions for ICT-driven models. In conclusion, initial consumer responses to internet-only banks, which incorporate ICT as an enabling technology within essential financial services, appear to prioritize convenience and procedural efficiency. This study thus offers theoretical insights suggesting that both internet-only and traditional banks should address these consumer demands by enhancing service speed and simplicity.

Enhancing Fraud Detection Systems through Advanced Data Engineering Techniques

Aims: Fraud remains a persistent issue in various industries, particularly in finance, e-commerce, and healthcare, where traditional rule-based systems have struggled to keep pace with the evolving complexity of fraudulent activities. This study aims to develop an enhanced fraud detection framework by addressing the limitations of traditional rule-based systems, particularly in industries where sophisticated fraud schemes prevail. Study Design: The research utilizes advanced data engineering techniques, including big data analytics, machine learning, and real-time processing, to improve the accuracy and efficiency of fraud detection systems. Place and Duration of Study: The study was conducted over two years across industries with high fraud susceptibility, including financial services, e-commerce platforms, and healthcare organizations. Methodology: The framework integrates various data sources, including transaction logs, user behavior, and external fraud indicators. These datasets were pre-processed through data cleaning, feature engineering, and integration. Supervised and unsupervised machine learning models, such as Random Forest and Gradient Boosting, were applied to detect fraud patterns. Real-time data processing enabled immediate detection and response. The system continuously learned from historical data, adapting to new fraud tactics and improving detection over time. Results: The proposed framework demonstrated a significant improvement in fraud detection accuracy, with machine learning models achieving over 90% accuracy rates. There was also a 30% reduction in false positives compared to traditional methods, and detection times were shortened by 40%, enabling faster identification and mitigation of emerging fraud schemes. Conclusion: This study concludes that integrating advanced data engineering techniques with machine learning significantly enhances fraud detection systems' accuracy, scalability, and adaptability. While promising, further improvements are needed, particularly in addressing the evolving nature of fraud schemes and ensuring the scalability of real-time data processing. These areas present opportunities for future research and development.

EXPRESS: AI-based Financial Advice: An Ethical Discourse on AI-based Financial Advice and Ethical Reflection Framework

This article presents a first step in identifying the ethical issues of AI-based financial advice. Consumers must navigate an ever more complex array of financial decisions. (Generative) AI-based financial advice may increase access to and acceptance of financial advice and strengthen consumers’ financial well-being. However, significant ethical challenges exist in designing, developing, and deploying AI-based financial advice. To analyze the perils and pitfalls of AI-based financial advice, we develop a definition of what constitutes good AI-based financial advice and provide a first assessment of ethical challenges related to AI-based financial advice. The iterative multi-stakeholder approach, including workshops and semi-structured interviews with consumers and experts, results in an ethical discourse structured around the four fundamental values of the European Commission’s Ethics Guidelines for Trustworthy AI, human autonomy, explicability, fairness, prevention of harm, and trust as the overall objectives. Based on our analyses, we derive a simple yet comprehensive AI Ethics Framework for Financial Advice (AIFA). The AIFA reflection framework guides public policymakers, managers of financial service providers, and technology developers in incorporating ethical discourse in developing and deploying (generative) AI-based financial advice.

Analyzing the Impact of Microfinance Initiatives on Poverty Alleviation and Economic Development

This study investigates the impact of microfinance on poverty alleviation, economic development, and social outcomes in low-income communities. Microfinance, through providing small loans and financial services to individuals typically excluded from the formal financial system, has the potential to improve household income, stimulate entrepreneurship, and foster local economic growth. Using a quantitative research approach, the study employed a cross-sectional survey design with stratified random sampling of 250 microfinance beneficiaries and 250 non-beneficiaries. Data were collected through structured questionnaires, interviews, and secondary sources, including government reports and MFI records. Statistical analysis, including descriptive statistics, paired sample t-tests, independent sample t-tests, multiple regression analysis, and Pearson’s correlation, was used to assess relationships between microfinance access and key economic and social indicators. The results show that microfinance beneficiaries experienced a significant increase in household income (mean increase of 28%) compared to non-beneficiaries. Additionally, entrepreneurship rates increased by 15% among beneficiaries, and improvements were reported in health (17% improvement) and education (13% improvement). However, challenges such as high interest rates, limited outreach to marginalized groups, and over-indebtedness were identified. Despite these limitations, microfinance was found to have a positive impact on economic development, though more accessible and tailored programs are needed to maximize its potential. Recommendations for policy improvements, programmatic changes, and areas for future research are provided to enhance the effectiveness of microfinance initiatives.

The promise and perils of digital finance: evidence from crime rate in China

ABSTRACT This study explores the societal impact of the rapid global expansion of digital finance, employing China Household Finance Survey within a criminal economics framework. We found that the development of digital finance effectively alleviates the overall crime incidence, particularly in regions with higher mobile phone usage and lower proportions of older adults. The crime reduction effect correlates with the decline in cash transactions and the promotion of entrepreneurial activities. Moreover, variations exist in different digital finance services on property and non-property crimes. This empirical evidence offers valuable insights into the broader implications for countries experiencing unprecedented digital finance growth.

Pemanfaatan Artificial Intellegence (AI) dalam Meningkatkan Inklusi Ekonomi dan Keuangan

In the current digital era, economic and financial inclusion is a crucial issue in various countries including Indonesia. The use of artificial intelligence (AI) has great potential to improve economic and financial inclusion by providing easier, more efficient, and affordable access to financial and economic services for those who were previously marginalized. This research aims to identify Artificial Intelligence (AI) can be used to provide more inclusive financial services to those who are underserved, as well as to analyze its impact on the overall economic welfare of the community, especially Gorontalo city. This research used a descriptive qualitative approach, involving case studies and interviews with stakeholders. The results show that the utilization of Artificial Intelligence (AI) chatbots and virtual assistants has a significant impact on service and user satisfaction, as well as providing confidence in decision making so as to increase economic and financial inclusion for the community

Analisis Pengaruh Rasio-Rasio Keuangan Terhadap Rasio Beban Operasional-Pendapatan Operasional (BOPO) pada Bank Umum Syariah di Indonesia

This research aims to determine the influence of Islamic banking financial ratios in the form of Return on Assets (ROA) Ratio, Non Performing Financing (NPF) Ratio, Financing to Deposit Ratio (FDR) and Total Asset Turnover (TATO) on the Operational Cost-Operational Income Ratio (BOPO) at Sharia Commercial Banks in Indonesia. This research uses a quantitative approach with sample data totaling 7 (seven) sharia commercial banks out of 13 (thirteen) sharia commercial bank populations registered with the Financial Services Authority. Research data uses secondary data for the annual period in the period 2010 - 2023. By using the ARDL (Autoreggressive Distributed Lag) panel model using the PMG (Pooled Mean Group) method, the research results show that in the panel, it turns out that the Leading Indicator is the effectiveness of the variable in controlling the BOPO Ratio at Sharia Commercial Banks in Indonesia is Return on Assets (ROA), where ROA significantly influences the BOPO Ratio at Bank Muamalat Indonesia, Bank Aceh Syariah, Bank Riau Kepri Syariah, Bank Jabar Banten Syariah, Bank Mega Syariah, and Bank NTB Syariah, with stable positions in the short and long term. Of the 7 (seven) Sharia Commercial Banks that are the objects of research, there are 4 (four) banks that are leading indicators of the effectiveness of sharia banking in influencing the stability of the BOPO ratio, namely: Bank Aceh Syariah, Bank Riau Kepri Syariah, Bank Jabar Banten Syariah, and Bank Mega Syariah through ROA, NPF, FDR, and TATO. Financing to Deposit Ratio (FDR) is also capable of being a Leading Indicator of variable effectiveness to influence the BOPO Ratio at Bank Muamalat Indonesia, Bank Aceh Syariah, Bank Riau Kepri Syariah, Bank BCA Syariah, Bank Jabar Banten Syariah, Bank Mega Syariah, and Bank NTB Syariah, However, its position is unstable in the short and long term.

AI-Based Phishing Detection and Automated Response: A Multi-Channel Security Framework for Modern Communication Platforms

Phishing attacks have evolved in sophistication over the changing digital communication landscape, taking advantage of several channels like social media, SMS, and email to trick people and businesses. This research offers a multi-channel security architecture for automated phishing response and detection that uses cutting-edge artificial intelligence (AI) technology to counteract this ubiquitous threat. The system utilizes automatic reaction mechanisms to mitigate threats in real time and incorporates state-of-the-art AI algorithms to improve the detection of phishing attempts across various communication channels. This study examines recent developments in artificial intelligence (AI) for cybersecurity, emphasizing the use of deep learning, machine learning, and natural language processing in phishing detection and response. It also looks at how phishing techniques have changed over time, how difficult it is to integrate AI across different platforms, and how dangerous it could be for AI systems to come under hostile attack. The report shows the usefulness and practical use of AI-driven solutions with case studies from social media, financial services, and enterprise communication platforms. It also discusses ethical and regulatory issues, highlighting the necessity of adhering to data protection regulations and using AI responsibly. The technological difficulties, potential avenues for future investigation, and prospects for innovation in AI-based phishing detection are covered in the paper's conclusion. With this methodology, cybersecurity researchers and practitioners can benefit from a thorough approach to improving cybersecurity with artificial intelligence.

Impact of trust-building strategies on investment decisions: Mediating role of the financial advisor-client relationship

Trust is a fundamental element in financial interactions, particularly in the advisory sector, influencing investment decisions and overall client satisfaction. This study aims to explore the impact of trust-building strategies on investment decisions through the financial advisor-client relationship. The research employs a structured questionnaire to gather data on trust-building strategies, the advisor-client relationship, and investment decisions. The study found that trust-building strategies, such as transparency and competence demonstration, positively influenced investor decisions. Specifically, 78% of investors reported increased confidence in their investment choices after engaging with advisors who prioritized transparency and expertise. Moreover, 85% of investors indicated a preference for advisors who demonstrated reliability and ethical conduct, leading to a stronger advisor-client relationship. The findings underscore the importance of trust in financial advisory services and suggest that enhancing trust through transparent practices can lead to more informed and collaborative decision-making processes. The study emphasizes the evolving nature of investment decision-making and proposes integrating technological innovations like AI and robo-advisors. The study provides valuable insights for financial institutions to invest in advisor training and guidance, benefiting all stakeholders involved.

Assessing Financial Inclusion Across Indian States and Union Territories

Financial inclusion is essential for the effective channelisation of money, allowing individuals to access financial products and services that enhance their financial well-being and contribute to the economic growth of a nation. Governments worldwide are recognising the importance of financial inclusion and are taking initiatives to enhance it. In India, the Pradhan Mantri Jan Dhan Yojana (PMJDY), launched in 2014 stands as a significant effort by the government to boost financial inclusion. This study is an attempt to assess financial inclusion across Indian states and union territories, focusing on three key dimensions: automated teller machines (ATM) penetration, insurance penetration and mutual fund penetration. This study is based entirely on secondary data, sourced from the annual reports of the Reserve Bank of India (RBI), Insurance Regulatory and Development Authority of India (IRDAI), Securities and Exchange Board of India (SEBI), Association of Mutual Funds in India (AMFI) and Unique Identification Authority of India (UIAI). The findings of this study provide valuable insights into the current state of financial inclusion in India and will contribute to effective policy formation aimed at enhancing financial inclusion across Indian states and union territories.

Event-Driven Architecture: Harnessing Kafka and Spring Boot for Scalable, Real-Time Applications

This comprehensive article explores the transformative impact of Event-Driven Architecture (EDA) in modern financial services, focusing on its implementation using Apache Kafka and Spring Boot. The article examines how financial institutions have revolutionized their transaction processing capabilities through EDA adoption, achieving significant improvements in system performance, reliability, and customer experience. Through a detailed examination of real-world implementations, the analysis demonstrates how EDA has enabled banks to handle unprecedented transaction volumes while substantially reducing system latency and improving resource utilization. The integration of Kafka and Spring Boot has proven particularly effective, with major financial institutions leveraging these technologies to achieve superior performance metrics and system availability. The article further explores critical patterns, including event sourcing, CQRS, and saga patterns, alongside cloud-based best practices for monitoring, performance optimization, and security implementations. By examining various implementation strategies and their outcomes, this article provides a comprehensive framework for building scalable, resilient financial systems that meet the demanding requirements of modern banking operations while ensuring regulatory compliance and maintaining high security and reliability standards.

COVID-19 and Market Response: Evidence From Listed Firms in Tanzania and Kenya

This study investigates the effects of COVID-19 on the financial performance of listed firms in the financial and consumer goods industries in Tanzania and Kenya. The choice of Tanzania and Kenya as focal points is motivated by their contrasting responses to the pandemic and their roles as economic powerhouses in the region. Using data from the Dar es Salaam Stock Exchange and Nairobi Stock Exchange spanning the period from 2015 to 2022, the study employs the Dynamic panel-data model, the two-step system GMM, to quantify the impact of the pandemic. The research has two specific objectives: to analyze the effect of COVID-19 on the financial performance of listed firms in the financial industry and to assess its impact on the consumer goods industry in both countries. Key findings reveal that in the financial sector, firms showed resilience with a positive impact on profitability during the pandemic, driven by the adoption of digital financial services and effective risk management. In contrast, the consumer goods sector experienced a significant negative impact, highlighting severe disruptions in supply chains and consumer demand. Notably, firms in Tanzania outperformed those in Kenya, due to less restrictive COVID-19 measures. These findings suggest policymakers should support digital innovations, prudent leveraging, and economic growth to sustain and improve firm profitability during future disruptions.

Enforcement of consumer rights protection laws and intention to reuse digital financial services among Generation Z youth: Empirical evidence from Vietnamese commercial banks

Digital financial services are crucial in boosting the competitive edge of businesses and economies in numerous developing nations. This study aims to explore the factors that affect consumers’ perceptions of the implementation of consumer protection laws and their willingness to continue using digital financial services. Data were collected through interviews with 689 Gen Z consumers (born after 1996) who have used digital financial services in Vietnamese commercial banks. The results of the partial least square – structural equation modeling indicate that six factors influence attitudes toward the enforcement of consumer protection laws, in descending order: perceived benefits, understanding of legal regulations, perceived asymmetry, perceived risk, understanding of technology and digital finance, and understanding of dispute resolution. Additionally, attitudes toward law enforcement, as well as understanding of technology and digital finance, positively impact consumers’ intention to reuse digital financial services, while perceived risk has the opposite effect. Furthermore, all six independent factors impact the intention to reuse digital financial services through the mediating role of attitudes toward the enforcement of consumer protection laws. The study’s findings also lay the groundwork for policy recommendations for legislative authorities and strategic guidance for service providers and consumers in emerging markets in the future. AcknowledgmentThis study is the result of collaboration between researchers from the University of Law, Hue University, and School of Business and Economics, Duy Tan University. The authors would like to thank both institutions for their support and facilitation in the publication of this research. This study was conducted under project code DHH2024-12-85, Decision No. 298/QĐ-ĐHH dated March 27, 2024, issued by the Director of Hue University.

SLR ABOUT THE COSTS OF PRIVATE BLOCKCHAIN TECHNOLOGY FOR BUSINESSES

Since the appearance of Bitcoin (2009), blockchain technology has been used in many fields. Companies use it for financial services, goods tracking, data authentication and secure storage, among other things, in order to make their operations more transparent and efficient. This technology has revolutionized the data management and transaction processing, but the associated costs are also significant and relevant to understand. The costs of blockchains vary and depend on the type of blockchain and how it is used. In this article, we examine the costs of using blockchain technology based on international literature, studies and reports with systematic literature review. In the results the range of possibilities offered by technology is presented, as well as the technology related cost types, and expenditures what companies have to deal with.

Financial behavior between male and female: a systematic literature review

Finance is an essential aspect of existence. Handling it is reflected in one’s financial behavior. Poor financial decisions have consequences, therefore it's critical for people of both genders, men and women, to be financially informed in making financial decisions. A synthesis of the differences in financial behavior between men and women is the aim of this systematic literature review. Twenty-seven papers (27) published papers between 2014 and 2024 were extracted from the database using the Preferred Reporting Items for Systematic Review (PRISMA) framework. The findings showed that, in comparison to women, men are more financially knowledgeable; they have a greater risk appetite than women, which allows then to take advantage of financial products and services. Contrarily, females with their risk aversion attitude, leaves them financially susceptible because it prevents them from taking advantage of financial products and services like optimizing the potential for money growth. In terms of spending, women are more conservative, and are price sensitive than men. The findings also indicates that women are more vulnerable to financial misconduct; yet, financial literacy will mitigate this risk. Therefore, programs for gender-sensitive financial education should be taken into consideration to close the gap in financial literacy and give women more power in making financial decisions. With this, it would promote financial inclusion and aid in the realization of Sustainable Development Goals (SDG) 5 and 10 or Gender Equality and Reduce inequalities respectively. Future studies may focus on how financial technology affects gendered financial behavior to promote more equal economic outcomes.

THE INNOVATIVE TRANSFORMATION IN THE RA BANKING SYSTEM

The analysis shows that the innovative transformation in the banking system of Armenia is a multi-level process that has a significant impact on the entire financial sector of the country. One of the key aspects of this transformation is the deep integration of modern technology into banking. This not only facilitates the interaction of customers and banks, but also increases the level of transparency and efficiency of financial transactions. The innovation of the RA banking system contributes to the expansion of access to financial services, enabling more people to use financial services, especially where they were previously limited. It was concluded that innovations and technological developments enable the banking system to provide faster, safer and more convenient services, reduce human errors and improve the efficiency of processes. New technologies improve the level of security. All of this is leading to greater competition in the banking industry, new ways of working and strategies, and overall improvements in customer service and financial operations (Egorova, A., A., (2015). But they also present new challenges, such as data protection and security issues, as well as the need to use new technologies.

Building Financial Wellness: Randomized Controlled Trial of a Financial Education and Support Intervention.

Many people receiving services for psychiatric disorders live on low incomes, navigate complex financial situations, and have limited economic security. The authors sought to determine whether a financial wellness intervention delivered virtually by peers would increase financial literacy, reduce economic strain, and improve financial competency. One hundred participants receiving services for psychiatric disorders were recruited from community programs and via social media and were randomly assigned (1:1) to receive either an intervention called Building Financial Wellness (N=51) or services as usual (N=49). The intervention involved six virtual 1.5-hour group sessions, followed by three virtual one-on-one booster sessions. Outcomes were assessed with the Consumer Financial Protection Bureau's Financial Well-Being Scale (primary), Financial Strain Questionnaire, Financial Capability Scale, and Financial Self-Sufficiency Scale. Knowledge regarding money management was measured with a financial literacy assessment based on class content. Intent-to-treat longitudinal multivariable analysis included random-effects linear and logistic regression models. Overall, 86% of the study participants either lived in poverty (46%) or met the federal definition of low income (40%). Participants assigned to the intervention had greater improvement over time in financial well-being, capability, strain, self-sufficiency, and literacy. Satisfaction with the intervention was high. Reports from participants receiving booster sessions indicated that ongoing support facilitated their achievement of longer-term financial goals. Provision of financial education and support improved monetary well-being, competence, and literacy. With poverty long considered to be an intractable problem associated with psychiatric disorders, peer-taught financial education focused on financial wellness can help people acquire money management skills and manage economic stressors.

Factors Affecting Muslims' Decision in Tangerang Selatan During Recession to Make Sharia Investment

The pandemic has had a significant impact on the global economy, including Indonesia, which experienced a recession in 2020. However, a unique phenomenon occurs in the Islamic capital market, where Islamic stocks show stability and even experience significant increases during the recession. The study explores how the recession affects the decision of Muslims in Indonesia to invest in Sharia and whether Sharia investment can be an effective solution to deal with a recession. Data from the Central Statistics Agency and the Financial Services Authority shows that the sharia capital market in Indonesia continues to grow, especially in the form of sharia stocks and sharia mutual funds. This study aims to analyze the factors that affect the decision of the Muslim community to make sharia investments during the recession due to the COVID-19 pandemic. This study uses quantitative methods with respondents from various sectors of the Muslim community in Indonesia, including students, office workers, and entrepreneurs. The results of this study found that the decisions of the Muslim community have a significant influence on Islamic investment, with the results of the t-test showing a t-count value of 25.366 and a determination coefficient (R²) of 86.8%. This means that most of the variations in sharia investment can be explained by community decisions, while the remaining 13.2% is influenced by other variables. The conclusion of this study is that increasing Islamic financial literacy and religious understanding can be an effective strategy to encourage interest in Islamic investment in Indonesia. This research is expected to be a reference for financial institutions and policymakers in improving accessibility and education related to Sharia investment.

Disaster Preparedness and capacity building for Resilience in Agriculture

Abstract. Agriculture faces unprecedented challenges due to the increasing frequency and severity of natural disasters and extreme weather events. Agriculture sector needs resilience to support food production and livelihoods because it is susceptible to cyclones, floods, droughts, soil erosion, pests, and disease outbreaks. Geospatial technology plays a significant role in disaster management for agriculture, offering tools for preparedness, response, and recovery. This study explores the role of geospatial technology in early warning systems and risk assessment for different types of natural disasters that impact agriculture activity. Sustainable farming practices that are essential for resilience include crop diversity, climate-resilience varieties, and adaptation strategies. Capacity building and training are vital for effective geospatial technology utilization, especially in developing countries like India, where infrastructure and technology access may be limited. Tailored capacity-building programs are essential, emphasizing climate-smart practices, sustainable land management, and post-disaster recovery strategies. Access to financial services and insurance schemes enhances resilience by helping farmers cope with losses and recover from disasters. In order to improve resilience and sustainability in agriculture, geospatial decision support systems make it possible to evaluate alternative planning, optimise resource allocation, and implement adaptive management.