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AI and Business Intelligence Integration for Improved Efficiency and Reporting Accuracy in Small U.S. Financial Institutions
Full text linkThis article seeks to examine how AI is more than merely a device for automation — how it is also a mechanism for structural change, inclusion and trust in financial systems. The article integrates secondary data with expert opinion, and demonstrates how in Uzbekistan, AI in fintech is becoming the “invisible hand” of market effectiveness and the “visible hand” of digital governance. Personal reflections are also singled out in this paper. Tags: Artificial Intelligence, Machine Learning (ML), Natural Language Processing (NLP), FinTech, Credit Scoring, Fraud Detection, Customer experience, Biometric Authentication, Digital Banking, Government Strategy, Uzbekistan, Innovation
Using Renewable Energy to Reduce Production Costs and Achieve Environmental Sustainability: An Applied Study
Full text linkThis paper aims to investigate the impacts of solar energy exploitation on the reduction of cost of production and the enhancement of environmental sustainability. The analysis produced a number of results with the most notable one being that solar energy is an important modern technology that can be used to curb the cost of production and lessen the use of fossil fuels in the production of power. As a result, this dynamic results in high levels of emissions of pollutants that can be attributed to the expansion of industrial activity. In addition, solar energy is critical towards stemming out carbon emitting mechanical propulsion systems driven by fuels besides conserving resources and attaining cost savings and enhanced environmental performance
Integrating AI-Driven Compliance Frameworks to Automate Regulatory Monitoring across U.S. Healthcare, Finance and Institutional Governance Systems
Full text linkThis paper explores how Artificial Intelligence (AI)-based compliance systems can be used to automate regulation monitoring in three major sectors in the U.S. healthcare, finance, and institutional governance. It will seek to determine the awareness, perceived benefits, implementation difficulties, effectiveness, and future prospects of AI application in compliance management. The study provides empirical data to the knowledge of improving compliance efficiency, transparency, and accountability of AI technologies in complex regulatory settings. A quantitative method of conducting a research was used and a set of questions was measured with structured questionnaire and was sent to a sample of 300 professionals representing healthcare, finance and governance institutions. The research employed the descriptive, correlation, and inferential statistics to analyze the relationships between the core constructs. The SPSS was used to analyze data with the involvement of reliability testing, correlation, multiple regression, ANOVA, t-tests, and exploratory factor analysis (EFA) to prove the measurement model and evaluate the dynamics between variables. The findings also indicated that, all constructs had high internal consistency with Cronbach Alpha values varying between 0.84 and 0.93, which was a strong instrument reliability. Descriptive statistics revealed that the overall perception of the AI adoption is positive, with the highest means being Effectiveness and Impact and Perceived Benefits. Correlation, regression analyses indicated that Perceived Benefits, Future Prospects, and Awareness and Adoption significantly and positively predicted Effectiveness and Impacts whereas the Challenges and Barriers had a negative effect. It was found that the model explains a strong 69 percent of the variance in effectiveness. Also, global sectoral differences in perceived effectiveness were significant based on the results of ANOVA, and the results of the t-test based on gender showed that female respondents were slightly more confident about the benefits of AI. The EFA found four different but related factors that include AI Effectiveness, Compliance Benefits, Implementation Barriers, and Future Readiness that explain 70% of the total variance. The results highlight the importance of strategic preparedness, sufficient infrastructure, and ethical governance as the elements that ensure success in the process of AI integration into compliance. To achieve a sustainable adoption, organizations need to deal with issues of data privacy, transparency, and skills. The research proposes capacity-building programs, cross-sectional coordination, and the creation of uniform AI governance systems to facilitate accountability and predictability in regulation automation. The study offers one of the limited empirical evaluations of AI-based compliance systems in a wide variety of regulated sectors in the U.S. It builds upon the existing works of literature by connecting the efficacy of technology to the organizational preparedness and perceived value, which provides practical implications to policymakers, compliance professionals, and institutional leaders. The study can add value to the developing debate on intelligent governance and ethical automation by confirming a robust framework of assessing AI compliance performance
Developing Hybrid Post-Quantum Encryption Frameworks for U.S. Databases Integrating Financial, Governmental, and Critical Infrastructure Protections
Full text linkPurposeThe rapid evolution of quantum computing is a major menace to the current cryptography design and poses a risk to the confidentiality of sensitive data in the financial, government/critical infrastructure arena of the United States. The following paper aims at exploring the development, adoption, and motivation of hybrid post-quantum encryption (PQC) models, i.e., classical and quantum-resistant algorithms. It particularly measures the awareness, practical application levels, perceived benefits, and readiness to implement among the key sectors in the United States, and measures the assistance and collaboration of the policy in the process.
Design/methodology/approachThe study follows a descriptive and correlational design, with a mixed-methods approach with a quantitative survey as its main focus. The data were gathered within 235 cybersecurity professionals and decision-makers within U.S. financial, governmental, and critical infrastructure organizations using a structured survey. This survey tool proved to be very reliable (Cronbachs Alpha = 0.928). The data were analyzed using descriptive statistics, Pearson correlation, multiple regression and Analysis of Variance (ANOVA) to determine the relationship between variables and find out the differences between sectors.
FindingsThe results show that the general awareness of the post-quantum cryptography among respondents is rather high (M=4.08). There were found strong positive correlations between awareness, implementation of hybrid practices, perceived security benefits, and implementation readiness. To identify predictive variables of the implementation readiness, regression analysis was conducted and demonstrated that policy support, security benefits, and hybrid practices were substantial predictors of implementation readiness with a combined account of 68.6 percent of the variation in implementation readiness. In addition, the results of ANOVA indicated statistically significant sectoral disparities in the perceived security benefits of hybrid PQC in that government and defense industries were more willing to adopt this type of technology than the performance sensitive financial industry.
Originality/valueThis study offers an opportune and empirical study on sector-specific preparedness and perceptions toward hybrid PQC in the United States, which is a sensitive national security domain. It provides new ideas as it quantitatively connects the awareness, policy support and practical application to implementation readiness, and it outlines the subtle issues in various industries. The results provide policymakers, technology creators, and organizational executives with evidence-based solutions to create custom strategies, training methods, and regulatory systems to enable a safe and seamless move to quantum-resistant cryptography
Analysis of Determinant Factors Affecting Investment Opportunity Set and Automotive Industry Stock Return on The Tokyo Stock Exchange
Full text linkThis study aims to analyze the relationship between capital structure, profitability, and dividend policy on stock returns with investment opportunity set as an intervening variable in companies listed on the Tokyo Stock Exchange Transportation Equipment Sub-Sector and members of the Japan Automobile Manufacturers Association in 2015-2024. This study uses a lag time treatment on the Capital Structure, Profitability and Dividend Policy variables with the aim of finding a stronger and more significant correlation on the variables studied, the data collection technique used is the documentation technique processed using the Path Analysis method using SPSS Amos software. 26. The results of the study indicate that the influence between Capital Structure, Profitability, and Dividend Policy on Investment Opportunity Set is not significant. The influence between Capital Structure, Profitability, and Dividend Policy on Stock Returns through Investment Opportunity Set as an intervening variable is not significant. While the influence between Investment Opportunity Set on Stock Returns is significant
AI-Powered Fraud Detection: Strengthening Risk Monitoring with Business Intelligence in U.S. Financial Institutions
Full text linkThe growing complexity of financial fraud in the United States has pushed organizations to adopt advanced technologies for more effective risk monitoring. This study examines how various U.S. financial institutions—including banks, fintech firms, and credit unions—implement AI and business intelligence (BI) tools for fraud detection. A survey of 400 professionals from these sectors investigates how AI adoption relates to trust in the technology, staff training levels, BI usage, and future investment intentions. In addition to standard statistical analyses, machine learning models were applied to uncover hidden patterns influencing adoption behavior. The results indicate that AI integration is driven mainly by investment readiness, confidence in AI, the extent of BI utilization, and perceived AI speed, whereas individual perceptual factors alone show limited significance. Overall, the findings suggest that successful AI adoption is shaped by organizational strategy, institutional culture, and existing technological infrastructure. To maximize the effectiveness of fraud detection, U.S. financial institutions should adopt integrated AI–BI solutions, maintain regulatory compliance, and enhance workforce skills to fully leverage the capabilities of AI
The Role of Artificial Intelligence in Enhancing the Accuracy of Accounting Estimates: Evidence from the Iraqi Telecommunications Sector
Full text linkThis study explores how artificial intelligence (AI) could improve accounting estimates\u27 precision, openness, and auditability in the Iraqi telecom industry. The structure, consistency, and disclosure procedures of accounting estimates are assessed by the study using a comparative document-based examination of Asiacell, Zain Iraq, and Al-Khatem Telecom\u27s annual financial reports from 2020 to 2023. The results are compared to international standards such as IAS 8 and ISA 540 (Revised). Although these disclosures did not specifically mention the usage of AI technologies, the uniformity and openness that were noted point to organized models that may have been facilitated by business software. According to the study, using AI such as explainable AI (XAI) and predictive analytics could enhance estimation quality and promote audit preparedness. The lack of primary data, such as surveys or interviews, and the lack of direct confirmation of AI adoption are the study\u27s limitations. To further comprehend AI\u27s changing role in financial estimate, future study is advised to investigate organizational preparedness, do sectoral comparisons, and include longitudinal evaluations
The Impact of AI-Integrated Dashboards and Automation on CRM Workflow Optimization in U.S. Small and Mid-Sized Brokerage Firms
Full text linkThis article examines how effectively AI-driven dashboards and automated tools are being utilized by small and mid-sized brokerage firms in the United States to enhance CRM workflows. Drawing on responses from 200 CRM professionals, the study explores the extent of AI adoption, its perceived usefulness, organizational readiness, reasons for non-adoption, and future expansion plans. The findings show that slightly more than half of the participants (55.5%) currently use AI dashboards, and most users report favorable experiences. The analysis reveals a strong association between AI dashboard usage and an organization’s decision to adopt AI, while challenges such as employee resistance and insufficient training reduce its effectiveness and limit future adoption. Factor analysis and reliability testing confirm that the scales measuring AI effectiveness and barriers are sound. Overall, the results indicate that although AI tools contribute to smoother CRM processes, organizations continue to encounter both structural and technical obstacles. The study provides practical insights for CRM practitioners, software developers, and policymakers seeking to advance digital transformation in the U.S. brokerage industry
The Role of External Auditing in Limiting the Practice of Creative Accounting:An Analytical Study of the Opinions of a Sample of Academics and Professionals (Accountants and Auditors) at the University of Kirkuk
Full text linkThe study aims to examine the role of external auditing in limiting the practice of creative accounting in financial statements (income statement, balance sheet, cash flow statement, and statement of changes in equity) at the University of Kirkuk. The necessary data to achieve the research objectives were collected and analyzed through a questionnaire designed and distributed to the research sample, consisting of academics and professionals working at the university. The study employed a descriptive-analytical approach, and the data were processed using SPSS software. The research concluded several findings, the most significant of which is the presence of a statistically significant positive effect of external auditing in reducing the practice of creative accounting in financial statements. The study also found that creative accounting practices exist in financial statements at varying levels, with the highest occurrence in the income statement and the lowest in the cash flow statement. The researcher recommends enhancing the role of external auditing by applying international auditing standards and developing internal control systems to be more efficient and capable of detecting improper practices in the preparation of financial statements
Influence of Components of the Artificial Intelligence on the Fin-tech Market of Uzbekistan: Banking and Insurance Systems
Full text linkThis article seeks to examine how AI is more than merely a device for automation — how it is also a mechanism for structural change, inclusion and trust in financial systems. The article integrates secondary data with expert opinion, and demonstrates how in Uzbekistan, AI in fintech is becoming the “invisible hand” of market effectiveness and the “visible hand” of digital governance. Personal reflections are also singled out in this paper. Tags: Artificial Intelligence, Machine Learning (ML), Natural Language Processing (NLP), FinTech, Credit Scoring, Fraud Detection, Customer experience, Biometric Authentication, Digital Banking, Government Strategy, Uzbekistan, Innovation