Previous studies have suggested that digitization of finance leads to growth in the economy in several middle- and high-income countries, but research in low- and lower-middle-income countries (LLMICs) remains limited. This research aimed to examine the trends, barriers, relationships, and prospects of finance digitization in LLMICs. This study used analytical and descriptive cross-sectional study designs. Sixty-six countries were purposively selected based on the available data on the Global Findex and the World Development Indicators databases. Descriptive analysis was used to identify the trends in the finance digitization indicators, correlation analysis was used to assess the nature of the association between finance digitization and the economy, and exponential smoothing was used to predict future outcomes in digital finance. The results indicated that the adoption and utilization of finance digitization increased in these countries, but the growth rates varied by region and income group. Low-income countries reported the highest rates of subscriptions to digital finance accounts and storing money in digital accounts, while lower-middle-income countries (LMICs) reported higher rates of inbound/outbound digital transactions, borrowings, and savings using digital channels. Sub-Saharan Africa reported the highest rates of digital finance account subscriptions, digital savings, and digital borrowings, while Europe and Central Asia reported the highest rates of in/out digital transactions. Barriers to digitization in these countries included poor access to the internet, high cost of digital finance products, and lack of a mobile phone, with low-income countries facing more challenges. The analysis revealed a negative significant relationship between finance digitization and Gross National Income growth and a positive significant correlation between finance digitization and other economic growth indicators (gross savings and Gross Domestic Product). Finance digitization was predicted to continue to rise in these countries for the next decade. The study recommended that policymakers should promote the adoption of digital finance and address the barriers and risks of finance digitization in LLMICs, as it had positive effects on economic growth.

The concept of public financial accountability, often associated with account-rendering, lacks a clear and comprehensive definition in the realm of accounting literature. Disentanglement the true essence of a phenomenon is essential, as formal definitions can only provide a superficial understanding. This study seeks to delve into the core principles of public financial accountability and their implications for financial reporting in the public sector. Applying a qualitative approach, data was gathered through in-depth interviews with 25 Nigerian scholars, professionals, and public affairs experts. The analysis reveals that the essence of public financial accountability lies in upholding citisens' trust in public officials, ensuring the responsible management of public financial resources for the greater public good, and effectively communicating financial decisions, actions, and outcomes to the public through a transparent reporting mechanism. This study sheds light on the fundamental nature of financial accountability in the public sector, enhancing our understanding of its significance in governance and financial reporting.

This study investigates the impact of financial integration on international dynamics from the perspective of volatility shocks. To achieve this, I employ an IRBC model with time-varying volatilities, recursive preferences, and a global bank. The model demonstrates that volatility shocks trigger precautionary saving incentives, but the specific effects vary based on the type of shock. In the presence of productivity volatilities, countries with a higher level of financial integration exhibit greater divergence in their business cycles, while financial integration tends to result in more synchronized business cycles in the face of financial volatilities. Disregarding volatility shocks would underestimate the impact of financial integration on the comovement of business cycles across countries. Furthermore, welfare analysis also indicates that financial markets play a crucial role in enhancing social welfare, regardless of the type of volatility.

The demand for renewable energy is increasing globally due to concerns about climate change, pollution, and the finite nature of fossil fuel resources, as renewable energy has been recognized as a significant factor in realizing sustainable development. The government of Saudi Arabia adopted the reduction of fossil fuel subsidies policy as a financial motivation for supporting both the production and consumption of fossil fuels. Therefore, this study aims to investigate the influence and shocks of Saudi’s financial development indicators on renewable energy consumption (REC). And to examine the track of causality between financial development indicators and REC. The study covers the annual data period of 1990-2021 and applies the Basic Vector Autoregressive model (VAR), Granger causality test, forecast error variance decomposition (FEVD), and impulse response function (IRF). The results imply that the financial development indicators have a significant positive impact on REC. The results of causality between REC and financial development indicators were conflicting. The results reveal that REC variation is explained by its innovative shocks and has a positive response to shocks in financial development. Authorities can encourage investment in renewable energy consumption by providing financial incentives also the governments can foster national and international partnerships between investors, policymakers, and industry stakeholders. Employing different determinants of financial development indicators and incorporating population factors in the REC function will be highly recommended for forming the renewable energy demand in Saudi Arabia.

This study delves into the integration of Decentralized Finance (DeFi) within metaverses, probing its implications and potential. It elucidates DeFi protocols and the intricacies of metaverses before inspecting their intersection and the resulting economic prospects. The analysis further appraises inherent risks such as financial volatility, security, and regulatory issues. Case studies provide tangible insights into DeFi applications in metaverses. Future trajectories of DeFi in metaverses are projected, underlining the possible impact on the broader financial sector. This paper contributes to burgeoning research at the nexus of blockchain technology, finance, and virtual reality.

This study aims to assess and identify the role of disruptive/digital technologies in financial innovation strategies as part of social innovations at both firm and country level. There are few studies of this type that "cross-examine" technical/social innovative capacity at the firm level vs. the same innovative capacity at the level of the world's major countries. Our proposed study brings some novel elements to the literature on this topic. First, the study synthesizes the factors/variables explaining technical/social innovative capacity as ranked by the GCI (Global Competitiveness Index) and GII (Global Innovation Index) at the country level and then correlates these variables with the factors explaining innovative capacity for the 50 companies in the BCG (Boston Consulting Group) ranking. Second, the study identifies three "driving forces" (digital technologies, managers and the market) as the main variables determining financial innovativeness at firm level. Third, based on the "cross" analysis of the information/data provided by the BCG study vs. the GII and GCI studies, the study suggests some ways to delineate and quantify financial innovation as part of social innovation (e.g., it is argued that 80% of the social innovation achieved annually by a firm relates to the financial relationships engaged by the firm with various categories of stakeholders). Finally, the study is also important from a pragmatic point of view as it suggests/proposes a number of principles that can be considered by managers for building a KM (knowledge management) and continuous innovation strategy. From a theoretical perspective, the study provides a starting point for further research aimed at explaining firm-level financial innovation through the massive use of disruptive technologies.

Distortion of financial statements is recognized as one of the most important issues in the field of accounting and auditing, which is also one of the most common issues today. In this regard, the present research was conducted, in which stock exchange information was used to investigate, predict, and model accounting distortions. For this purpose, financial performance, non-financial metrics, market-based metrics and commitment, or selection items were reviewed over a 6-year period. For collecting data of distorting companies, database of the Society of Certified Public Accountants in Iran was used and the information was analyzed using data mining methods (decision tree, neural networks, and Bayesian method). The results showed that analysis of financial statements҆ information has a high accuracy in determining and identifying the distorted financial statements. Using this information, it is possible to get better acquainted with the methods of document distortion and to take necessary measures in order to control and prevent administrative violations at national and international levels. Given frequent occurrence of these violations, artificial intelligence models can be used to identify these papers.

FinTech has been in the focus of the discussion for quite some time. However, the market share of FinTech companies is still relatively small in compared to more traditional financial services. The purpose of this paper is to analyse the status quo, current developments and challenges ahead for the Latvian FinTech sector. We combine three analyses: the political and legal, the economic, the social and the technological environment (PEST) analysis, an analysis of the size and performance of FinTech companies during the last 10 years, and a survey among FinTech companies. We find that the current status of regulation is one of the main obstacles to FinTech development, because it does not sufficiently consider FinTech-specific aspects. Problems in attracting skilled workforce, and an environment that is not very supportive of new developments in finance are further challenges and might explain at least part of the growth and performance difficulties. A revision, modernization and harmonization of regulation is essential to create a level playing field for all market participants: FinTech companies, traditional financial service providers and those originally traditional players that are integrating FinTech solutions in their business model. Further efforts are also required to foster the Latvia’s attractiveness for skilled workforce. We hope that this study helps increase the visibility of Latvian FinTech and contributes to the development of the new Latvian FinTech strategy.

Methods of path integrals are used to develop multi-factor probabilities of bid-ask variables for use in high-frequency trading (HFT). Adaptive Simulated Annealing (ASA) is used to fit the nonlinear forms so developed to a day of BitMEX tick data. Maxima algebraic code is used to develop the path integral codes into C codes, and sampling code is used for the fitting process. After these fits, the resultant C code is very fast and useful for forecasting upcoming ask, bid, midprice, etc., when narrow and wide windows of incoming data are used. A bonus is the availability of canonical momenta indicators (CMI) useful to forecast direction and strengths of these variables.

Based on the seminal paper of Case, Quigley and Shiller (2013), we investigate the effects of financial and housing wealth on consumption. Using quarterly data from 1975 to 2016, for all States of U.S. economy, and a different methodology in measuring wealth, we report relatively greater financial effects than housing effects on consumption. Specifically, in our basic utilized model, the calculated elasticity for financial wealth is 0.060, while for housing is 0.045. The results are not in agreement with the ones obtained by Case, Quigley and Shiller. In an attempt to investigate the disparity we proceed by incorporating the introduction of the Tax Reform Act in 1986, which increased incentives for owner-occupied housing investments. Finally, due to distributional factors at work, and taking into account the pronounced uneven distribution of wealth we investigate the effects of wealth for 8 states that include the Metropolitan areas comprising of the well known Case-Shiller 10-City Composite Index. Now the housing effect on consumption is much stronger and larger than the financial effect. Additionally, we forecast the consumption changes at the time of the high rise and large drops in house prices for these states. Forecasts showed a recession from the fall of Lehman Brothers until the fourth quarter of 2011. These forecasts were not verified. Probably, the new techniques used by politics played an important role. We also find that extreme behaviors cannot be predicted.

Considering the impact of religiosity on the perceptions regarding life quality, in this paper we focus on the effects of the appurtenance to a religion on the standard of living in several economically developing countries (Turkey, Ukraine, Senegal and Morocco). The data have been collected using a survey carried out in 2012 and the empirical analysis was based on non-parametric tests and multinomial logistic regression. The results indicate there are differences between religious persons and atheists regarding gender, marital status, perceptions of daily life and standards of living. Females and officially married people or single people tend to be more religious. A person claiming to belong to a religion has 2-4-fold more chances to achieve a considerable improvement in the standards of living as compared to an atheist. Moreover, religious people from the analyzed countries are more optimistic about their life overall. Taking into account the sample’s characteristics and the countries chosen, we can claim that the results obtained are truly cross-cultural in nature. Moreover, most of the conclusions reached would be to some extent relevant to other developing economies of Eastern Europe, North Africa and Middle East.

Financial market data analysts are increasingly turning towards machine learning techniques for data analysis and making decisions. This paper explores how knowledge graphs, essentially a network of real entities and their relationships, can be used to improve collaborative financial market data analysis and make it more efficient and user friendly. This paper reviews the current state of financial market data analysis, the challenges in deploying machine learning models in industrial environments, and the concepts such as ML-Ops and knowledge graphs. A software architecture comprising various roles, layers and services such as Data Engineers, Data Analysts, public users, APIs, workflows, analytics libraries, UX layer, Business Layer, etc. is introduced and described in detail. Then, it discusses how knowledge graphs can be used to enhance collaborative financial market data analysis. Finally, a case study is presented to demonstrate the usage of the whole system, within the context of financial market data analytics of equities.

With the continuous advancement of digital transformation, digital payments are playing an increasingly important role in the financial industry. This study aims to utilize machine learning models to predict and analyze digital payment behavior. Initially, the background and significance of digital payments in the financial sector are introduced. Subsequently, the current status and trends of traditional digital payment distribution are reviewed, alongside related work on digital payment behavior prediction. Methodologically, principles and applications of machine learning models such as logistic regression, decision trees, and random forests are elaborated, along with experimental design and data preprocessing methods. The experimental results and discussion section illustrates the performance of each model in digital payment prediction and explores their impact on credit decisions. This exploration equips financial institutions with more effective user behavior analysis and risk management tools, thereby fostering future development and application of digital payment technologies.

Contemporary financial systems, despite their inherent complexity and resilience, face significant challenges related to transparency, efficiency, and security. Notable deficiencies in transparency and emerging security vulnerabilities underscore the pressing need for innovative solutions in current financial practices. Hence, this paper introduces a financial distribution system based on a consortium blockchain. Given organizations’ preference for keeping sensitive data private, the partially decentralized nature of consortium blockchains plays a pivotal role in the proposed system’s architecture. Moreover, within this system, the proposed smart contract serves a dual role. It functions not only as a transactional tool but also as a specialized solution designed to improve transactional procedures. Its multifaceted capabilities include ensuring data accuracy, facilitating swift execution, and ensuring adherence to regulatory requirements within the dynamic financial distribution landscape. Through rigorous testing and empirical analysis utilizing the Hyperledger Besu platform, it has been observed that the performance of the proposed system surpasses traditional blockchain frameworks. The results unequivocally demonstrate the proposed system’s proficiency in handling high-frequency financial transactions with minimal computational burden.

Financial bubble prediction has been a significant area of interest in empirical finance, garnering substantial attention in the literature. This study aimed to detect and forecast financial bubbles in the Vietnamese stock market from 2001 to 2021. The PSY procedure, which involves a right-tailed unit root test to identify the existence of financial bubbles, was employed to achieve this goal. Machine learning algorithms were then utilized to predict real-time financial bubble events. The results revealed the presence of financial bubbles in the Vietnamese stock market during 2006-2007 and 2017-2018. Additionally, the empirical evidence supported the superior performance of the Random Forest and Artificial Neural Network algorithms over traditional statistical methods in predicting financial bubbles in the Vietnamese stock market.

Abstract—Annually, approximately 500,000 Merger and Ac- quisition (M&A) transactions are disclosed globally, each trans- action inciting substantial perturbations to the associated com- panies’ equity prices. The probability of an M&A transaction’s closure, as perceived by the public, inherently influences the stock price of the target company leading up to the proposed date of the deal. Given the recent advancements in the realm of Natural Language Processing (NLP), we propose an empirical investigation into the correlation between digital dialogue sur- rounding M&A transactions and consequent movements in the stock prices of involved companies. Utilizing transformer-based encoder-only architectures, we fine tune a stance detection model on an extensive dataset, amassed from digital communication platforms, featuring public discourse related to five historical M&A transactions. Ultimately, we achieved 70% accuracy on deal-completion stance detection using the Roberta-base model. We subsequently employ the aggregated the public sentiment towards the completion or termination of a proposed M&A transaction to model stock price movement. Utilizing a multitude of time-series based approaches, we achieve a mean absolute error of 2.29 USD for next-day price prediction and 3.40 USD for next-week price prediction. Ultimately, we find an existing but tenuous relationship between online discourse and the price trajectory of target companies, ultimately highlighting the complex social and economic phenomena behind M&A deals.Index Terms—Mergers and Acquisitions, Stock prediction, su- pervised learning, neural networks, Recurrent Neural Network, LSTM, stance detection, transformers

In resent years, China’s digital economy has achieved significant global recognition for its instrumental role in supporting sustainable economic and social development. Based on the panel data from China's provinces between 2013-2021, this paper investigates the impact and transmission mechanism of financial deepening on digital economy development. The study finds that financial deepening significantly improves digital economy development. Heterogeneity analysis indicates that financial deepening offers greater support to digital economy development in central and western regions than in the east. Further analysis shows that financial deepening improves technological innovation, which in turn promotes the digital economy development. After applying a test of robustness, the results proved significant.

Globally, over 1.4 billion adult people remain unbanked. This worrisome phenomenon was exacerbated by the outbreak of the COVID-19 pandemic, which further created a new dimension of inequality in accessing financial services. Digital financial inclusion promises to be an effective tool for addressing this socioeconomic ill and propelling economic development. Given the limited studies on the subject in the context of the developing economies, it is imperative to understand the existing policies, practices, and barriers to digital financial inclusion in the developing economies so as to provide cutting-edge interventions for redress. It is against this background that this study seeks to address the following research questions: (1) What is the state of digital financial inclusion in the developing economy? (2) What are the policies and practices regarding digital financial inclusion in the developing economy? (3) What are the barriers to digital financial inclusion and innovative interventions for redress? Findings reveal that about 44% of the adult population in developing countries does not have access to financial services, with only a few countries that have made significant progress and gains through policy and practice such as mobile financial services, mobile money interoperability, native connectivity, human capital development, and digitalization of public services for digital financial inclusion. The findings also identify challenges and implications with recommendations, which are discussed in detail in the paper.

The Centers for Disease Control and Prevention recommends everyone between 13-64 years be tested for HIV at least once as a routine procedure. HIV routine screening is reimbursable by Medicare, Medicaid, expanded Medicaid, and most commercial insurance plans. Yet, scaling-up HIV routine screening remains a challenge. We conducted a scoping review for studies on financial benefits and barriers associated with HIV screening in clinical settings in the U.S. to inform an evidence-based strategy to scale-up HIV routine screening. We searched Ovid MEDLINE®, Cochrane, and Scopus for studies published between 2006 - 2020 in English. The search identified 383 Citations; we screened 220 and excluded 163 (outside the time limit, irrelevant, or outside the U.S.). Of the 220 screened articles, we included 35 and disqualified 155 (did not meet the eligibility criteria). We organized eligible articles under two themes: financial benefits/barriers in healthcare settings (9 articles); and Cost-effectiveness in healthcare settings (26 articles). The review concluded recommendations in three areas: (1) Finance: Incentivize healthcare providers/systems for implementing HIV routine screening and/or separate its reimbursement from bundle payments; (2) Personnel: Encourage nurse-initiated HIV screening programs in primary care settings and educate providers on CDC recommendations; and (3) Approach: Use opt-out approach.

Responding to the influences of climate change, on the one hand, and selected benefits of digital technology, on the other hand, an energy transition of global scale appears to be underway. Many observers project that a significant element of the energy transition will be a growing dependence on electricity, a dependence possibly doubling by 2050. Such a transformation, however, would likely require re-configuring the architecture of complex, centralized electricity grids, an artifact of a context of more than a century ago. In concert with the energy transition, we argue to modify the objective of the electricity grid to enable efficient, pervasive optimization in local service areas that provides incentives for users to be efficient in their energy use. At the core of our argument is the presentation of economic incentives denominated in an electricity-backed commodity currency such that incumbent electricity generators could augment their economic purpose of electricity production and electricity distribution to include financial intermediation. A direct consequence of this institutional transformation is the opportunity for all users to generate wealth. There are others who have been inspired to conjure ways that energy could be a candidate currency. Our argument is distinctive, though, in exploiting how an institution (the power grid system) could be repositioned and how all agents in the system could benefit by the institutionalization of electricity as money.

Cash holding is important for Chinese manufacturing firms coping with the increasing cost of financing and stiff market conditions. This study examines the impact of cash holding on the firm value of Chinese manufacturing firms. We find evidence that a non-linear relationship exists between cash holding and firm value in manufacturing firms of China. The study reveals that financially constrained firms having a higher level of cash holding negatively affects the firm value, while the unconstrained firms having a lower level of cash holding positively influences the firm value. Finally, this research is enriched by adopting the novel measure of managerial op-timism and reveals the interactive role of cash holding and optimism on firm value. The study concludes that managerial optimism influences the firm’s cash holding decisions and this is more costly for unconstrained firms.

Hybrid Classical-Quantum computing has already arrived at several commercial quantum computers, offered to researchers and businesses. Here, applications are made to a model of financial options, Statistical Mechanics of Financial Markets (SMFM). These applications were published in many papers since the 1980's. This project only uses Classical (super-)computers to include quantum features of these models. Since 1989, an optimization code, Adaptive Simulated Annealing (ASA), has been to fit parameters in such models. Since 2015, a path-integral algorithm, PATHINT, used previously to accurately describe several systems in several disciplines, has been generalized from 1 dimension to N dimensions, and from classical to quantum systems, qPATHINT. Published papers have described the use of qPATHINT to neocortical interactions and financial options. The classical space by SMFM applies nonlinear nonequilibrium multivariate statistical mechanics to fit parameters in conditional short-time probability distributions, while the quantum space described by qPATHINT deals specifically with quantum systems, e.g., quantum money. This project thereby demonstrates how some hybrid classical-quantum systems may be calculated quite well using only classical (super-)computers.

(1) Background: The CEO message of hospital homepage contain various contents such as the hospital's future vision, promises with customers, upgraded services and public activities. The CEO’s message of the homepage includes non-financial information as well as financial information of corporates. Also, it provides useful information for not only company's goals and vision but also firm performance and strategies for the future. This study aims to investigate associations between CEO’s message of hospitals homepages and financial status. We used the balanced scorecard frame to analyze what content on the hospital's homepage is related to the hospital's various financial ratios. (2) Methods: We adopt a text mining method to extract significantly repeated keywords from the CEO’s message of hospital website. And we classify these keywords by a balanced scorecard frame. To examine the relationship between keywords of CEO’s message of the hospital homepage and hospital’s financial ratio, T-test is conducted for the difference in the TF-IDF (Term Frequency is Divided by Inverse Document Frequency) mean of the home page contents and its relationship with the views of the balanced scorecard framework. (3) Results: According to empirical results on 65 samples collected from local hospitals, there are some significant relationship between the qualitative content of the hospital's homepage and the quantitative financial ratio that indicates profitability, activity, leverage, liquidity, and transfer to essential business fund (EBF) income. (4) Conclusions: The introduction section of a homepage is most accessible to customers, containing the aims and ideals of hospitals and reflecting their values and visions [1]. In addition, in view of financial status, they can either emphasize financial strength or focus on other areas to mask weakness of financial information. This study reminds us of the importance of hospital website’s disclosure, and it can be inferred from the financial status of the hospital. It also highlights the need for harmonization between quantitative data, financial statements, and qualitative data, CEO’s messages. (5) Implications: To our best knowledge, this paper is the first research attempting to investigate the relation between text of hospital homepage and financial ratio of hospital through text mining technique and balanced scorecard frame. Hospitals take a crucial part in a country’s welfare and healthcare backbone industry. Nevertheless, in many countries, hospital organization sectors tend to remain a source of critical fiscal deficits due to its ineffective and sloppy management. We expect that the result of this paper can provide hospital managers to useful information.

Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations. Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes PATHINT/PATHTREE (and their quantum generalizations qPATHINT/qPATHTREE) are offered to detail such systems. Method: ASA and PATHINT/PATHTREE have been effective to forecast properties in three disparate disciplines in neuroscience, financial markets, and combat analysis. Applications are described for COVID-19. Results: Results of detailed calculations have led to new results and insights not previously obtained. Conclusion: These 3 applications give strong support to a quite generic application of these tools to stochastic nonlinear systems.

Background: Forecasting nonlinear stochastic systems most often is quite difficult, without giving in to temptations to simply simplify models for the sake of permitting simple computations. Objective: Here, two basic algorithms, Adaptive Simulated Annealing (ASA) and path-integral codes PATHINT/PATHTREE (and their quantum generalizations qPATHINT/qPATHTREE) are offered to detail such systems. Method: ASA and PATHINT/PATHTREE have been effective to forecast properties in three disparate disciplines in neuroscience, financial markets, and combat analysis. Applications are described for COVID-19. Results: Results of detailed calculations have led to new results and insights not previously obtained. Conclusion: These 3 applications give strong support to a quite generic application of these tools to stochastic nonlinear systems.

Many countries have been facing the problem of bank insolvency across the globe. Asset deterioration is one of the main reasons for insolvency of banks. The objective of the paper is to ascertain the determinants of nonperforming loans (NPLs) in the banking sector of Pakistan for the period 2006-16. Other than the bank specific and macro variables proposed by the literature, the roles of weighted maturity and output gap are for the first time examined. We find significant impact of output gap on NPLs however weighted maturity has insignificant role in shaping the future NPLs. Bank specific drivers of NPLs include bank size and capital adequacy ratio.

This study compared the performance of five Family Generalized Auto-Regressive Conditional Heteroscedastic (fGARCH) models (sGARCH, gjrGARCH, iGARCH, TGARCH and NGARCH) in the presence of high positive autocorrelation. To achieve this, financial time series was simulated with autocorrelated coefficients as ρ = (0.8, 0.85, 0.9, 0.95, 0.99), at different time series lengths (as 250, 500, 750, 1000, 1250, 1500) and each trial was repeated 1000 times carried out in R environment using rugarch package. And the performance of the preferred model was judged using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Results from the simulation revealed that these GARCH models performances varies with the different autocorrelation values and at different time series lengths. But in the overall, NGARCH model dominates with 62.5% and 59.3% using RMSE and MAE respectively. We therefore recommended that investors, financial analysts and researchers interested in stock prices and asset return should adapt NGARCH model when there is high positive autocorrelation in the financial time series data.

This paper highlights the impact of financial inclusion on individuals’ borrowing and saving decisions in the United States and the United Arab Emirates. It does so, using data from the 2014 Global Financial Inclusion database, and an empirical strategy consisting of first testing the significance of the joint bivariate model over its binary conterparts using the Lagrange multiplier test, followed by a contrast between the fully-parametric and semi-parametric specifications of the saving and borrowing equations. Based on model performance measures, the semi-parametric bivariate probit specification is identified as a better framework for describing the two processes of saving and borrowing, with a correlation coefficient of 12.3%. Although no significant difference exists between UAE and US residents in borrowing behavior, we find that US residents are 31.4% more likely to save than their UAE counterparts. In addition, and in line with the Permanent Income Hypothesis, the results reveal the absence of an income based saving or borrowing gradient in the two countries. Conversely, we found the prevalence of a gender based saving (12.4%) and borrowing (13.8%) inequality in favor of the male gender. Furthermore, access to a bank account and a debit card, companies policy of direct wage and salary transfer, and government transfer programs with direct deposit options are all financial inclusion strategies that are found to significantly raise the likelihood of saving and borrowing. As such, companies with payroll practices based on cash or physical paycheck issuing, especially in the US, should revise such policy to create more financial inclusion, and thereby more saving potential which in turn would contribute to further borrowing, investment and growth of the national economy.

In this paper, we focus on the impact of financial liberalization on stability of emerging stock market. We identify crises in a group of Latin American (Argentina, Brazil and Chile) and Asian countries (Philippines, Korea, Taiwan and Thailand) during 1975–2005. This paper aims to apply the methodology of CMAX method. Our results indicate that liberalization triggers more unstable stock market in the short run and generate several crises. Still, liberalization seems to generate more stable financial markets in the long run. Financial liberalization does not increase the frequency of crises in emerging countries and at long-term, crises are less several.

This research suggests a multi-stakeholder framework to increase the use of fintech in Africa, which would help the continent boost its financial inclusion and reach its Sustainable Development Goals (SDGs). The study evaluates previous research and frameworks that have been created to aid in the adoption of fintech by several stakeholders in developing nations, some of which have been tested in African nations with limited success. To begin with, the study suggests the use of the World Bank’s Maximising Finance for Development (MFD) approach through the prioritization of national ownership, creation of an enabling environment for private sector investment, partnering with multilateral development banks and other stakeholders, fostering innovation and digital literacy, and focusing on cost-effective, non-government guaranteed financing. In the same vein, in line with the G20’s High-Level Principles for Digital Financial Inclusion, the adoption of financial technologies and digital financial services in Africa can be promoted through the creation of a country-specific strategy. Each government can create a regulatory environment that encourages innovation and competition, improve its digital infrastructure, increase its digital literacy and awareness, and collaborate with private sector stakeholders to expand financial inclusion. Furthermore, The Better Than Cash Alliance’s strategy to increase fintech adoption can also be implemented through partnership with businesses, international organizations, and other nations. By joining the Alliance, countries can enact rules and regulations that facilitate fintech adoption, promote awareness and education, and design and execute national digital payment infrastructure with the help of fintech companies. Finally, the mSTAR initiative suggests collaborating with USAID, in order to provide support to underrepresented populations, incorporate digital financial services, increase public-private collaboration, and educate and train policymakers, practitioners, and technologists. By implementing these strategies, African nations can accelerate the adoption of fintech solutions and increase financial inclusion.

In this research paper, we address the critical role of data security in the rapidly evolving FinTech sector. We explore the challenges and strategies for establishing robust data security systems, emphasizing the consequences of data breaches and common vulnerabilities. The paper highlights the efficacy of technologies like encryption, blockchain, and cloud security, supported by real-world case studies from leading FinTech companies. Additionally, we examine regulatory frameworks and standards essential for maintaining data security. Concluding with the proposal of an integrated security system model, the paper underscores the synergy between technological innovation, regulatory compliance, and proactive risk management in the FinTech industry

The financial crisis augmented the need to predict real estate prices. The current study examines the application of Artificial Neural Network (ANN) model and Vector Autoregressive (VAR) model in forecasting real estate prices. The study uses daily observations, which accounted for a total of 2955 observations collected. We found that ANN outperformed significantly the VAR model providing evidence that these models can be used for valuation purposes in the area of real estate and financial markets. These findings are novel and important as they provide evidence of the usefulness of more sophisticated methodologies for market participants and regulators in real estate and financial markets.

Digitalization has fundamentally changed the global economy and will continue to do so. This study investigates how the US Federal Reserve and US Treasury may work together to use decentralized finance (DeFi) systems to promote economic growth in local communities. The study looks into the potential for transformation and the difficulties in incorporating DeFi into conventional financial institutions. Research shows that the use of cash as a means of payment is widely expected to decline in the future. As a result, the public’s ability to make transactions using central bank money may decline rapidly. This study's goals are to solve economic issues, promote innovation, and increase financial efficiency. The use of in-depth interviews, theme analysis, case studies, stakeholder perspectives, comparative analysis, and document analysis is suggested as part of a qualitative research methodology. The goal of these approaches is to offer a sophisticated comprehension of the dynamics of collaboration and the consequences of DeFi integration in the context of the Federal Reserve-Treasury relationship. Important data sources that are necessary to answer the research question are indicated, such as US Treasury statistics, Federal Reserve publications, DeFi platforms, and International Monetary Fund economic indicators. Informed decision-making and policy formation may pave the way for a more inclusive and efficient financial ecosystem, which will eventually drive regional economic growth in the United States and promote monetary sovereignty for the aforementioned monetary entities. This can be achieved by investigating creative collaboration tactics between the Federal Reserve and the US Treasury.

The Ghana Venture Capital Trust Fund (VCTF), a government-sponsored initiative, plays a pivotal role in providing patient capital to foster entrepreneurship and spur economic development, particularly in emerging markets where traditional funding avenues may be limited. This study aims to conduct a comprehensive assessment of the VCTF's financial robustness, growth trajectory, and sustainability over a seven-year period from 2016 to 2022. Through an examination of critical financial metrics, growth indicators, and sustainability benchmarks, we scrutinize the fund's financial health, investment strategies, and capacity to bolster the Ghanaian entrepreneurial ecosystem.The analysis reveals nuanced insights into the VCTF's financial performance over the study period. Despite encountering challenges such as negative net profit margins and subdued asset turnover ratios in previous years, the fund showcases resilience and sustainability, particularly as evidenced by notable improvements in 2022. These findings carry implications for management, policymakers, and various stakeholders within the Ghanaian venture capital landscape, offering valuable insights to inform strategic decision-making and policy formulation.

Financial stress can have significant implications for individuals, businesses, asset prices and the economy as a whole. This study examines the nonlinear structure and dynamic changes in the multifractal behavior of cross-correlation between the financial stress index (FSI) and four well-known commodity indices, namely Commodity Research Bureau Index (CRBI), Baltic Dry Index (BDI), London Metal Index (LME) and Brent Oil prices (BROIL), using multifractal detrended cross correlation analysis (MFDCCA). For analysis, we utilized daily values of FSI and commodity index prices from 16th June 2016 to 9th July 2023. The following are the most important empirical findings: (I) All of the chosen commodity market indices show cross correlations with the FSI and have notable multifractal characteristics. (II) The presence of power law cross-correlation implies that a noteworthy shift in FSI is likely to coincide with a considerable shift in the commodity indices. (III) The multifractal cross-correlation is highest between FSI and Brent Oil (BROIL) and lowest with LME. (IV) The rolling windows analysis reveals a varying degree of persistency between FSI and commodity markets. The findings of this study have a number of important implications for commodity market investors and policymakers.

Hospitals are perpetually challenged by the dual requirements of concurrently improving the quality of healthcare and maintaining financial solvency. Both issues are among the top concerns for hospital executives across the United States, yet some have questioned if the efforts to enhance quality are financially sustainable. led us to examine if improving quality in the hospital setting impacts revenue. Using multivariate regression, we assessed if numerous quality measures were associated with our targeted measure of hospital profitability: the net patient revenue per adjusted discharge. The independent variables included the HCAHPS Summary Star Rating, Hospital Compare Overall Rating, All-Cause hospital-wide Readmission Rate, Total Performance Score, Clinical Outcomes Domain Score, Safety Domain Score, Person and Community Engagement Domain Score, and the Efficiency and Cost Reduction Score. Our results indicated that improving quality was significantly associated with improved net patient revenue per adjusted discharge for seven of the eight of these quality measures at the hospital level. It is clear that failing to address quality and patient safety issues is costly for US hospitals, thus we believe our findings support the premise that increased attention to the quality of care delivered as well as patients’ perceptions of care may allow hospitals to accentuate profitability and advance a hospital’s financial position.

Globally, large numbers of adults remain unbanked and most of them live in rural areas of the Third World. The recent outbreak of the COVID-19 pandemic has shown us how inequalities in accessing financial services continue to affect us. However, financial inclusion has emerged as an effective tool to tackle socioeconomic ills and drive economic development. In fact, due to these modern technological developments, the number of studies in this area is very limited, especially in the context of developing economies. This study examines the impacts of migrant remittances on digital financial inclusion within households using the Migration and Remittance Household Survey in Bangladesh. To meet the research objectives of this study, a household survey was conducted and interviewed 2,165 households in 2022-2023 in Bangladesh. This study finds that the coefficient of remittance has a positive relationship with the probability of using mobile banking for a household's financial transactions. However, the use of ATM cards by households for financial transactions has not been significantly affected. The article concludes that remittance flows may enhance access to and use of digital financial inclusion by reducing some of the barriers and costs in Bangladesh, which can greatly contribute to the country's economic growth by creating and increasing a strong fund for investment.

Microfinance banks and Institutions must simultaneously provide micro financial loans to unprivileged and poor people as well as self-sustaining, which means covering enough costs to eliminate the need for subsidies. To ascertain if Micro-finance Institutions can successfully navigate the double challenge of financial self-sustainability (FSS) as well as outreach to poor clientele and women borrowers i.e. outreach. There is no other alternative but to analyse the balance between FSS and outreach indicators of MFIs. The research goal is to see whether there was any compromise between the self-sustainability and outreach towards poor and female customers. The study used data of 100 MFIs driven from the database of microfinance information’s exchange (MIX) market with the objective to determine trade off between financial sustainability and outreach. The study found financial performance variables are positively and significantly related with average loans size which shows a mission drift, in which MFIs serve wealthy clientele. However, Indian MFIs have a extremely high outreach with their female clientele, confirming MFI's social commitment to objective of women’s empowerment. The research recommends to the Policy-makers that MFIs are compromising their financial services to underprivileged people and women in order to be financially sustainable. To guarantee that institutions are focused on outreach to underserved people in rural areas, the government should reform the policies regarding governing MFIs.

This research was conducted with the aim of knowing how to compare the financial performance of the oil and gas trading industry with cross-sectional analysis techniques. The type of research conducted in this research is qualitative research with research objects at several companies, namely PT Radiant Utama Interinsco Tbk, PT Elnusa Tbk, PT AKR Corporindo Tbk, and PT Aneka Gas Industri Tbk. The data used in this study comes from secondary data, namely the internet in the form of company financial reports for the 2019-2021 period obtained from the Indonesia Stock Exchange. The results of this study indicate that PT Radiant Utama Interinsco Tbk has the best financial performance on inventory turnover ratio and average age, PT Elnusa Tbk has good inventory performance on current ratio, quick ratio, DAR, and DER., PT AKR. Corporindo Tbk has performed well on the ratios of TIE, FCC, Dividend Payout, Dividend Yield, and PER. PT Aneka Gas Industri Tbk has performed well on the ratio of Receivables Turnover Ratio and Average Age of Receivables.

The effects of the 2008 financial crisis undoubtedly caused problems not only to the banking sector but also to the real economy of the developed and the developing countries in almost all around the globe. Besides, as is widely known, every banking crisis entails the corresponding cost to the economy of each country affected by it, which results from the shakeout and the restructuring of its financial system. The purpose of this research is to investigate the consequences of the financial crisis and the COVID-19 health crisis and how these affected the course of the four systemic banks (Eurobank, Alpha Bank, National Bank, Piraeus Bank) through the analysis of ratios for the period of 2015-2020.

The study's motivation is to gauge the nexus between economic policy uncertainty and financial innovation for the period 2004M1 to 2018M12 in BRIC nations. For establishing a long-run cointegration study applied Autoregressive Distributed Lagged (ARDL) and asymmetry effects of economic policy uncertainty investigated following nonlinear framework known as NARDL. Furthermore, directional causality is established by performing a non-granger causality test. Cointegration test results of Fpss, Wpss, and tBDM confirmed the long-run association between EPU and financial innovation. On the other hand, the Wald test results proved asymmetry effects furring from EPU to financial innovation both in the long-run and short-run. Referring to asymmetry effects that positive and negative shocks in financial innovation, the study revealed that negative linkage between shocks in EPU and financial innovation in the long-run but short-run effects are insignificant. Furthermore, financial innovation measured by R&D investment exhibits positive linked with shocks in EPU, implying that uncertainty induces innovation in the economy. Refers to directional causality estimation, the study revealed evidence supporting the feedback hypothesis between EPU and financial innovation in all sample countries.

Numerous studies in the literature have investigated the effect of financial development on poverty, and tend to report a poverty reduction effect of financial development. The present paper considers the issue in the other way around, by examining the effect of poverty on financial development. In particular, it has investigated the financial development effect of poverty that passes through three main channels, including the education level, the level of trade openness, and the degree of export product concentration. The analysis is carried out using a sample of 97 developing countries over the period 1980-2017, and the two-step Generalized Methods of Moments (GMM). Results have shown that poverty genuinely affects financial development through these three channels. Specially, lower poverty rates induce greater financial development in countries that experience higher education levels. Similarly, a rise in poverty rates in the context of restrictive trade policies (that eventually result in lower levels of trade openness) undermines the development of the financial sector. Finally, higher poverty levels adversely affect financial development in countries that experience an increase in the level of export product concentration.

The paper investigated the components of savings accumulation in Nigeria over the period 1980 to 2017. Secondary data were collated from World Development Index (WDI). In evaluating the objectives, the study employed the Auto Regressive Distributive Lag (ARDL) and Vector Error Correction Model (VECM) estimation methods. The key findings of the study show that the components of savings identified in literature understudied in the paper specifically, GDP per capita, foreign direct investment, financial deepening, interest rate, inflation rate exchange rate significantly influence savings accumulation in Nigeria either in short run, long run or both. Financial deepening was found statistically significant but influences savings negatively. Inflation rate was statistically insignificant although negative. The result from the VECM causality test revealed that short run and long run causal relationship exist between savings and the afore mentioned components in Nigeria. Hence, the study recommends careful manipulation of the identified savings components in a manner that they will not yield a counterproductive result in the economy rather contribute to the growth of savings and ultimately, the growth of Nigeria economy as a whole. It further recommends that the Nigerian government through its financial institutions encourage savings from both small and big savers which to large extent will assuage the perceived undeserved influence of financial deepening on savings accumulation.

This paper analyzes if the Financial Fair Play (FFP) regulations set by UEFA have influenced the auditing fees charged to the football clubs. In addition, it explores the determinants of audit fees. We use a two-sample t test with equal variances to determine whether differences are present. After this, we carry out a panel data regression with clubs fix effect to estimate the determinants of audit fees in football clubs. Our findings reveal an increase of audit fees after the implementation of FFP regulations. On top of that, audit fees are explained by the presence of foreign investors if the audit firm is one of the Big4 and if the auditor is a woman. The regulation change has an impact on the audit fees charged by auditors for their services. However, this increase can be compensated across future years given the improving financial situation of clubs; therefore, the auditors’ risk diminishes and subsequent audit fees may be reduced. UEFA should monitor audit fees as well as the quality of the audit reports, which have become crucial to obtaining the license to participate in UEFA competitions.

Over the past decade, the credit quality of loan portfolios across most countries in the world remained relatively stable until the financial crises hit the global economy in 2007–2008. In this paper I discuss, the relationship between non-performing loans and economic landscape. Since 2008, nonperforming loans have been an increasingly hot topic in the international scene, due to their important and rising volume and their impact on the economy as a whole, on the banking system and on its credit supply. Since then, average bank asset quality deteriorated sharply due to the global economic recession. Yet the deterioration of loan performance was very uneven across countries. I am interested in explaining these differences in bank asset quality across countries and over time. In this paper, I therefore study the empirical determinants of non-performing loan (NPL) ratios using a data set for EU countries covering the past decade. The paper assumes that the spatial organization of banking systems and the geographical distribution of comercial banks branches, ATMs and GDP growth are major factors influencing the effectiveness in credit system. The aim of this paper is to construct a continuous and quantifiable model, which will demonstrate a role of economic condition, technology, competition, policy, business climate in Financial Stability. Main hypotheses suggests, that GDP growth, interest rate, new business, FDI, ATMs and geographical distribution of branches have an influences on NPL (non-performing loans).

The relationship between economic growth, growth volatility and financial sector development continues to attract attention in the theoretical and empirical literature. Over time, some studies hypothesize that finance has a causal linear relationship with growth. Recently several other authors contradict this claim and argue that the relationship that exists between finance and growth is nonlinear. We investigate these claims for Nigeria for the period between 1970 and 2015, using semi-parametric econometric methods, Hansen sample splitting techniques and threshold estimator. We observed no evidence of ‘Too much finance’ as claimed by many researchers in recent times. We show that the relationship between financial development and economic growth is U-shaped. This is equally true for the relationship between financial development and growth volatility. We also discuss policy implications of our findings and recommend financial innovations and decentralization of stock exchanges to boost access to financial services, in addition, improved regulation to enhance financial market efficiency.

The striving for sustainable development has become the goal of actions undertaken not only by representatives of public authorities and institutions representing this sector, but also representatives of private entities who are increasingly recognizing the benefits and sources of long-term development based on the principles and objectives of sustainable development. These are mainly based on the pursuit of synergy in the three basic areas of activities, i.e., in the economic, social, and environmental dimensions as well as in the maintenance of natural resources. The implementation of these activities is connected with the necessity of incurring financial expenditures, which the government (public sector) does not have in the required value. Therefore, in the process of sustainable development for which the government is responsible, the active participation of the financial sector (banks) is necessary. Achieving results within the alliance of the concept of sustainable development requires the setting of a kind of contract, the parties of which are the government, society, and financial institutions. The purpose of the conducted research is to indicate by which means the government and the financial sector can stimulate economic growth towards its sustainable development.

The financial inclusion, including all the people with the finance, is very concerned issue all over the world where Bangladesh is also trying to include all the people with the finance. Bangladesh lies in such a group of countries where only 17.6% - 38.6% adults are presently under the reach of the formal financial services. This is because the present banks and other formal financial modes consider the outcome and profitability in a way that, the rural and non-developed areas are always out of the consideration. But these areas consist of the most population of Bangladesh. And only then financial inclusiveness will be successful in Bangladesh when people from these regions will be under formal financial consideration. The paper seeks for a solution to the issue and presents the Unit Banking System as a probable way towards financial inclusion. For implementing the system in Bangladesh, the system needs a slight modification to cope in Bangladeshi economic condition and address the specific needs without hampering the surroundings. Considering all these, the paper shows the status, problems and key points of financial scenario of inclusion in Bangladesh and shows policy for a Modified Unit banking System.

This paper relies on accounting-based measures of country risk to investigate U.S. global banks' exposure to foreign country risk over the 2017 fiscal year as measured by the sum of cross-border risk, foreign office risk, and derivative risk claims. We achieve this using panel linear modeling methods with country level heterogeneity and time fixed effects, along with a constructed panel data of 284 observations on 71 countries distributed across 6 world regional blocks, and observed over 4 consecutive quarters starting from 4th quarter 2016 and ending with 3rd quarter 2017. The results show that on average, over the four quarters, a 1% increase in foreign banking sector's claims significantly increases U.S. global banks cross border risk exposure by 0.34%, while reducing derivative risk exposure by 0.22%, but have no significant impact on foreign office risk exposure. Similar results are observed with public sector claims which significantly increase banks' exposure to cross border risk by 0.21%, while reducing derivative risk exposure by 0.19%. Conversely however, non-bank financial sector claims are found to have no significant affect on cross-border risk exposure, but significantly reduce foreign office risk exposure by 0.09%, while increasing derivative risk exposure by 0.06%. These results indicate the presence of sectoral heterogeneities in U.S. banks' exposure to foreign counterparties' risk, and also that overall, over the course of 2017 the level of U.S. global banks' cross-border risk exposure increased, while their level of derivative risk exposure decreased, and the level of foreign office risk exposure remained relatively unchanged.

An optimal withdrawal strategy beginning at age 65 provides a lifetime income from a portfolio, adjusted annually for inflation, while reducing the probability of living in financial ruin to an ac-ceptable level. This paper analyzes the probability of living in financial ruin, potentially for multiple years, rather than just the event of ruin. A stochastic Excel model was developed to simulate the effect of varying investment returns on a portfolio with two asset classes; large company stocks and long-term government bonds. A stochastic model is also applied to retiree mortality. The following variables were analyzed to determine their relative impact on withdrawal strategies: • Withdrawing a constant percentage of the portfolio, • Gender, • Initial asset allocation, • Asset allocation rebalancing methods, and • Low investment return environments. For both genders and most withdrawal rates, an approximately equal initial asset allocation of stocks and bonds, combined with a level rebalancing function, provided the lowest probability of living in financial ruin. Because each investment return followed its own probability distribution function, some retirees experienced financial ruin even in the most conservative simulations.

This paper attempts to assess the economic significance and implications of collateralization in different financial markets, which is essentially a matter of theoretical justification and empirical verification. We present a comprehensive theoretical framework that allows for collateralization adhering to bankruptcy laws. As such, the model can back out differences in asset prices due to collateralized counterparty risk. This framework is very useful for pricing outstanding defaultable financial contracts. By using a unique data set, we are able to achieve a clean decomposition of prices into their credit risk factors. We find empirical evidence that counterparty risk is not overly important in credit-related spreads. Only the joint effects of collateralization and credit risk can sufficiently explain unsecured credit costs. This finding suggests that failure to properly account for collateralization may result in significant mispricing of financial contracts. We also analyze the difference between cleared and OTC markets.

This study looked into how financial knowledge and entrepreneurial proficiency affected the performance of small, sustainable businesses. In parallel, we looked at how business resilience mediated the relationship between entrepreneurial proficiency and financial knowledge and long-term company success. Using an offline questionnaire, we employed a quantitative approach to gather data from 275 Indian small company owners. PLS-SEM was used to analyse the data that had been gathered. The findings show that resilience and entrepreneurial ability are very positively impacted by financial knowledge. The business resilience and sustainable performance of Indian SMEs are significantly enhanced by entrepreneurial competencies. Moreover, it was shown that business resilience moderated the influence of financial knowledge and proficiency on sustainable performance among Indian SMEs, while concurrently having a significant impact on sustainable performance. In keeping with India Vision of Viksit Bharat@2047: Crystal Gazing Through MSME Sector, which places a strong emphasis on entrepreneurship and the growth of a financially independent entrepreneurial community, this study helps to open up business options for regional business owners who oversee small businesses. According to the most recent figures (2021–2022) from the Ministry of Statistics & Programme Implementation, MSMEs make up a startling 29.15% of India’s GDP. This indicates their critical significance in the development of the country as it equates to a sizeable portion of the economic pie. In addition to adding to the corpus of knowledge, this research can help policymakers develop relevant plans to motivate SMEs that have been most negatively impacted by the COVID-19 pandemic to operate sustainably. There are also several other ramifications for financial institutions and business owners.

The financial performance of local governments is closely related to the economic growth of a region. Strong financial performance provides a solid foundation for sustainable economic development. This study analyses the relationship between local government financial performance, capital expenditure, and sustainable economic growth in Banten Province. A quantitative approach was employed, using secondary data from Regional Revenue and Expenditure Budgets and economic growth statistics. Purposive sampling was utilised, and data analysis was conducted using Path Analysis. The findings reveal that several financial ratio variables significantly impact economic growth directly and indirectly through capital expenditure as a mediating variable. Directly, the independence ratio, effectiveness ratio, efficiency ratio, fiscal decentralisation ratio, dependency ratio, and capital expenditure significantly influence economic growth. The independence and effectiveness ratios have a positive impact, indicating that improvements in these variables directly foster economic growth. However, the efficiency and fiscal decentralisation ratios have a negative impact, suggesting that increases in these variables may reduce economic growth. Indirectly, through capital expenditure, the independence, effectiveness, dependency, and compatibility ratios significantly affect economic growth, with the independence ratio being the most dominant. Conversely, the fiscal decentralisation and efficiency ratios do not show significant indirect effects, indicating that capital expenditure is not an effective mediator for these variables.

Objective: The long-term care insurance (LTCI) system was introduced in 2000 to provide financial support for long-term care services to older adults. What is known on this topic report focuses on a comparative analysis of how the LTCI system has affected older people in Japan. Methods: We obtained data from the literature about the LTCI system, compared and analysed the collected articles, and concluded. Results: The LTCI system has improved access to long-term care services, with more older adults receiving care than before the system’s implementation. This service has improved the quality of life for many elderly individuals who require assistance with daily activities. Furthermore, the LTCI system has alleviated the financial burden of long-term care services since the insurance covers a large portion of the costs. It has made older adults maintain their independence and dignity, as they can afford the necessary care without relying solely on their savings or burdening their families. Conclusions: Japan’s LTCI system has positively impacted older adults by improving access to long-term care services and alleviating financial burdens. However, challenges such as increasing demand and variations in service quality need to be addressed to ensure the system effectively supports older people in Japan.

The primary objective of this study is to examine the extent of financial integration between Latin American and US financial markets, particularly in light of recent efforts to foster integration through trade agreements. Spanning from January 1, 1990, to December 31, 2019, the sample focuses on major market indices and key sectors. Financial integration is quantified using a DCC multivariate GARCH model, incorporating a smooth transition model, structural breaks, and regression-based approaches. Results indicate increased comovement with the US for main market indices in Argentina, Chile, Colombia, Mexico, and Peru, while Brazil shows a decrease. Similar trends are observed in sectoral analyses. The study also reveals heightened correlation post-trade agreements. Structural break analysis highlights significant shifts in dynamic correlations for countries with US free trade agreements. These findings support the argument of increased financial integration, bearing significance for portfolio diversification and international policy formulation.

The purpose of this study is to bring out a scientometric analysis of the advances of digital transformation in the global banking sector. For this, a background search of the term "Digital Transformation Banking " has been brought out from the Web of Science (Wos) Database, covering records published between 2002 and 2023. A set of 312 publications was identified, which mainly includes a set of 264 academic articles, 29 articles published without cataloging a specific volume of a journal, 9 articles under review, 5 editorial material documents, 4 conference articles, and 1 document is a book chapter. Nowadays the scientific production is low but showing growing development presenting 123 publications and 7,754 citations for the year 2022. Among the scientific production, 43 publications from the Republic of China (8.8%) and 35 publications from Ukraine (7.8%) stand out. ,2%). It is also worth mentioning that the most relevant authors on this topic are Ricardo Palomo, professor and dean of San Pablo University, and Robert J Kauffman, professor at Singapore Management University in terms of influence. Main institutions in terms of scientific production, mainly: the Massachusetts Institute of Technology (MIT) of the United States and the Russian Academy of Sciences of Russia.

Amidst China's new economic normal, the real economy faces various domestic and global challenges. Technological innovation, with its capital intensity and uncertain returns, is crucial to rejuvenate emerging industries and revamp the industrial structure. Meanwhile, financial agglomeration plays a dual role: directly fostering real economic development and indirectly affecting it through technological innovation. This study analyzes data from 30 mainland Chinese provinces and cities between 2011 and 2018, utilizing fuzzy matter-element analysis and location entropy method. Relying on a spatial econometric model, we explore the impact of technological innovation and financial clustering on real economic growth, including spatial ripple effects. The conclusions are derived from Chinese evidence and offer valuable insights into the evolving innovation and financial dynamics within the participating nations.

This paper aims to discuss the relationship between financial development and inflation in Kenya using time series data between 1973 and 2021. The short- and long-run impact of financial development on inflation remains an important issue in the empirical and theoretical literature especially for country specific, but has yet to receive significant research consideration. For this purpose, the paper uses an ARDL analysis method, which is considered an advanced analytical model. Empirical findings confirmed that financial development has a significant long-run impact on inflation in Kenya. On the contrary, results confirmed that there is no significant short-run effect of financial development on inflation. In addition, there is significant long-run and short-run negative relationship between interest rate and inflation. The results indicate significant long-run Granger and ARDL causality from financial development to inflation. The main policy implications of the empirical results of this paper suggest supervision of financial sector must be directed in a way that would stimulate a stable and a moderate inflation rate. In particular, both financial institution and government should enhance the infrastructures of the financial market and promote the utilisation of financial services.

The purpose of this study was to evaluate the financial performances of the publicly held healthcare companies in crisis periods in Türkiye. The 2018 Economic Crisis and the COVID-19 pandemic crisis were included in the study as the crisis periods. We collected the financial data of the publicly held healthcare companies and calculated three liquidity, three turnover, three leverage and three profitability ratios by ratio analysis to use as financial performance indicators. We then conducted Wilcoxon signed-rank tests and we did separate analyses for the 2018 Economic Crisis and the COVID-19 pandemic crisis. The results of the analyses showed that there were no statistically significant differences between the publicly held healthcare companies’ liquidity, turnover, leverage, profitability ratios and thus their financial performances before the crises and after the crises. While the results are reassuring and give valuable insights to managers and policy makers to determine the areas that needs to be strengthened to be better prepared for possible future crises, our sample was limited. Therefore, this study presents an exploratory foundation for future studies which are needed to make a case of financial stability for the publicly held healthcare companies before and after the crisis periods.

The purpose of this original study is to critically analyze the emergence and development of the national models of financial regulation; international standards and codes; regional and national financial regulation and supervision (the case of UK, USA, Sweden, EU and Finland). The research raises both academic and regulatory concerns. It aims at shaping changes (innovations) in the supervisory practices of national and international regulators in response to new developments in FinTech markets, digital products, financial instruments and risks. Secondly, it will stimulate more systematic work on regulatory databases, registration and reporting procedures in various economies in different financial markets. The author identifies five main systems of national financial regulatory markets: the multi-tiered, multi-agency US system; the Twin Peaks model (UK); the mega-regulatory model (Sweden). There is a thorough review of international standards and institutions that work for the stability of financial systems. The analysis of regional and national systems of financial regulation and supervision is based on the examples of the EU and Finnish institutions. National macro and microeconomic regulation and supervision have been examined with a focus on the US Federal Reserve and the US Treasury. National and international regulatory institutions have been evolving along several lines. First, minimum capital and credit risk requirements for banks (80s of the 20th century) are complemented in the 21st century by buffer reserves, liquidity and leverage standards. Second, regulation focuses on ensuring the sustainability of the national economy. The regulatory focus is on ensuring the sustainability of national and global financial systems. Third, there is an increase in the number of supervised institutions. Fourth, there is a division of functions between central banks (macroeconomic regulation) and one or two mega-regulators (microeconomic regulation and supervision). Fifth, there is a division of labour between the international financial institutions (BIS, IMF, WB) and national regulators. Sixth, the focus is on protecting consumers and investors, and countering money laundering and the financing of terrorism. Seventh, there is an understanding for a common approach by central banks to new financial technologies and cybersecurity.

Since the early 21st century, the globalization trend and technological innovations have changed the ways and speed of market growth. Rapid market expansion and the pressure for firms to achieve sustainable business growth via mergers and acquisitions have become the norms for acquiring the necessary competencies, expanding market shares and business integrations. This study explains the factors that correlate to the IJM's financial performance based on the market dynamics in recent years. This case study is a qualitative approach employing systematic review and content analysis. As a result, firms begin to diversify or venture into the business segments that might be related to or complement their core businesses, intentionally or unintentionally, which eventually evolved into the conglomerate form. This case study provides a financial performance analysis of IJM Corporation Berhad's success and challenges from its conglomerate business model. The fact that a well-diversified firm will have better risk management in the event of an economic downturn is also a primary driver for firms to embark on a corporate diversification strategy. This case study reveals IJM's conglomerate model has been successful during its rapid business growth; however, it has shown signs of diminishing in recent years.

Cost-effective community engagement is needed to address causes of mental illness related to social issues (i.e. isolation, stigma and lack of purpose) that are typically outside the scope of healthcare. This pilot study evaluated the relationship between clinical healthcare resources and a community-based social engagement organization in a medium-sized community in the midwestern US. Analyses were based on a retrospective longitudinal comparison of clinical visit frequency from two cohorts that joined the Momentum Center for Social Engagement (MC) and either frequently participated (Engaged; n = 9) or had extenuating circumstances limiting participation (Non-engaged; n = 3). The frequency of >1800 visits to the member’s primary mental healthcare provider were compared during the period from November 2016 - May 2021. Engaged MC members reduced frequency of regular visits to their primary mental healthcare provider by 50%, while Non-engaged MC members maintained clinical visit frequency. The financial value of reduced healthcare visits and associated wellbeing improvements was estimated to be $1.0 million, 95% CI: [$0.6-1.4 million], or roughly four times the budget received by the MC from the healthcare provider. Thus, the MC appears to be a valuable approach to improving mental health in conjunction with existing community healthcare services. Clinical implications include considering the unique MC-style community-based support as a component of practice.

The Covid-19 health crisis and its related confinement measures and policies has had a significant impact on the telework adoptions rates, where many businesses were affected abruptly without being prepared, resulting in numerous ad-hoc applications especially while assessing employee’s performance and productivity while working remotely. The difficulties that have emerged with the pandemic have revealed the fragility of the traditional performance appraisal process and the unintentional existence of proximity bias. The Lebanese liquidity crisis is an ongoing financial crisis affecting Lebanon that became fully apparent toward late-2019 when large demonstrations erupted amid acute political instability and economic challenges. In light of the compounded simultaneous occurrence of recurring episodes of COVID-19 outbreaks and the ongoing country’s financial liquidity crisis, the standing of the Lebanese banking sector – who played key roles in the Lebanese economy and were long considered as financially sound and stable – has drastically changed. Faced with such a situation, Lebanese commercial banks started contracting both their branch network and human capital base, and thus they been forced to rethink their human capital strategies by implementing new practices allowing them to adapt to this context of crisis. It is in this perspective that the present research work is inscribed, where we explore the main managerial practices and processes implemented within top Lebanese banks to assess their employee’s performance during the compounded simultaneous crises. A thematic qualitative analysis method of an exploratory nature was adopted, and semi-structured interviews were conducted with senior managers from top Lebanese commercial banks. Results were processed using a deductive approach for themes identifications. Accordingly, it was concluded that in such times of acute crisis, Lebanese banks have altered the purpose of their Performance Appraisal Review (PAR) process and have implicitly or explicitly adopted a Forced Ranking method to primarily focus on retaining just the top performers, while placing those at the bottom on probation with the risk of termination.

For the majority of the contractual arrangements used in construction projects, the owner is not responsible for the cost deviations due to the variability of labor productivity or material price, amongst many other aspects. Consequently, the cost performance of a project may be entirely distinct for the owner and the contractor. Since the majority of the quantitative research on cost estimation and deviation found in the literature adopts the owners’ perspective, this research provides a contribution towards modelling costs and cost deviation from a contractors’ perspective. From an initial sample of 13 residential building and 10 office building projects, it was possible to develop models for cost estimation at the early stage of development including both endogenous and exogenous variables. Although the sample is relatively small, the authors were able to fully analyze all the cost data, using no secondary sources of data (very frequent in cost modelling studies). The statistically significant variables in the cost estimation models were the areas above and below ground and the years following the 2008 financial crisis, including the international bailout (2011-2014) period. For estimating the unit cost, a nonlinear model was obtained with the number of underground and total floor, the floor ratio and the years following the 2008 financial crisis, including the international bailout (2011-2014) period as predictors. For the office buildings, it was also found a statistically significant correlation between the cost deviation and the number of underground floors.

The impact of organizational accreditation and professional certification and the evidence-based measurable impact of those for both academic programs and affiliates is one of specific interest to universities and individuals in the healthcare management field [1]. The authors’ analysis examined the impact of hiring graduates from higher education programs that held external accreditation from the Commission on Accreditation of Healthcare Management Education (CAHME). Graduates’ affiliation with the American College of Healthcare Executives (ACHE) professional healthcare leadership organization was also assessed as an independent variable. Study outcomes focused on these graduates’ respective healthcare organization’s performance measures (cost, quality, and access) to assess the researchers’ inquiry into the perceived value of a CAHME-accredited graduate degree in healthcare administration and a professional ACHE affiliation [2]. The results from this study found no effect of CAHME accreditation or ACHE affiliation on healthcare organization performance outcomes. The study findings support the need for future research surrounding healthcare administration professional graduate degree program characteristics and leader development affiliations, as perceived by various industry stakeholders.

Abstract: Seismic performance and loss assessments can have widely varying degrees of uncertainty. An essential issue is whether a particular assessed seismic loss or performance result has sufficient reliability to serve as the basis for risk management decisions and actions, including whether or not a code prescribed performance level is met, or if an assessed loss level is acceptable. A method is developed measuring the reliability of performance and loss assessments for individual buildings and for portfolios. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the evaluation, and the technical validity of the assessment procedure or model. The approach characterizes the uncertainty of each component of the assessment procedure for each building in qualitative terms. The resulting reliability measure is likely to be most useful for the cases where an entity is determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low risk of seismic damage loss over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.

The objective of this paper is to assess the potential for potable water savings due to rainwater use in a precast concrete factory in southern Brazil. The economic feasibility and the rainwater quality were also assessed. The current water consumption, future water demand and rainwater demand in the factory were estimated. The future demand considered was two times higher than the current water consumption since there are plans to increase the production. Three scenarios were then simulated using the computer programme Netuno. The ideal rainwater tank capacity, the potential for potable water savings and the economic feasibility analysis for each scenario were estimated. Samples of rainwater were collected in the factory and tested for quality for manufacturing precast concrete. For a rainwater tank capacity equal to 25,000 litres, the potential for potable water savings for the first scenario was 55.4%, but the first scenario was considered economically unfeasible. For the same tank capacity, the second and third scenarios presented viable results regarding potable water savings and payback. As for the rainwater quality, it was proven to be adequate for manufacturing precast concrete. The main conclusion is that rainwater can be used to manufacture precast concrete in the factory studied herein.

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

Online transactions are becoming more popular in present situation where the globe is facing an unknown disease COVID-19. Now authorities of Countries requested peoples to use cashless transaction as far as possible. Practically it is not always possible to use it in all transactions. Since number of such cashless transactions have been increasing during lockdown period due to COVID-19, fraudulent transactions are also increasing in a rapid way. Fraud can be analysed by viewing a series of customer transactions data that was done in his/her previous transactions. Normally banks or other transaction authorities warned their customers about the transaction If any deviation is noticed by them from available patterns. These authorities think that it is possibly of fraudulent transaction. For detection of fraud during COVID-19, banks and credit card companies are applying various methods such as data mining , decision tree, rule based mining, neural network, fuzzy clustering approach and machine learning methods. These approaches is try to find out normal usage pattern of customers based on their past activities. The objective of this paper is to find out such fraud transactions during such unmanageable situation.Digital payment schemes are often threatened by fraudulent activities. Detecting fraud transaction in during money transfer may save customers from financial loss. Mobile based money transactions are focused in this paper for fraud detection. A Deep Learning (DL) framework is suggested in this paper that monitors and detects fraudulent activities. Implementing and applying recurrent neural network on PaySim generated synthetic financial dataset, deceptive transactions are identified. The proposed method is capable to detect deceptive transactions with an accuracy of 99.87%, F1-Score of 0.99 and MSE of 0.01.

This study investigates the impact of global financial crisis and the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of global financial crisis and the present COVID-19 pandemic on crude oil futures market. This investigation of the impact of global financial crisis and the COVID-19 on crude oil futures has not been much studied at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. Daily crude oil futures used in this study covers the period from the 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered from 2ndJanuary 2000 to 26th April 2020 . The global financial crisis period covered from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered from 1st January 2020 to 27th April, 2020. The study used both student t and skewed student t innovations with AIC, goodness-of-test fit and backtesting to select the best model. Most of the estimated ARMA-GARCH models are supported by skewed student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting.This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in other to survive and be sustained during financial and health crisis.

This article comprehensively explores multiple aspects of cryptocurrencies and their price forecasting. Firstly, the article introduces the definition of cryptocurrency and its development process on a global scale, especially focusing on the launch of Facebook Libra and China's central bank digital currency, highlighting the importance and influence of digital currency in the global financial market. Subsequently, the article analyzes the advantages of digital currencies over traditional currencies, including improving economic transaction efficiency, reducing transaction costs and enhancing transaction transparency. Meanwhile, the article also explores the challenges and risks potentially brought by the development of digital currencies, such as regulatory uncertainty and market volatility. In this context, the article raises the importance of cryptocurrency price forecasting and introduces the forecasting models and techniques commonly used today. Finally, through specific experimental analysis, the effectiveness of using the deep learning model CNN-LSTM to predict the price of Bitcoin is demonstrated, and the directions of future research and optimization strategy are proposed. In summary, this paper comprehensively presents the research status and prospects of cryptocurrency and its price prediction field through systematic introduction and analysis.

The present study discusses how adopting cryptos affects financial inclusion in developing economies. Primary constructs like Financial Inclusion (FI), Perceived Economic Empowerment (PEE), Trust in Financial Institutions (TFI), User Satisfaction (US), and Cryptocurrency Adoption (CA) were tested through Structural Equation Modeling (SEM). The results indicated that CA significantly and positively influenced FI, US, TFI, and PEE. These relationships extend to the interaction effects: US, TFI, and PEE all positively related to FI. It is a reflection of cryptocurrencies as an opportunity to redress most of the afflictions characteristic of traditional finance systems and to promote financial inclusion and economic empowerment in developing countries. Future research should also investigate whether digital literacy and regulatory environments support cryptocurrency access.

The main objective of this study is to analyze the impact of investment in Research & Development on the performance and value of companies, that is, to try to explain how R&D investment influences the companies’ performance. For this purpose, a dynamic panel data model was estimated using the Generalized Method of Moments, which made possible to measure the impact of R&D investment on performance through the Return on Operating Assets ratio for the Portuguese companies that invested the most between 2012 to 2019. The results show that the investment in R&D is not statistically significant in explaining the operating return on assets. However, the lagged financial performance in one period, the leverage, the asset turnover ratio and the accounts payable turnover show to have impact on the variable under study.

We use the Maximum Overlap Discrete Wavelet Transform (MODWT) to analyse the interconnectedness between the stock markets of continental Europe and the BRICS countries. More specifically, we examine the presence of financial contagion in the stock markets of Brazil, Russia, India, China, and South Africa subsequent to the EuroZone Sovereign Debt Crisis (EZDC). We find evidence of co-movement and volatility spillover at short time scales between the Eurozone equity market and the equity markets in South Africa and Russia, with the Eurozone stock market leading the BRICS markets. The presence of co-movement in short time scales is indicative of the presence of financial contagion. No financial contagion is observed in the Brazilian, Chinese, and Indian stock markets during the European sovereign debt crisis. The absence of financial contagion observed in these three BRICS countries during the European sovereign debt crisis suggests that policymakers in these countries should prioritise addressing idiosyncratic shock channels.

As prominent oil producers, the Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world's attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC's economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. The study employs quantile regression, a powerful statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several important insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th) -83537.3 and the higher quantile (90th) -549002.3. The relationship between GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth-environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a stronger negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. The study's outcomes hold crucial policy implications for the GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions

Purpose: The pandemic, named COVID-19, which shook global economy, production and trade has equally affected the social and domestic lives of ours. In this study the COVID-19’s impact has been investigated on lack of social interaction, financial stress and how it influences the domestic violence in a developing country like Pakistan. The study focuses on some of the important factors that are root causes of increased domestic violence in Pakistan. Design/methodology/approach: The study is quantitative and survey questionnaire has been conducted for structural equation modelling (SEM) to evaluate the hypotheses. The modified scale was validated using confirmatory factor analysis, the Purposive and snowball sampling technique is used for collecting data from 200 respondents of Punjab Pakistan for data analysis through SPSS and SmartPLS. Findings: It is revealed that Covid 19 has a significant effect on lack of social interaction and financial stress. Moreover, lack of social interaction and financial stress also enhances domestic violence. Finally, lack of social interaction and financial stress mediates COVID-19 and domestic violence. Originality/value: This study appears to be frontier research which determines the impact of COVID-19 on lack of social interaction, financial stress and domestic violence particularly in a developing country like Pakistan.

This study explores the capital structure determinants of Korean firms over an extensive period (1995-2021), encompassing both stable and crisis conditions. Employing a dynamic panel data model and the Generalized Method of Moments (GMM) estimation, we address the endogeneity issue introduced by the inclusion of lagged dependent variables. Our research integrates firm-specific internal factors with macroeconomic external variables to provide a comprehensive understanding of the influence of varying economic environments on capital structure. Our study suggests that in times of economic stability, the capital structure decisions of a firm are more influenced by internal factors such as profitability. However, in periods of economic downturns, it's the external macroeconomic market conditions that tend to have a greater impact on these decisions. It's also noteworthy that both book leverage (BL) and market leverage (ML) exhibit quicker adjustments during stable periods as opposed to periods of crisis. This indicates a higher agility of firms in adapting their capital structures in stable normal conditions. Our findings contribute to existing literature by offering a holistic view of capital structure determinants in Korean firms. They underscore the necessity of adaptable financial strategies that account for both internal dynamics and external economic conditions. This study fills a gap in current research, presenting new insights into the dynamics of capital structure in Korean firms and suggesting a multifaceted approach to understanding capital structure in diverse economic contexts.

This study investigated the impact of sustainability reporting on financial performance, with a focus on companies in the Turkish food, beverage and tobacco and textile, wearing apparel and leather sectors. The sustainability reports of 48 companies listed on the Istanbul Stock Exchange for 2022 were studied, and the quality of sustainability practices was determined by using a general index (Sustainability Reporting Disclosure Quality Index (SRDQI)) and three partial indices (Environmental Disclosure Quality Index, Social Disclosure Quality Index, and Corporate Governance Disclosure Quality Index (CGDQI)). To analyze the relationships between financial performance and sustainability practices two types of regression models were developed, based on which eight models were directly examined. The results indicate the complete absence of a statistically significant impact of SRDQI on all financial performance measures used. Among the partial indices, only CGDQI has a significant positive effect on the Assets Turnover Ratio. An analysis of the influence of control variables shows a multidirectional dependence of individual financial performance measures on the size of companies, their age, industry affiliation, as well as on the structure of capital used. Finally, this study provides directions for improving the institutional environment of sustainability reporting for Turkish companies.

The COVID-19 pandemic had a wide-ranging impact, resulting in a global recession due to weakened purchasing power. This circumstance necessitates business organizations adapting to developments and being more conscious of the risk of financial statement fraud. The intention of this research is to investigate the way corporate governance affected financial statement fraud during the COVID-19 pandemic. To acquire empirical data for examining corporate governance variables on financial statement fraud, the research was examined using quantitative methods. The study takes advantage of secondary data acquired from annual reports of companies under special monitoring listed on the Indonesia Stock Exchange of 2020-2021. The logistic regression method was used to evaluate 134 data sets, and financial statement fraud was measured using the Z-Score and F-Score models. The results indicate that using the Z-score, only the board size has a negative effect on financial statement fraud during the COVID- 19 pandemic. Meanwhile, using the F-Score, the corporate governance variables studied are not proven to have an influence on financial statement fraud during the COVID 19 pandemic.

Indonesian crypto asset owners are expanding despite the government's ban. Crypto assets are too risky for Indonesian investors. This study uses the Theory of Planned Behavior and exogenous variables like financial literacy, trust, and government regulation to determine the causes of the intention to invest in crypto assets. Exogenous variables and behavioral intentions were moderated by gender. The study employs a quantitative approach, collecting data through a questionnaire survey of 149 adults over the age of 17 who have invested in non-crypto assets. SmartPLS was used to analyze research data. Financial literacy and trust, according to the study's findings, have an impact on the intention to invest in crypto assets. Gender can moderate the relationship between belief and behavioral intention. Women are more likely than men to invest in crypto assets due to the block chain system's security, transparency, and ease of use. This research is expected to help the government address the risks associated with investing in crypto assets by increasing transaction security with futures clearing and monitoring by using third parties as depositors. It also governs the laws governing crypto exchanges' liability to their investors.

This article mainly proposes the point of view that financial literacy curriculum aims to make kinds of people, to make people with financial creativity of resource integration thinking and continuous ‘to conscience’ of morality, which is cultivate a way of thinking that can maximize benefits through the use of resource integration and constantly ‘to conscience’ to achieve goals for participants in financial structures with balanced interests. In this sense, this article argues that financial literacy is to make kinds of people with a financial mindset and constantly strengthen ‘to conscience’ through uniting of knowledge and action to achieve human well-being and benign operation of society. In this sense, this article attempts to determine what is really taught in financial literacy education in terms of curriculum theory. That is to improve creativity by cultivating financial thinking with constant ‘to conscience’. The views of this paper provide a new way of thinking about financial literacy education assessment. This changes the evaluation criteria of financial literacy education from the result-oriented of wealth growth to the process-oriented of financial creativity growth, trying to move the criticism of financial literacy education curriculum and evaluation from controversy to unity.

The financial sector, too, is developing innovative services and products that have the potential to make a more positive impact on global environmental goals. However, research sheds little light on environmental attitudes and behavioral patterns of employees in this sector. There are multiple factors promoting or inhibiting environmental behavior. Those factors may be rooted in individual or subjective norms, but also social influence and to some extent financial incentives and benefits. A survey concerning the intention to improve and actually show ‘green behavior’ was developed based on widely used acceptance models which differentiate between desirable behavior and the intention to show such behavior. Employees are predominately responsive towards environmental behavior: 20% are convinced of the need to act in a “green” and sustainable manner, only 5% are hard to win over or are not accessible at all. Financial loss or benefits combined with social motives contribute to sustainable living whereas financial benefits alone actually hinder such behavior. The study underlines the existence of a intention-behavior gap: The intention to behave sustainably is built somewhat separately from various influences. There are moderating factors like sex, age and family status that influence the decisions. This then leads to a gap between intention and actual behavior.

The COVID-19 crisis has emphasized the importance of digital transformation of SMEs and has served as an accelerator. Digital transformation empowers SMEs to rethink the way they make decisions and apply technology in meaningful and sustainable ways. The purpose of this study is to explore the role of digital transformation, fostered by COVID-19, and its potential contribution to the sustainability of SMEs. This paper examines a new conceptual framework designed on resource-based theory perspectives by using a survey data of 246 SMEs in Latvia and employing mediation analysis. The main findings of the study are that digital orientation and digital capability have direct positive effects on digital transformation; higher levels of digital orientation and capability, mediated by digital transformation, lead to higher revenue; as well as a more sophisticated business model in the case of digital orientation. Even if we cannot confirm that higher digital capability, mediated by digital transformation, leads to a more sophisticated business model, we found statistically significant direct effects from digital capability to digital transformation and from digital transformation to business model. These findings can be useful for policymakers, managers and practitioners to clarify how digital orientation, digital capability intermediated through digital transformation affect sustainability of SMEs.

There is an increasing pressure by community and customers forcing companies to insert environmental concerns in their practices. To help companies initiatives, the green bonds market was incepted. Our research question is how to select bonds in a growing billion-dollar market. This paper presents a multi-criteria decision analysis (MCDA) model to enable investors identify opportunities based not only in opinions, but grounded on objective facts. Analytic Hierarchy Process (AHP) and Complex Proportional Assessment (COPRAS) are two MCDA methods applied in this paper. Top-fifteen green bonds ranked by specialized media were assessed with the proposed MCDA model. Criteria included the Environmental Performance Index (EPI) proposed by Yale University, and common financial indicators as assets, risks (β), and dividends. The new AHP–COPRAS rank is compared with another published by specialized media.

Pakistan is under developing country and it has an unpredictable market nature of shareholder-investors observe the company’s performance. This research could help to companies in understanding financial behavior, attitude and investors’ satisfaction in stock trade. Financial behavior is comparatively new subject in Pakistan therefore; this study has examined the financial behavior and attitude of investors. The behavioral finance that has been attempted to understand the positive experiences influences investors’ financial behavior. This study has find out that investor satisfaction is strongest in influence of positive financial behavior of investor and trader in stock trading; positive experience and brokers suggestions are strengthens the investment decision of investors and increases behavior loyalty to prefer over competitor. The main purpose of research to determine the effect of financial behavior on investors’ attitude and behavioral loyalty and investors’ satisfaction to preference over competitor. The research framework links with experiences in stock trade for positive (negative) experiences, attitude and financial behavior is developed. The research framework is measured data from sample of Karachi and Karachi Stock Exchange; the data is analyzed in smart PLS based on PLS-SEM. This study focused on trading experience with company’s active investors and traders in banking industry in Pakistan. The future research could be research in other sectors with inter-related issue of investors and traders (brokers) in stock trade. This is the first study in this research area; this study will be determine the experiences with positive (negative) financial behavior, attitude, satisfaction and behavioral loyalty of investors and traders in stock trade. Therefore, adding in this area of study which will help understanding the investors and traders attitude, preference and financial behavior in financial market.

Real estate industry is related to the national economy and people's livelihood，characterized by a high degree of financial intensity. The enterprises in this industry need certain financial ability and large shareholder controlling ability to support their survival. However，due to the multiple adverse impacts of current state policies，banks and private capital，the credit crunch，the sudden decrease in withdrawn funds and the limitation of internal financing，the problem of capital restraint of real estate enterprises has become more and more serious. From the perspective of corporate governance，this paper studies the interaction among financial constraints，ownership concentration and corporate performance under different shareholding states by analyzing the quantitative characteristics of equity structure，and looks for the appropriate range of the largest shareholder holding ratio，which has considered the financial performance and risk. It is found that raising the ownership concentration can effectively ease the financing constraints and improve the performance of enterprises，both of which are significant under the state of high ownership concentration， while the financial constraints play a significant intermediary effect under the State of absolute holding， while in the decentralized state of ownership，there is a significant regulatory effect，and the interaction of the three will be different due to the size of the enterprise.

This research aims to determine the influence of the independent commissioners, audit committee, institutional ownership, firm size and leverage against the integrity of the financial reporting information. This research is quantitative research with the causal approach. This study uses secondary data and panel data regression analysis method. The research results prove that audit committee, institutional ownership and leverage effect on the integrity of the financial reporting information. But it does not prove that the independent commissioner and firm size effect on the integrity of the financial reporting information.

There is an increasing concern on the quality of jobs and productivity witnessed in the flexible employment arrangements. The aim of this study is to examine the relationship between various employment arrangements and the workplace performance. Home-based working-teleworking, flexible timing and compressed hours are the main employment types examined using the Workplace Employee Relations Survey (WERS) in years 2004 and 2011. The workplace performance is measured by two outcomes- the financial performance and labour productivity. First, the determinants of those flexible employment types are explored. Second, the ordinary least squares (OLS) method is followed. Third, an instrumental variable (IV) approach is applied to account for plausible endogeneity and to estimate the causal effects. The findings reveal a significant and positive relationship between these types of flexible employment arrangements and the workplace performance. Education, age, wage, quality of relations between managers-employees, years of experience, the area of the market the workplace is operated and the competition are significant factors and are positively associated with the propensity of the flexible employment arrangements implementation. This can have various profound policy implications for employees, employers and the society overall, including family-work balance, coping with family demands, improving the firm performance, reducing traffic congestion and stress among others. It is the first study that explores the relationship between flexible employment types and workplace performance using an IV approach. This allows us to estimate the causal effects of flexible employment types and the possible associated social implications.

With the continuous advancement of digital transformation, digital payments are playing an increasingly important role in the financial industry. This study aims to utilize machine learning models to predict and analyze digital payment behavior. Initially, the background and significance of digital payments in the financial sector are introduced. Subsequently, the current status and trends of traditional digital payment distribution are reviewed, alongside related work on digital payment behavior prediction. Methodologically, principles and applications of machine learning models such as logistic regression, decision trees, and random forests are elaborated, along with experimental design and data preprocessing methods. The experimental results and discussion section illustrates the performance of each model in digital payment prediction and explores their impact on credit decisions. This exploration equips financial institutions with more effective user behavior analysis and risk management tools, thereby fostering future development and application of digital payment technologies.

This study introduces a novel method that combines Generative Adversarial Networks (GANs) with conformal prediction to revolutionize the domain of stock ticker forecasting. Our approach enhances prediction accuracy and offers dependable prediction intervals to gauge uncertainty, surpassing current GAN-based techniques in unpredictable market scenarios. We made a validation using AAPL stock data, showing the ability of our model to generate accurate forecasts and reliable assessments of prediction uncertainty. The prediction intervals generated provide investors and risk managers with a powerful tool to make informed decisions. Our approach represents a notable advancement in financial prediction as it improves the clarity and reliability of forecasts. By incorporating conformal prediction into the GAN framework, the reliability of forecasts is improved, providing a thorough evaluation of uncertainty that is crucial for successful risk management. This framework has the potential to transform the field of predictive analytics in finance. It shows a solution that balances accuracy and uncertainty quantification. The results clearly show the effectiveness of this method, paving the way for its potential application in a wide range of financial prediction scenarios.

The use of e-scooters and e-bicycles has been on the rise with an increased medical and financial burden. Our purpose was to identify risk factors for increased medical charges and recommend appropriate steps. We studied a retrospective cohort presenting to a level 1 urban trauma center from January 2018 through July 2019 due to micro-mobility platforms. The primary outcome for comparison was total billing cost and a regression analysis was performed to identify variables associated with higher cost. A total of 4073 patients were identified. The majority of which were males (67%), aged 20-30 years (41%). Helmet use reported in only 39.8%. Radiologic studies were performed more often in the e-bicycle group. Total billing charges amounted to 28.3 million New Israeli Shekels ($7.9 million). Average total cost was higher for e-bicycle injuries and in non-helmet users. Other factors associated with higher cost were age, and time of day 12:00-18:00. We recommend that urban cities invest in infrastructure in advance to micro-mobility introduction, regulate the use of e-platforms, designate resources for education on personal protective equipment and prepare medical centers in advance.

Financial fraud poses a severe threat to the integrity of corporate financial statements and market efficiency. While auditors play a crucial role in detecting and preventing such fraud, the unique characteristics of this domain, including class imbalance, high misclassification costs, and am-biguous attributes, pose significant challenges. Traditional classification algorithms may not be optimally suited for this task. This paper proposes a novel stacking ensemble learning approach to enhanced detecting of Financial Statement Scam. By combining the strengths of multiple base learners, including Random Forest, XGBoost, and Gradient Boosting Decision Trees, our model leverages their diverse predictions to improve overall performance. A Logistic Regression me-ta-learner is employed to integrate the outputs of the base learners, capturing their collective wisdom while mitigating individual weaknesses. Extensive experimentation using a real-world dataset shown the superiority of our approach, achieving remarkable recall, precision, accuracy, and area under the curve metrics. The proposed model outperforms individual base learners, under-scoring the efficacy of ensemble learning in tackling the intricate problem of financial fraud detection. This research contributes to the creation of substantial and robust fraud detection systems, fostering trust and transparency in financial markets.

External audit reliance issues on the internal audit function (IAF) are increasingly important in financial auditing, yet its application in audit engagements lags behind other applications. Despite the belief that audit reliance will shape auditing in the future, limited and intervalley publications explore this transformative potential. This paper investigates the increasing importance of external audit reliance issues in financial auditing. It investigates the use of the IAF in external audit reliance decisions and its potential to enhance audit quality, process transparency, and stakeholders' credibility. Through a systematic literature review of 68 scientific articles from 1984 to 2022, factors influencing external auditors' dependence on the IAF are analyzed, including IAF work quality, assistance type, organizational factors, customer pressure, and business risk. The review highlights the IAF's crucial role in improving financial reporting integrity and external audit effectiveness. However, the challenges that allowed external auditors to decide whether to rely on the works of IAF like limited disclosures and accessible data hinder assessing IAF reliance effects, leading to information asymmetry that may impact stakeholder confidence. The paper discusses implications, limitations, and future research directions to explore technology adoption and optimize audit practices, promoting transparency in the audit process.

The purpose of the article is to measure, using the VAIC and MVAIC models, the impact of intellectual capital and its elements on the financial performance of Omani industrial companies listed on the Muscat Stock Exchange (MSE) from 2017 to 2021. Regression analysis using the Gretl software was applied to the study of panel data on the activities of 34 industrial companies in Oman, obtained from the official MSE website and from published financial statements. The analysis of literature sources was carried out using bibliometric analysis, the results of which were visualized using the VOSviewer software. To analyze the relationships between financial performance and its determinants (intellectual capital variables and control variables), four types of PERF models were developed, based on which sixteen models were directly examined. Four dependent variables (Earnings before interest, Taxes, Depreciation and Amortization, Return on Assets, Return on Equity, Assets Turnover Ratio) and eight independent variables (Value Added Intellectual Coefficient, Modified Value Added Intellectual Coefficient, Capital Employed Efficiency, Human Capital Efficiency, Structural Capital Efficiency, Relational Capital Efficiency, Size, and Leverage) were used to form these models. The Empirical Results section has discussed descriptive statistics and correlations, selection of estimate panel data parameter based on the F-statistics, Breusch-Pagan test, and Hausman test, assumption test results (Normality, Autocorrelation, Heteroscedasticity), and panel regression models. Analysis of the impact of VAIC, MVAIC and its elements on the financial performance of Omani industrial companies has yielded mixed results. VAIC and MVAIC in general have a significant positive effect only on ATO. For individual elements of VAIC and MVAIC, the following most significant associations with financial performance measures were found: CEE negatively affects ROE; SCE has a positive effect on l_EBITDA and ATO; RCE negatively affects ATO; l_SIZE has a positive effect on l_EBITDA and ROA; and LEV has a positive effect on ROA.

Weighted Student Funding (WSF) systems have been implemented in various countries to give schools more autonomy over how to allocate their funding. School principals use funding to maintain school operations and foster innovation for achieving educational goals. However, despite the importance of this process, scholarly research has largely overlooked how principals make decisions about their financial resources. Accordingly, this study seeks to provide practical insights into the strategies used by one school by highlighting their staff’s perceptions about using their WSF to maintain school operations and spur innovation. Using a case study approach, we investigated a principal who effectively used a school’s WSF to transform a failing school into an innovative one. The findings revealed that the principal strategically implemented financial management mechanisms in a way that inspired teachers to deeply consider how a school's WSF can help achieve educational goals. The principal fostered consensus on the school's direction, encouraged innovation through hands-on experiential learning and strategic planning, and facilitated funding for innovative teachers by guiding proposal development. Insights into the shifting cultural and practical landscape of financial resource utilization within schools are discussed.

Recent years have seen dramatic growth in the number of scholarly scientific works dedicated to the topic of Artificial Intelligence (AI), banking, and finance. With the development of scientometric tools, it is now possible to map, visualize, analyze, and assess scientific activities in many fields of engineering and social sciences including Islamic banking and finance. Based on data retrieved from the Scopus database and using a qualitative method, this study investigates, evaluates, and identifies significant development, trends, and players in the application of AI in Islamic banking and finance using the Visualization Of Similarities Method (VOS) between objects in VOSviewer. From 2006 to 2022, 387 documents were retrieved from the Scopus database; Results revealed that the top five most active countries in terms of publications are Malaysia (117 documents), Indonesia (89 documents), the United Kingdom (36 documents), the USA (24 documents), and Saudi Arabia and Bahrain (24 documents each). The International Islamic University Malaysia and Universitas Indonesia came out on top of active institutions while the top funding source came from the Ministry of Higher Education, Malaysia. The comprehensive findings and analysis reported in this study serve as a roadmap for future academics to create theory and practice for applying AI in Islamic banking and finance.

Advanced Hepatocellular carcinoma (HCC) is no longer a terminal illness. This change was mainly attributed to the development of new treatments including tyrosine-kinase inhibitors (TKIs), vascular endothelial growth factor (VEGF) inhibitors and immune checkpoint inhibitors (ICPIs) but the financial toxicity of treating advanced HCC is of a major concern specially in low middle-income countries (LMICs) where the patients are still battling for their most basic rights. Most of advanced HCC patients in LMICs have very limited accessibility to the new treatments including ICPIs. Searching for out of the box solutions to improve access to treatments -mainly ICPIs- is an utmost necessity for LMICs advanced HCC patients.

This research article provides criticism and arguments why the canonical framework for derivatives pricing is incomplete and why the delta-hedging approach is not appropriate. An argument is put forward, based on the efficient market hypothesis, why a proper risk-adjusted discount rate should enter into the Black-Scholes model instead of the risk-free rate. The resulting pricing equation for derivatives and in particular the formula for European call options is then shown to depend explicitly on the drift of the underlying asset, which is following a geometric Brownian motion. It is conjectured that with the generalized model, the predicted results by the model could be closer to real data. The adjusted pricing model could partly also explain the mystery of volatility smile. The present model also provides answers to many finance professionals and academics who have been intrigued by the risk-neutral features of the original Black-Scholes pricing framework. The model provides generally different fair values for financial derivatives compared to the Black-Scholes model. In particular, the present model predicts that the original Black-Scholes model tends to undervalue for example European call options.

Financial statement analysis is an analysis that uses analytical procedures to evaluate a company's financial health, risks, performance, and future growth potential. This article aims to find out the application of analysis of financial statements of PT. Astra Internasional, Tbk towards the decision-making of novice investors in the Indonesian capital market. This article is qualitative descriptive with literature studies. The results of this article can be concluded that the analysis of the financial statements of PT. Astra Internasional, Tbk can help novice investors in the Indonesian capital market in making investment decisions.

The main purpose of study is to identify the impact of COVID-19 pandemic on the green financing of banks and non-bank financial institutions (NBFIs) in an emerging economy such as Bangladesh. Also, this study shows the green banking activities of the banks and NBFIs during the pandemic. To analyze the impact of the pandemic on green financing, secondary data were obtained from the quarterly and annual reports of Bangladesh Bank (BB) on green financing as well as the annual reports and websites of 61 banks and 34 NBFIs in Bangladesh for the period 2021–2019. Subsequently, the study deployed dependent t-test statistics, growth rate (year-on-year), descriptive statistics, relative percentage changes, and varying tables and graphs to analyze the obtained secondary data. The empirical findings revealed that during the COVID-19 pandemic, there was an increase in green finance for all banks and NBFIs compared to before the epidemic, indicating that the pandemic had no negative impact on the total green finance growth of all banks and NBFIs. On the other hand, compared to the pre-pandemic period, bank-wise growth in green financing was higher for state-owned commercial banks (SOCBs), specialized banks (SDBs), and private commercial banks (PCBs) but lower for foreign-owned commercial banks (FCBs) during the COVID-19 epidemic. This suggests that the pandemic does not affect the expansion of green finance by SOCBs, SDBs and PCBs but significantly impacted the growth of green financing by FCBs. Furthermore, the research findings showed that the total outstanding and classified loans within the green finance investment decrease for both banks and NBFIs during the COVID-19 pandemic. The results indicated that the Bangladeshi banks’ level of automation towards green banking were satisfactory during the pandemic. Therefore, major policy implications for the green economic recovery by the government, BB, and managers of the banks and financial institutions in emerging economies like Bangladesh were discussed.