1 June 2025
The rising complexity of financial fraud in highly digitalized regions such as the Gulf Cooperation Council (GCC) poses challenging issues owing to class imbalance, adversarial attacks, concept drift, and explainability requirements. This paper sugge...
Green technology innovation (GTI) is crucial for sustainable economic development and achieving “peak carbon” and “carbon neutrality” goals. While fiscal vertical imbalance (FVI) may exert an inhibiting effect on regional GTI,...
Based on the perspective of financial geography, this study analyzed the convergent mechanism of urban–rural financial imbalances under the influence of spatial spillover through the theoretical framework of spatial process, spatial action, and...
This paper examines the role of the quality of institutions, financial development and FDI on current account imbalances, which narrowed during the Global Financial Crisis. In doing so, we utilize (i) a sample of 49 advanced and emerging economies du...
The class imbalance problem in finance fraud datasets often leads to biased prediction towards the nonfraud class, resulting in poor performance in the fraud class. This study explores the effects of utilizing the Synthetic Minority Oversampling TEch...
One of the key challenges in financial distress data is class imbalance, where the data are characterized by a highly imbalanced ratio between the number of distressed and non-distressed samples. This study examines eight resampling techniques for im...
Bank telemarketing campaigns often experience low subscription rates due to customer heterogeneity and severe class imbalance, which pose challenges for reliable predictive modeling. This study investigates a data-driven approach that integrates synt...
Corporate transparency is vital for sustainable governance. However, detecting financial misstatements remains challenging due to their rarity and resulting class imbalance. Using financial statement data from Korean firms, this study develops an int...
With the widespread use of credit cards in online and offline transactions, credit card fraud has become a significant challenge in the financial sector. The rapid advancement of payment technologies has led to increasingly sophisticated fraud techni...
In Poland, responsibility for educational tasks has mainly been delegated to local governments, although the state still plays a decisive role. Municipalities finance these tasks using educational subsidies and targeted grants from the central budget...
Financial fraud has become a critical challenge for modern financial systems due to the rapid growth of digital transactions, online banking services, and electronic payment platforms. Traditional rule-based fraud detection systems are increasingly i...
The growth of state transfers to offset disparities in regional development affects the stability of the country’s financial system. This article delves into this outcome, empirically analyzing whether the transfer system for horizontal fiscal...
Credit risk assessment under severe class imbalance requires both structured imbalance correction and principled decision rules, yet most studies treat these as independent steps. This study develops a general integrated three-layer framework for cre...
Detecting fraudulent and anomalous transactions in large-scale digital payment systems is significantly challenging due to severe class imbalance and the fact that transactional risk is tightly coupled to the historical interactions and behaviors of...
Imbalanced datasets are one of the main issues encountered by artificial intelligence researchers, as machine learning (ML) algorithms can become biased toward the majority class and perform insufficiently on the minority classes. Financial distress...
Evaluations of financial early-warning models can appear stronger when temporal separation is incomplete or when the event definition uses information unavailable at the forecast origin. This study examines one-day-ahead risk ranking of large absolut...
A new econometric methodology based on deep learning is proposed for determining the causality of the financial time series. This method is applied to the imbalances in daily transactions in individual stocks and also in exchange-traded funds (ETFs)...
Recently, several studies have argued about the interactions of the real economy and financial system, as well as the importance of financial cycles in business cycle fluctuations. To date, there exists near consensus among central bankers, economist...
Wind energy forecasting is a critical aspect for wind energy producers, given that the chaotic nature and the intermittence of meteorological wind cause difficulties for both the integration and the commercialization of wind-produced electricity. For...
This paper aims to tackle the problem of low accuracy in predicting financial distress in Chinese industrial enterprises, attributable to data imbalance and insufficient information. It utilizes annual data on systemic risk indicators and financial m...
In this paper, to provide references for coordinating the development of digital inclusive finance between provinces and regions in China, we measure the digital financial inclusion index of 31 provinces in China from 2011 to 2020 based on three dime...
Two key challenges in financial distress prediction are pronounced class imbalance between majority and minority classes and the persistent misclassification of hard-to-learn samples. To tackle these issues, this study proposes an ensemble framework...
Accurate early-warning forecasting of corporate financial distress remains a critical challenge due to nonlinear financial relationships, severe data imbalance, and the high operational costs of false alarms in risk-monitoring systems. This study pro...
Timely identification of company financial risks is crucial for investors and regulators. However, existing studies overlook the class imbalance caused by the scarcity of high-risk samples, and the interpretability of deep models is insufficient, mak...
Raw sentiment extracted from Chinese financial news is noisy and difficult to use directly for market prediction. This study proposes a mathematical filtering framework that converts noisy Chinese financial news sentiment into reliable quantitative s...
In this paper, based on Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, five financial serials are dynamically weighted, and then China’s Financial Conditions Index is synthesized to measure China’s financial cycl...
Balance plays an important role in the sustainable development of China’s financial inclusion. First, this paper reports the entropy weight method used to construct a financial inclusion index (FII) and measure the level of development of finan...
The literature dedicated to the problems of transboundary pollution often aims to verify what the environmental and energy interactions between countries are. Little attention is paid to the financial relations of the phenomenon. We analyze how finan...
Predicting company bankruptcy is a critical task in financial risk assessment. This study introduces a novel approach using Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) to enhance bankruptcy prediction accuracy. By...
The paper focuses on the stochastic forecast of the financial sustainability ofbasic pension, based on predictions for the population of China. The population was calculated iteratively by using Leslie matrix. An auto-regressive moving average model...
With the rapid development of information technology and the deep integration of the Internet platform, the scale and form of financial transactions continue to grow and expand, significantly improving users’ payment experience and life efficie...
The United Nations’ 2030 Agenda for Sustainable Development aims to promote inclusive and sustainable economic growth and encourage the formalization and growth of micro, small, and medium enterprises through access to financial services. This...
Sustainable financial inclusion is an essential factor for economic development, social justice, and environmental sustainability. The primary objective of this bibliometric analysis is to investigate trends in sustainable financial inclusion publica...
Predicting credit default risk is important to financial institutions, as accurately predicting the likelihood of a borrower defaulting on their loans will help to reduce financial losses, thereby maintaining profitability and stability. Although mac...
Aggregate financial conditions indices (FCIs) are constructed to fulfil two aims: (i) The FCIs should resemble non-model-based composite indices in that their composition is adequately invariant for concatenation during regular updates; (ii) the conc...
This paper attempts to detect the unavoidable impacts of COVID-19 on geopolitical and financial events related to Islamic banking and the finance sector in Pakistan. It considers only those major events that triggered imbalances in the equity prices...
Effective identification of corporate default risk is crucial for maintaining financial stability and safeguarding investors’ interests. Existing models remain limited in addressing class imbalance and the dynamic evolution of default-related f...
This study proposes the Double-Ensemble Learning Classification with SMOTE (DELC-SMOTE), a novel hierarchical framework designed to address the critical challenge of severe class imbalance in financial bond default prediction. The model integrates th...
21 July 2022
The global digital operation of finance has accelerated, and the transformation and upgrading of the financial industry has been fully empowered by digital technology, which has promoted the development of traditional financial industry toward green...
Graph Neural Networks (GNNs) face fundamental algorithmic challenges in real-world applications due to a combination of data heterogeneity, adversarial heterophily, and severe class imbalance. A critical research gap exists for a unified framework th...
This study tests for racial discrimination against minority managers in Major League Baseball using financial-market imbalances as it relates to the wagering marketplace for the sport. Using detailed betting data on the percentage bet on the favorite...
In the context of new quality productive forces, enterprises must leverage technological innovation and intelligent management to enhance financial risk resilience. This article proposes a financial distress prediction model based on deep learning, c...
Purpose: This study examines the impact of macroeconomic factors on GCC banks’ stability. As GCC countries still rely on oil export revenues to cover government expenses and perform an undiversified economy, hence, increased awareness of the fi...
China’s economy has been growing at a rapid pace in recent years, but the quality of economic development has not been consistent with the quantity, which is not conducive to sustainable economic development. How to improve the quality of econo...
This paper analyses the effectiveness of the financial control system implemented by the Spanish professional football League in 2015 as a tool to improve the governance of clubs in the first and second divisions as well as its probable impact on com...
Bankruptcy prediction has been a popular and challenging research topic in both computer science and economics due to its importance to financial institutions, fund managers, lenders, governments, as well as economic stakeholders in recent years. In...
The proliferation of renewable energy sources has presented challenges for Balancing Responsible Parties (BRPs) in accurately forecasting production and consumption. This issue is being addressed through the emergence of the balancing markets, which...
Financial fraud represents a critical global challenge with substantial economic and social consequences. This comprehensive review synthesizes the current knowledge on machine learning approaches for financial fraud detection, examining their effect...
In many countries, the economic crisis brought high volumes of deficit and debt in public entities, which jeopardized the ability of governments to continue providing public services and caused considerable imbalances of economic growth in different...
In recent years, weakened by the fall of economic growth, many enterprises fell into the crisis caused by financial difficulties. Bankruptcy prediction, a machine learning model, is a great utility for financial institutions, fund managers, lenders,...
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