Risks

15 pages, 525 KiB

Open AccessArticle

Impacts of Financial Inclusion and Life Insurance Products on Poverty in Sub-Saharan African (SSA) Countries

by Oladotun Larry Anifowose and Bibi Zaheenah Chummun

Risks 2025, 13(6), 109; https://doi.org/10.3390/risks13060109 - 4 Jun 2025

In recent years, scholars have been paying more attention to financial inclusion, which has been positioned as a crucial component in accomplishing the majority of the seventeen Sustainable Development Goals set forward by the United Nations. Investigating the effects of life insurance and [...] Read more.

In recent years, scholars have been paying more attention to financial inclusion, which has been positioned as a crucial component in accomplishing the majority of the seventeen Sustainable Development Goals set forward by the United Nations. Investigating the effects of life insurance and financial inclusion on poverty in 45 Sub-Saharan African (SSA) nations between 1999 and 2023 is the goal of this study. Using the Panel Autoregressive Distributed Lag (P-ARDL) method, this study concludes that poverty can be decreased through financial inclusion. Notably, we found that life insurance raises poverty when financial inclusion follows. This might be because there are not many microinsurance options available in SSA nations for those with low incomes. Due to their increased likelihood of being financially illiterate and their inability to purchase the necessary smart devices and internet services, the lower-income segments are unable to enjoy the same advantages as the higher-income segments. According to the findings, financial exclusion problems may be resolved by future life insurance, but this must be done in a sustainable manner. Future life insurance should address the requirements of the underprivileged and lower-income groups, and financial inclusion should be progressively enhanced. Full article

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42 pages, 4414 KiB

Open AccessArticle

Building an InsurTech Ecosystem Within the Insurance Industry

by Iván Sosa and Sergio Sosa

Risks 2025, 13(6), 108; https://doi.org/10.3390/risks13060108 - 3 Jun 2025

Abstract

The emergence of InsurTech has significantly transformed the traditional insurance industry, leading to the development of a new ecosystem characterized by digital intermediation, strategic partnerships, and increasing interdependence among actors. This paper investigates the structural configuration of the InsurTech ecosystem, emphasizing its role [...] Read more.

The emergence of InsurTech has significantly transformed the traditional insurance industry, leading to the development of a new ecosystem characterized by digital intermediation, strategic partnerships, and increasing interdependence among actors. This paper investigates the structural configuration of the InsurTech ecosystem, emphasizing its role in reshaping how value is created, delivered, and captured across the industry. Based on a sample of 364 active InsurTech firms from 2020 to 2023, the research employs network analysis to map the interactions and co-occurrences among seven defined archetypes: Enablers, Innovators, Connectors, Integrators, Protectors, Transformers, and Disruptors. The findings reveal a trend toward higher density and functional complementarity among archetypes by providing a framework for understanding the dynamics of the InsurTech ecosystem and the strategic implications. Building on these findings, this paper introduces a novel five-phase framework for understanding the ecosystem’s evolution: (1) digitalization and technologies, (2) customer-centric approach, (3) data and analytics, (4) platform-based business models, and (5) ecosystem partnerships. This research advances the theoretical understanding of InsurTech as a networked system of role-based interdependencies and provides a methodological approach to analyzing this scenario through network theory. Furthermore, it contributes to academic discourse and industry practice, offering practical guidance for insurers, startups, and policymakers by enabling actionable insights into the strategic positioning of InsurTech archetypes within the evolving insurance industry landscape. Full article

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28 pages, 4030 KiB

Open AccessFeature PaperArticle

Linking Futures and Options Pricing in the Natural Gas Market

by Francesco Rotondi

Risks 2025, 13(6), 107; https://doi.org/10.3390/risks13060107 - 3 Jun 2025

Abstract

A robust model for natural gas prices should simultaneously capture the observed prices of both futures and options. While incorporating a seasonal factor in the convenience yield of the spot price effectively replicates forward curves, it proves insufficient for accurately modelling the options [...] Read more.

A robust model for natural gas prices should simultaneously capture the observed prices of both futures and options. While incorporating a seasonal factor in the convenience yield of the spot price effectively replicates forward curves, it proves insufficient for accurately modelling the options price surface. The latter is more sensitive to the volatility structure of the spot price process, which has a limited impact on futures pricing. In this paper, we analyse European natural gas spot, futures, and options prices throughout 2024 and propose a no-arbitrage model that integrates both a seasonal stochastic convenience yield and a local volatility factor. This framework enables a simultaneous and accurate fit of both forward curves and options prices. Full article

(This article belongs to the Special Issue Financial Derivatives and Hedging in Energy Markets)

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22 pages, 609 KiB

Open AccessArticle

The Impact of Fintech on the Stability of Middle Eastern and North African (MENA) Banks

by Aisha Mohammad Afzal, Bashar Abu Khalaf, Maryam Saad Al-Naimi and Enas Samara

Risks 2025, 13(6), 106; https://doi.org/10.3390/risks13060106 - 29 May 2025

Abstract

This study investigates the impact of financial technology (Fintech) on bank stability in the Middle East and North Africa (MENA). Utilizing panel data from 94 banks in 10 countries over a 13-year period from 2011 to 2023, this research employs panel GMM regression [...] Read more.

This study investigates the impact of financial technology (Fintech) on bank stability in the Middle East and North Africa (MENA). Utilizing panel data from 94 banks in 10 countries over a 13-year period from 2011 to 2023, this research employs panel GMM regression to examine the relationship between the level of Fintech adoption, as measured by the Fintech index, and a bank’s stability. This paper controls for bank characteristics (efficiency, profitability, size, liquidity risk, and dividend payout ratio) and macroeconomic variables (GDP growth and inflation). The Fintech index is calculated using data text mining from the banks’ annual reports. This research contributes to the existing literature by providing empirical evidence of the positive effects of Fintech adoption in the MENA banking sector. The positive findings underscore the transformative impact of Fintech on banking stability, highlighting the importance of technological integration in MENA’s financial institutions for growth, stability, and effective strategies. The robustness of the results regression confirmed that our findings hold. Full article

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27 pages, 1061 KiB

Open AccessArticle

Assessing the Integrated Role of IT Governance, Fintech, and Blockchain in Enhancing Sustainability Performance and Mitigating Organizational Risk

by Faozi A. Almaqtari, Ali Thabit Yahya, Nahad Al-Maskari, Najib H. S. Farhan and Al-Muaayad Yaqoob Yahya Al-Aamri

Risks 2025, 13(6), 105; https://doi.org/10.3390/risks13060105 - 29 May 2025

Abstract

In a digitalized business, blockchain technology, fintech, AI, and IT governance are crucial for reducing risks and aligning with organizational goals. IT governance ensures smooth and efficient adoption of fintech solutions and AI. Blockchain introduces trust and security through smart contracts, enhancing sustainability [...] Read more.

In a digitalized business, blockchain technology, fintech, AI, and IT governance are crucial for reducing risks and aligning with organizational goals. IT governance ensures smooth and efficient adoption of fintech solutions and AI. Blockchain introduces trust and security through smart contracts, enhancing sustainability performance. Thus, in today’s rapidly evolving digital environment, the integration of these technologies has become critical to organizational resilience in the long-term. The present study aims to explore how the integrated role of IT governance, fintech, and blockchain technologies can enhance sustainability practices to mitigate organizational risks. The study utilized a questionnaire survey to assess the impact of IT governance, fintech, and blockchain technologies on sustainability performance in Oman. The sample included commercial, industrial, and service companies, including banks. A non-probability sampling approach, including convenience and snowball sampling, was used. Software tools such as SPSS and Smart PLS were used to estimate quantitative data analysis and structural modeling results. The study concludes that IT governance dimensions alone have an insignificant impact on sustainability. Importantly, the integrated effect of IT governance (alignment, policies, and committees) improves sustainability. The results also report that IT governance significantly enhances fintech adoption, but it has an insignificant influence on blockchain adoption in organizations. The results reveal that the respondents perceive that sustainability is positively and significantly improved by IT governance strategic alignment and the steering committee. The study offers a unique perspective on the impact of blockchain, IT governance, and fintech technologies on sustainability, filling existing literature gaps and urging policymakers to achieve the Omani Vision 2040. Full article

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23 pages, 434 KiB

Open AccessArticle

A Deep Dive into Institutional and Economic Influences on Poverty in Europe

by Dorin Jula, Lavinia Mastac, Diane Paula Corina Vancea and Kamer-Ainur Aivaz

Risks 2025, 13(6), 104; https://doi.org/10.3390/risks13060104 - 28 May 2025

Abstract

This study analyzed the evolution of the poverty rate between 2004 and 2023 in 29 European countries, using two categories of variables: institutional variables (Corruption Control Index and Rule of Law Index) and economic variables (unemployment rate, shadow economy, government expenditures on social [...] Read more.

This study analyzed the evolution of the poverty rate between 2004 and 2023 in 29 European countries, using two categories of variables: institutional variables (Corruption Control Index and Rule of Law Index) and economic variables (unemployment rate, shadow economy, government expenditures on social protection and the Gini index). The methodology adopted included dynamic panel econometric models, applying a technique which involves the elimination of individual effects by a primary differencing of the variables and the use of the generalized method of moments (GMM) to evaluate the estimators. This methodology eliminates endogeneity caused by including the dependent variable with lag among the explanatory variables in the model. The results showed a strong negative correlation between the poverty rate and institutional variables, suggesting that improvements in governance and access to education and health resources are essential for poverty reduction. The shadow economy has also been identified as a poverty buffer, providing support in the absence of formal employment opportunities. The short-term impact of government expenditures on social protection was not significant, indicating the need for further analysis to better understand these dynamics. This research can make a significant contribution to the design of more effective public policies aimed at reducing shocks, reducing inequality and promoting sustainable economic growth. Full article

(This article belongs to the Special Issue Risk Analysis in Financial Crisis and Stock Market)

17 pages, 18004 KiB

Open AccessArticle

Implicit Prioritization of Life Insurance Coverage: A Study of Policyholder Preferences in a Danish Pension Company

by Julie Bjørner Søe

Risks 2025, 13(6), 103; https://doi.org/10.3390/risks13060103 - 26 May 2025

Abstract

This study evaluates the utility derived by policyholders in a Danish pension company, from their life insurance coverages. We quantify the relative importance policyholders assign to their existing coverages versus a hypothetical complete coverage scenario, thereby measuring the implicit priority of their current [...] Read more.

This study evaluates the utility derived by policyholders in a Danish pension company, from their life insurance coverages. We quantify the relative importance policyholders assign to their existing coverages versus a hypothetical complete coverage scenario, thereby measuring the implicit priority of their current coverage. By analyzing these implicit priorities based on individual attributes such as age, financial situation, and company agreement limitations, we gain a comprehensive understanding of policyholders’ evaluations of their current life insurance coverage. Utilizing a continuous-time life cycle model, we optimize consumption and life insurance decisions during the accumulation phase, applying well-established theoretical findings to actual data. Our analysis identifies trends, outliers, and insights that can inform potential improvements in life insurance coverage. This tool aims to assist policyholders in prioritizing their coverage according to their life situations and provides a foundation for advisory dialogues and product development. Full article

(This article belongs to the Special Issue Market-Consistent Actuarial Valuation and Risk-Based Capital Assessment)

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20 pages, 495 KiB

Open AccessArticle

The Use of the Fraud Pentagon Model in Assessing the Risk of Fraudulent Financial Reporting

by Georgiana Burlacu, Ioan-Bogdan Robu, Ion Anghel, Marius Eugen Rogoz and Ionela Munteanu

Risks 2025, 13(6), 102; https://doi.org/10.3390/risks13060102 - 22 May 2025

Abstract

This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring information to be accurate, reliable, and fairly presented and pressure [...] Read more.

This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring information to be accurate, reliable, and fairly presented and pressure to meet expectations can lead to manipulation. The Fraud Pentagon Theory identifies five potential drivers of such behavior: pressure, opportunity, rationalization, capability, and arrogance. This research contributes to the literature by empirically testing the theory in the Romanian context, an emerging market with limited prior analysis, using a sample of 62 listed companies over the 2017–2021 period. Regression analysis was applied, using the Dechow F-score, which combines accrual quality and financial performance to assess the likelihood of fraudulent financial reporting. The findings reveal that not all dimensions of the theory significantly affect the likelihood of fraudulent reporting. Specifically, pressure-related factors (financial performance and financial stability) were found to be statistically significant, while external pressure, opportunity (external auditor quality and nature of industry), rationalization (change of auditor), capability (change of director), and arrogance (number of CEO’s pictures) did not show significant influence in the Romanian framework. These results highlight the importance of contextual factors such as market structure, governance practices, and stakeholder expectations, suggesting that fraudulent reporting risk indicators may vary across different economic environments. Full article

(This article belongs to the Special Issue Risk Analysis in Financial Crisis and Stock Market)

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21 pages, 502 KiB

Open AccessArticle

Natural Resource Rent and Bank Stability in the MENA Region: Does Institutional Quality Matter?

by Abdelaziz Hakimi, Hichem Saidi and Mohamed Ali Khemiri

Risks 2025, 13(6), 101; https://doi.org/10.3390/risks13060101 - 22 May 2025

Abstract

In natural resource-dependent economies, global resource price volatility makes financial systems more vulnerable to economic shocks. The relationship between natural resource rent and bank stability lies in how fluctuations in resource revenues can affect financial institutions’ stability. The purpose of this paper is [...] Read more.

In natural resource-dependent economies, global resource price volatility makes financial systems more vulnerable to economic shocks. The relationship between natural resource rent and bank stability lies in how fluctuations in resource revenues can affect financial institutions’ stability. The purpose of this paper is twofold. First, it explores the effect of natural resource rent (NRR) on bank stability (BS) in the Middle East and North Africa (MENA) region. Second, it examines whether institutional quality (IQ) moderates the association between BS and NRR. To achieve these goals, we used a sample of 68 conventional banks located in the MENA region between 2005 and 2020 and performed the System Generalized Method of Moments (SGMM) as an econometric approach. The empirical findings show that NRR is negatively and significantly associated with BS, while IQ significantly enhances BS in the MENA region. Additionally, the outcomes support evidence that the MENA banks benefit from an interaction between IQ and NRR. This result was confirmed for both the Z-ROA and Z-ROE as measures of BS. The results of this paper could have several useful applications for policymakers and bankers. Policymakers should prioritize strengthening institutional frameworks to mitigate the adverse effects of resource dependence on financial stability. In addition, bankers are invited to focus on improving institutional quality by fostering an institutional environment, including compliance with anti-corruption standards and coordination with regulatory bodies to boost financial resilience. Full article

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19 pages, 1734 KiB

Open AccessArticle

Modeling Age-to-Age Development Factors in Auto Insurance Through Principal Component Analysis and Temporal Clustering

by Shengkun Xie and Chong Gan

Risks 2025, 13(6), 100; https://doi.org/10.3390/risks13060100 - 22 May 2025

Abstract

The estimation of age-to-age development factors is fundamental to loss reserving, with direct implications for risk management and regulatory compliance in the auto insurance sector. The precise and robust estimation of these factors underpins the credibility of case reserves and the effective management [...] Read more.

The estimation of age-to-age development factors is fundamental to loss reserving, with direct implications for risk management and regulatory compliance in the auto insurance sector. The precise and robust estimation of these factors underpins the credibility of case reserves and the effective management of future claim liabilities. This study investigates the underlying structure and sources of variability in development factor estimates by applying multivariate statistical techniques to the analysis of development triangles. Departing from conventional univariate summaries (e.g., mean or median), we introduce a comprehensive framework that incorporates temporal clustering of development factors and addresses associated modeling complexities, including high dimensionality and temporal dependency. The proposed methodology enhances interpretability and captures latent structures in the data, thereby improving the reliability of reserve estimates. Our findings contribute to the advancement of reserving practices by offering a more nuanced understanding of development factor behavior under uncertainty. Full article

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26 pages, 2575 KiB

Open AccessArticle

Comparing the Effectiveness of Machine Learning and Deep Learning Models in Student Credit Scoring: A Case Study in Vietnam

by Nguyen Thi Hong Thuy, Nguyen Thi Vinh Ha, Nguyen Nam Trung, Vu Thi Thanh Binh, Nguyen Thu Hang and Vu The Binh

Risks 2025, 13(5), 99; https://doi.org/10.3390/risks13050099 - 20 May 2025

Abstract

In emerging markets like Vietnam, where student borrowers often lack traditional credit histories, accurately predicting loan eligibility remains a critical yet underexplored challenge. While machine learning and deep learning techniques have shown promise in credit scoring, their comparative performance in the context of [...] Read more.

In emerging markets like Vietnam, where student borrowers often lack traditional credit histories, accurately predicting loan eligibility remains a critical yet underexplored challenge. While machine learning and deep learning techniques have shown promise in credit scoring, their comparative performance in the context of student loans has not been thoroughly investigated. This study aims to evaluate and compare the predictive effectiveness of four supervised learning models—such as Random Forest, Gradient Boosting, Support Vector Machine, and Deep Neural Network (implemented with PyTorch version 2.6.0)—in forecasting student credit eligibility. Primary data were collected from 1024 university students through structured surveys covering academic, financial, and personal variables. The models were trained and tested on the same dataset and evaluated using a comprehensive set of classification and regression metrics. The findings reveal that each model exhibits distinct strengths. Deep Learning achieved the highest classification accuracy (85.55%), while random forest demonstrated robust performance, particularly in providing balanced results across classification metrics. Gradient Boosting was effective in recall-oriented tasks, and support vector machine demonstrated strong precision for the positive class, although its recall was lower compared to other models. The study highlights the importance of aligning model selection with specific application goals, such as prioritizing accuracy, recall, or interpretability. It offers practical implications for financial institutions and universities in developing machine learning and deep learning tools for student loan eligibility prediction. Future research should consider longitudinal data, behavioral factors, and hybrid modeling approaches to further optimize predictive performance in educational finance. Full article

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24 pages, 2318 KiB

Open AccessFeature PaperArticle

Historical Perspectives in Volatility Forecasting Methods with Machine Learning

by Zhiang Qiu, Clemens Kownatzki, Fabien Scalzo and Eun Sang Cha

Risks 2025, 13(5), 98; https://doi.org/10.3390/risks13050098 - 20 May 2025

Abstract

Volatility forecasting for financial institutions plays a pivotal role across a wide range of domains, such as risk management, option pricing, and market making. For instance, banks can incorporate volatility forecasts into stress testing frameworks to ensure they are holding sufficient capital during [...] Read more.

Volatility forecasting for financial institutions plays a pivotal role across a wide range of domains, such as risk management, option pricing, and market making. For instance, banks can incorporate volatility forecasts into stress testing frameworks to ensure they are holding sufficient capital during extreme market conditions. However, volatility forecasting is challenging because volatility can only be estimated, and different factors influence volatility, ranging from macroeconomic indicators to investor sentiments. While recent works show promising advances in machine learning and artificial intelligence for volatility forecasting, a comprehensive assessment of current statistical and learning-based methods is lacking. Thus, this paper aims to provide a comprehensive survey of the historical evolution of volatility forecasting with a comparative benchmark of key landmark models, such as implied volatility, GARCH, LSTM, and Transformer. We open-source our benchmark code to further research in learning-based methods for volatility forecasting. Full article

(This article belongs to the Special Issue Volatility Modeling in Financial Market)

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22 pages, 503 KiB

Open AccessArticle

Breaking Barriers: Gender Diversity, ESG, and Corporate Misconduct in the GCC Region

by Laila Aladwey, Mohamed Fawzy Mohamed Elsayed and Ahmed Diab

Risks 2025, 13(5), 97; https://doi.org/10.3390/risks13050097 - 15 May 2025

Abstract

Our study explores how ESG performance affects corporate misconduct (CM) in Gulf Cooperation Council (GCC) firms and whether having more women on corporate boards influences this relationship. Using logistic regression and using data collected from GCC firms, we analyse the moderating effect of [...] Read more.

Our study explores how ESG performance affects corporate misconduct (CM) in Gulf Cooperation Council (GCC) firms and whether having more women on corporate boards influences this relationship. Using logistic regression and using data collected from GCC firms, we analyse the moderating effect of board gender diversity (BGD) on the relationship between ESG and CM. Our findings show that strong ESG performance reduces CM, and greater BGD further decreases misconduct. Moreover, gender-diverse boards strengthen the link between ESG and lower CM rates. This study contributes to the literature by examining how BGD influences the ESG-CM relationship in the GCC region. The current findings are valuable for investors, businesses, and policymakers. Investors should prioritize companies with strong ESG practices and diverse boards to minimize the risks they might face. Businesses should integrate female directors on boards to enhance ethical practices. Policymakers can promote corporate responsibility by incentivizing gender diversity and ESG adoption, which is crucial for a more transparent and accountable business environment. Full article

(This article belongs to the Special Issue ESG and Greenwashing in Financial Institutions: Meet Risk with Action)

25 pages, 3880 KiB

Open AccessArticle

The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach

by Alicia Fernanda Galindo-Manrique and Nuria Patricia Rojas-Vargas

Risks 2025, 13(5), 96; https://doi.org/10.3390/risks13050096 - 14 May 2025

Abstract

Women in emerging economies face unique constraints rooted in cultural norms, socio-economic disparities, and limited access to education and technology. Narrowing the digital gender gap by ensuring access to financial services may reduce the economic inequalities for women in these countries. This study [...] Read more.

Women in emerging economies face unique constraints rooted in cultural norms, socio-economic disparities, and limited access to education and technology. Narrowing the digital gender gap by ensuring access to financial services may reduce the economic inequalities for women in these countries. This study examines the influence of digital finance in narrowing the gender gap, guided by the research question: To what extent do digital financial services contribute to narrowing the gender gap in access to and usage of financial services in low-and middle-income economies? Gender inclusion was measured by the ratio of accounts owned by women over the total number of accounts. Digital financial inclusion was constructed based on eight components: mobile money account, storing money in financial institutions, Internet access, mobile phone owned, savings, savings in financial institutions, making or receiving a digital payment, and mobile phone or use of the Internet for shopping. A Bayesian regression approach was computed using the Global Findex Database data for 73 countries classified as low and lower-middle-income economies from 2011 to 2022. The Machine Learning approach evaluates the model’s ability to predict women’s autonomy and the role of digital finance. The results show that digital financial services would reduce the gender gap in low-income economies while augmenting the number of open accounts, especially for women. The results aid in the establishment of policies to reduce the gender gap. These results are relevant to the UNSDG agenda, mainly Goal 5 and Goal 10. Full article

(This article belongs to the Special Issue Applied Econometrics and International Finance: Analysis, Modeling, and Development)

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22 pages, 426 KiB

Open AccessArticle

Uncovering Systemic Risk in ASEAN Corporations: A Framework Based on Graph Theory and Hidden Models

by Marc Cortés Rufé, Jordi Martí Pidelaserra and Cecilia Kindelán Amorrich

Risks 2025, 13(5), 95; https://doi.org/10.3390/risks13050095 - 13 May 2025

Abstract

In the context of an ever-evolving global economy, ASEAN companies face dynamic systemic risk that reshapes their financial interrelationships. This study examines the transmission of these risks using advanced graph theory techniques, particularly the measurement of eigenvector centrality based on Euclidean distances, combined [...] Read more.

In the context of an ever-evolving global economy, ASEAN companies face dynamic systemic risk that reshapes their financial interrelationships. This study examines the transmission of these risks using advanced graph theory techniques, particularly the measurement of eigenvector centrality based on Euclidean distances, combined with a hidden model that incorporates macroeconomic variables, such as GDP. The research focuses on identifying critical nodes within the corporate network, evaluating their contagion potential—both in terms of reinforcing resilience and amplifying vulnerabilities—and analyzing the influence of external factors on the network’s structure and behavior. The findings offer an innovative framework for managing systemic risk and provide strategic guidelines for the formulation of economic policies in emerging ASEAN markets. Full article

(This article belongs to the Special Issue Advances in Risk Models and Actuarial Science)

16 pages, 1027 KiB

Open AccessArticle

The Determinants of Reward-Based Crowdfunding Success in Africa

by Lenny Phulong Mamaro, Athenia Bongani Sibindi and Ntwanano Jethro Godi

Risks 2025, 13(5), 94; https://doi.org/10.3390/risks13050094 - 12 May 2025

Abstract

This study focused on investigating the factors that drive reward-based crowdfunding in Africa, particularly considering the increasing limitations that entrepreneurs face in accessing traditional financial resources globally, by analysing 215 crowdfunding projects from prominent platforms like Kickstarter, IndieGoGo, and Fundraised. The research aimed [...] Read more.

This study focused on investigating the factors that drive reward-based crowdfunding in Africa, particularly considering the increasing limitations that entrepreneurs face in accessing traditional financial resources globally, by analysing 215 crowdfunding projects from prominent platforms like Kickstarter, IndieGoGo, and Fundraised. The research aimed to identify the key drivers of crowdfunding success. The results from an econometric logistic regression analysis revealed that while images, longer campaign durations, and videos positively influenced crowdfunding, they did not significantly contribute to achieving success. In contrast, the number of backers showed a positive and significant impact on outcomes, whereas the targeted funding amount negatively influenced the success. Notably, the presence of spelling errors was found to have a positive, though statistically insignificant, relationship with crowdfunding success. These findings enhance the existing literature on crowdfunding and offer valuable insights into concepts such as information asymmetry and signalling theory within the context of reward-based crowdfunding. Full article

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25 pages, 4566 KiB

Open AccessFeature PaperArticle

How Do Asymmetric Oil Prices and Economic Policy Uncertainty Shapes Stock Returns Across Oil Importing and Exporting Countries? Evidence from Instrumental Variable Quantile Regression Approach

by Aman Bilal, Shakeel Ahmed, Hassan Zada, Eleftherios Thalassinos and Muhammad Hassaan Nawaz

Risks 2025, 13(5), 93; https://doi.org/10.3390/risks13050093 - 9 May 2025

Abstract

This study employs asymmetric quantile regression to investigate the asymmetric impact of WTI crude oil prices and economic policy uncertainty (EPU) on stock market returns from May 2014 to December 2024 in oil-importing (China, India, Germany, Italy, Japan, USA, and South Korea) and [...] Read more.

This study employs asymmetric quantile regression to investigate the asymmetric impact of WTI crude oil prices and economic policy uncertainty (EPU) on stock market returns from May 2014 to December 2024 in oil-importing (China, India, Germany, Italy, Japan, USA, and South Korea) and oil-exporting (Saudi Arabia, Russia, Iraq, Canada, and the United Arab Emirates) countries. The findings reveal that an increase in oil prices significantly impacts the returns of all countries. For oil-importing countries, an increase in oil prices consistently exhibits a positive impact, with insignificant effects in lower and medium quantiles and significant effects in higher quantiles. Conversely, a decrease in oil prices generally decreases stock market returns across all quantiles. This study offers valuable insights for investors to manage risks and improve the predictability of oil price fluctuations. It also provides strategies and policy implications for capitalists and decision-makers. By addressing contemporary issues and using up-to-date data, the study supports financial institutions and portfolio managers in formulating effective strategies. Full article

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29 pages, 1872 KiB

Open AccessArticle

Responding to Climate Policy Risk Through the Dynamic Role of Green Innovation: Evidence from Carbon Information Disclosure in Emerging Markets

by Runyu Liu, Mara Ridhuan Che Abdul Rahman and Ainul Huda Jamil

Risks 2025, 13(5), 92; https://doi.org/10.3390/risks13050092 - 9 May 2025

Abstract

This study investigates how firms in emerging markets respond to climate policy risk, with a particular focus on the dynamic role of green innovation in shaping carbon information disclosure. Using a difference-in-differences (DID) framework, we examine the impact of China’s 2018 carbon reporting [...] Read more.

This study investigates how firms in emerging markets respond to climate policy risk, with a particular focus on the dynamic role of green innovation in shaping carbon information disclosure. Using a difference-in-differences (DID) framework, we examine the impact of China’s 2018 carbon reporting policy, which represents an institutionally significant but non-mandatory regulatory intervention, on the disclosure behaviors of A-share listed firms from 2013 to 2022. The results show that the policy significantly increased firms’ attention to carbon information disclosure, especially among those with limited green innovation capacity. In contrast, firms with stronger innovation capabilities exhibited more stable disclosure practices, suggesting a buffering effect against regulatory uncertainty. Further analysis reveals that the moderating effect of green innovation changes over time, as innovation-oriented firms gradually adjust their disclosure strategies in response to evolving policy expectations. These findings highlight green innovation as a key internal resource that enables firms to strategically adapt to climate policy risks. This study contributes to the literature on climate risk management and corporate sustainability by providing empirical evidence on how dynamic capabilities shape disclosure outcomes and risk management strategies under changing regulatory conditions. Full article

(This article belongs to the Special Issue Climate Change and Economic Impact: Mitigating Risks and Capitalizing on Emerging Opportunities)

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16 pages, 2181 KiB

Open AccessArticle

Achievement of Islamic Finance Objectives: Evidence from the UAE Islamic Banking Industry

by Muhammad Hanif

Risks 2025, 13(5), 91; https://doi.org/10.3390/risks13050091 - 8 May 2025

Abstract

The study documents the achievements of the Islamic Banking Services Industry (IBSI) in light of Islamic finance objectives (including commercial performance, financial stability, and wealth distribution). A balance sheet analysis of IBSI in the United Arab Emirates (UAE) for 33 quarters (2013 Q4–2021 [...] Read more.

The study documents the achievements of the Islamic Banking Services Industry (IBSI) in light of Islamic finance objectives (including commercial performance, financial stability, and wealth distribution). A balance sheet analysis of IBSI in the United Arab Emirates (UAE) for 33 quarters (2013 Q4–2021 Q3) is conducted, focusing on sources and uses of funds, as well as documentation of commercial performance. The findings suggest that the UAE IBSI has remained successful in achieving its micro/primary objectives (commercial performance) and made progress towards partial achievement of its macro/intermediate objectives (financial stability and equitable wealth distribution). While evidence suggests achievements in the area of financial stability, the aspect of equity in wealth distribution requires more focus. The study recommends that regulators develop a legal framework focusing on the business models for IBSI, aimed at achieving broader economic objectives. It is also recommended that managers of UAE IBSI include profit and loss-sharing contracts in deposit collection, financing and investment portfolios. The contribution to the literature includes the documentation of findings on the achievements of UAE IBSI in financial performance, as well as its broader economic objectives within the Islamic financial system. Full article

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