Institutional Stability Research Articles

COMPARATIVE ANALYSIS OF RF, SVR WITH GAUSSIAN KERNEL AND LSTM FOR PREDICTING LOAN DEFAULTS

This investigation elucidates the paramount endeavour of predicting loan defaults, which is imperative for the efficacious management of financial risk and the overall stability of financial institutions. Conventional statistical methodologies frequently encounter challenges in effectively capturing the nonlinear and sequential dynamics inherent in financial data, thereby necessitating the examination of more sophisticated machine learning methodologies. This research reports an experimental-based comparative evaluation of three ML and DL models—Long Short-Term Memory (LSTM) networks, Random Forest (RF), and Support Vector Regression (SVR)—to assess their efficacy in forecasting loan defaults. The models are evaluated using metrics such as Mean Squared Error (MSE), F1 score, and Accuracy, and their proficiency in addressing imbalanced datasets and elucidating intricate data relationships is highlighted. The results indicate that while the Random Forest model surpasses its counterparts in terms of accuracy and MSE, the LSTM model exhibits considerable potential in managing imbalanced data, as evidenced by its stable F1 score. Although SVR reveals competitive precision, it exhibits deficiencies in addressing class imbalance. The ANOVA analyses substantiate that the disparities in model performance are statistically significant. The research acknowledges that both the LSTM and SVR models remain in the developmental stages, with ongoing initiatives aimed at refining these models through hyperparameter optimization and advanced architectural frameworks to enhance their predictive efficacy in practical applications.

POPULIST POLITICS IN PAKISTAN: A CASE STUDY OF PAKISTAN THREEK -E- INSAF (PTI) FROM 2018-2023

Populism, although not a new political ideology, has witnessed a significant resurgence since the late 20th century. Emerging initially among Southern sharecroppers and tenant farmers in the United States during the 1880s, populism has since manifested globally, characterized by its opposition to elites and its appeal to the "common people." This thesis explores the nature of populism, its ideological foundations, and its impact on contemporary politics, with a particular focus on Pakistan's political landscape. The study critically examines the populist strategies of Pakistan Tehreek-e-Insaf (PTI) and its leader Imran Khan, assessing their socio-political and economic consequences from 2018 to 2023. By distinguishing between populist and non-populist politics in Pakistan, this research provides a comprehensive analysis of PTI's rise and its implications for democracy and governance in the region. The analysis reveals the intricate dynamics between populist rhetoric and policy, and their effects on the economic and sociopolitical fabric of Pakistan. Key findings indicate that PTI's populist approach has significantly reshaped political discourse and governance structures, promoting a narrative that pits the "pure people" against the "corrupt elite." The thesis also highlights the broader implications of populism for democratic practices, suggesting that while populism can invigorate political engagement and address genuine grievances, it also poses challenges to pluralism and institutional stability. Ultimately, this research contributes to a deeper understanding of populism in the Pakistani context, offering valuable insights into its potential trajectories and the critical balance required to sustain democratic values amidst rising populist sentiments.

CHALLENGES TO PUBLIC ADMINISTRATION IN THE CONTEXT OF INTERNAL MIGRATION IN UKRAINE

The article addresses the challenges faced by public administration in managing internal migration in Ukraine, driven by large-scale population movements due to the Russian-Ukrainian war, and the necessity of maintaining the stability of state institutions amidst social, economic, and demographic shifts. The purpose of the article is to identify the primary challenges confronting public administration in the context of internal migration and propose strategies to address them. To achieve this, the study employs an integrated approach, combining both quantitative and qualitative research methods. The article identifies the causes of internal migration and the key factors contributing to internal displacement: armed conflict, economic hardships, and social and environmental issues. It analyzes the main challenges to public administration in this context, including organizational difficulties, coordination problems between different levels of government, a lack of resources for effectively managing migration processes, and socio-economic challenges. It is demonstrated that there is insufficient infrastructure to provide housing, employment, and social services for internally displaced persons (IDPs), along with inadequate funding for support programs, and difficulties in integrating IDPs into new communities and fostering interaction with the local population. The article reviews state policy on internal migration, evaluates existing programs and strategies, assesses the effectiveness of current state initiatives, and highlights the barriers to implementing effective IDP policies, such as underfunding and lack of coordination. The author proposes solutions to enhance coordination and management, develop a unified migration management system, engage local communities in addressing IDP issues, increase funding and resources, expand state support programs, attract international assistance to tackle internal migration challenges, and implement legal reforms. Recommendations for improving migration management are also provided to overcome these challenges.

PUBLIC ADMINISTRATION UNDER MILITARY THREATS: UKRAINIAN EXPERIENCE OF ADAPTING TO CRISIS SITUATIONS

The article examines the Ukrainian experience of public administration under conditions of military threat as of 2022-2024. The key challenges faced by Ukraine during the full-scale war are analyzed, including the destruction of critical infrastructure and the need to ensure uninterrupted provision of public services. Special attention is paid to the digitization of public administration, which played a decisive role in maintaining the stability of state institutions. The role of the «Action» platform and other innovative solutions that enabled interaction between citizens and the government in crisis conditions is described. The impact of decentralization on the ability of local authorities to respond to the challenges of war has been studied. The interaction with international partners within the framework of the SIGMA program, which is aimed at providing support in the reform of public administration with a course towards European integration, is characterized. A comparative analysis of the Ukrainian experience with other European countries that faced large-scale crises was carried out, and unique aspects of the Ukrainian model of adaptation were revealed. The article analyzes strategies for the restoration and modernization of the state administration of Ukraine in crisis conditions. Attention is focused on the interaction between the state and corporate sectors to maintain economic activity even in conditions of active hostilities. The role of business relocation to safer regions and the influence of state support on the stabilization of the labor market and the economy are outlined. Programs aimed at restoring infrastructure and vital services in cooperation with international partners are mentioned. The experience of implementing temporary solutions to ensure the basic needs of the population is described. It examines the impact of international aid and financial support through IMF and World Bank programs that helped maintain budget stability and avoid economic collapse. The perspectives of public administration during Ukraine's integration into European structures and further strengthening of public administration are highlighted. Special attention is paid to the prospects for the development of public administration in the post-war period, the solution of socio-economic problems, the restoration of infrastructure and the attraction of investments. Strategic directions for reforming public administration for the future are proposed, taking into account the experience of the war and cooperation with international institutions.

Stability of financial institutions under the influence of cyber threats

Stability of financial institutions under the influence of cyber threats

Forging the Resistive Republic: Social Capital, Institutional Stability, and Civic Virtue in Pluralist Democracies

Republicans too often take for granted features not easy to bring about in the absence of social capital. Lovett and Pettit (2009) consider that it is through collective political actions that citizens shed light on acts of domination. For Pettit (2012), civic vigilance is the only guarantee that “the government will be forced to remain responsive to popular inputs”. As Kimpell (2023) mentions, one of the weak points of republican theories remains the lack of an account of norm generation. I aim to show how this could occur in a way that does not constitute itself an arbitrary interference of the government in the people’s lives. The kind of generalized reciprocity which is of utmost importance for republicanism often depends on the presence of ties that connect different socio-economic groups within communities and, “where such interactions do not naturally occur, forums for interaction can be intentionally created and designed to encourage development of social capital” (Warner 2001). More specifically, I argue that such forums for interaction could be represented by polycentric systems. Furthermore, I argue that embracing polycentricity constitutes a non-dominating way in which we could promote the “resistive community” (Pettit 2012) required by republicanism. I consider that the empirical results extensively documented in the Institutional Analysis and Development framework are an appropriate starting point for designing novel republican policies and institutions that can function alongside sufficient levels of trust.

Impacts of Industrial Disharmony on Tertiary Institutions in Nigeria

The issue of disharmony in Nigerian tertiary institutions has become a significant challenge, affecting academic quality, institutional stability, and national development. This paper examines the various cases and underlying causes of disharmony within Nigerian universities, polytechnics, and colleges of education. Through a critical review of the literature and empirical data, the paper highlights the adverse impacts of disharmony, such as reduced academic productivity, a decline in the quality of graduates, infrastructural decay, and loss of public trust in higher education. The study argues that addressing disharmony requires collaborative efforts between government, management of institutions, staff unions, and students. By promoting inclusivity, strengthening institutional autonomy, and ensuring effective conflict management mechanisms, Nigerian tertiary institutions can foster a more harmonious and productive academic environment.

The erosion of democracy in an age of wealth inequality: Unravelling the impact of subjective socioeconomic stratification

Since the 1980s, the growing wealth disparity in advanced capitalist societies has drawn attention from political economy scholars due to its profound effects on political systems. This research explores the relationship between wealth inequality and the stability of democratic institutions, focusing on how subjective class perceptions shape support for democratic governance. The findings indicate that as wealth inequality intensifies, it significantly reshapes class identities, influencing attitudes towards democracy. Both the subjective lower and upper classes exhibit diminished support for democratic systems, albeit for different reasons, which may pose risks to democratic stability. In contrast, the subjective middle class, a stronghold of democratic values, is shrinking in both proportion and influence as wealth inequality widens, potentially weakening democratic institutions further. This study underscores the connection between increasing wealth inequality and challenges to democratic values, highlighting the importance of policy measures to protect democratic integrity in the face of rising economic disparities.

The Impact of Digitalization on Credit Risk Management in Microfinance Institutions in Nueva Ecija, Philippines

The study examines the credit risk management practices of lending institutions in rural Nueva Ecija, Philippines, amidst their significant growth and the evolving economic landscape. Given their pivotal role in financial transactions, these institutions face inherent risks which necessitate effective management strategies. Employing a descriptive method, the research identified and evaluated credit risk management practices, focusing on credit analysis and collection policies. The study also assessed the impact of digitalization on these practices within microfinance institutions in the region. Findings indicated that while there was no significant relationship between credit risk management practices and loan collection performance, digitalization emerged as a promising avenue for enhancing efficiency and reducing risks. Metrics such as portfolio-at-risk, on-time repayment rate, and past due rate were used to evaluate loan collection performance. The study underscores the potential of digital tools and platforms in transforming credit risk management, offering opportunities to streamline operations and improve collection policies. It identifies current market challenges and outlines strategies to mitigate risks effectively, thereby enhancing the stability and efficacy of rural lending institutions in Nueva Ecija.

Mapping Non-Performing Assets: Figures from Dimension AI database

The issue of non-performing assets (NPAs) or non-performing loans (NPLs) presents a significant challenge in the financial sector, affecting the stability and profitability of financial institutions globally. Conducting a bibliometric analysis of NPLs aims to understand the current research landscape and identify opportunities for future study, ultimately contributing to the development of effective strategies to manage and mitigate the impact of NPLs. Systematic review analyzes articles in Banking, Finance, and Investment, focusing on Non-Performing Assets (NPAs) or Non-Performing Loans (NPLs) published between 2020 and 2024. 33 documents were selected based on relevance to the topic. Through rigorous filtering and review, key insights, methodologies, and findings were extracted from the selected articles. Articles related to Non-Performing Assets/Loans, the Malaysian Management Journal emerged as the most cited publication, with five citations. The research conducted by the Institute of Cost Accountants of India and Vidyasagar University also garnered considerable attention. Among the individual papers, those authored by Maity and Tarak Nath received five citations each. The findings of the study highlighted key themes including Efficiency Decline, NPL Impact on Performance, Capital Adequacy Influence, Credit Risk Moderation, Persistent NPA Challenges, and Complex Factors Contributing to NPLs. These findings underscore the multifaceted nature of NPAs and NPLs, emphasizing their significant impact on the banking and finance sector. Study underlines landscape of NPAs/NPLs, identifying key themes, influential publications, and authors, thus guiding future research directions and strategic interventions for managing NPAs/NPLs in the financial sector. bibliometric analysis of NPAs/NPLs in Banking, Finance, and Investment fields from 2020 to 2024.

"City upon a Hill" in the Face of Significant Challenges

The editor-in-chief proposes a context for examining the crisis processes in American society explored in the articles. The author suggests that this crisis should be viewed in the context of the American history cycles. Many of the current conflicts in the USA have a similar internal source, which is a sharp intra-elite conflict involving a significant part of society. This conflict is unusual in its depth, given that for many decades the «trademark» of the American political class has been its consensus character. One important element of this consensus can be seen as an unquestioned focus on global American leadership and a shared commitment among members of the community to the force imperatives in foreign policy – either the classic “hard” or “flexible” power. Among the sources of American foreign policy continuity are a number of factors. First, it is the stability of institutional mechanisms of decision-making, which, in turn, is based on a stable system of representation of dominant interests. Second, the stability of formal and informal institutions that ensure a high degree of elite cohesion; and the specificity of American political culture, which is based on a set of political and philosophical views of messianic nature. The consensual nature of the political elite was the system-forming basis of liberal democracy, so the breakdown of this consensus may entail – and partially has already entailed – a crisis of the US political system.

Analisis Deskriptif Penerapan Kecerdasan Buatan, Prediksi Integritas, Kinerja Keuangan dan Ukuran Perusahaan di Perbankan Indonesia dan Singapura Tahun 2021 – 2023

This study aims to analyze the application of artificial intelligence, integrity prediction, financial performance, and company size in the Indonesian and Singapore banking sectors during the 2021-2023 period. Secondary data is used in this study, including annual reports, financial reports, and other relevant data sources. The quantitative descriptive method was applied to analyze the collected data. The results show that the adoption of artificial intelligence in the banking sector has had a positive impact on operational efficiency, fraud detection, and risk management. In addition, corporate integrity prediction plays an important role in maintaining the stability and reputation of financial institutions, with artificial intelligence technology assisting in detecting potential risks and fraudulent activities. This study also found that firm size, as measured by total assets, contributes significantly to bank financial performance. These findings make an important contribution to the literature and provide insights for policy makers and banking practitioners to optimize the use of artificial intelligence technology and integrity prediction in improving firm performance and competitiveness.

Advancing credit risk assessment and financial decision-making: Integrating modern techniques and insights

Credit risk assessment and fraud detection are critical functions in the financial industry, necessary for ensuring the stability and integrity of financial institutions. Traditional approaches often struggle to accurately assess risk and detect fraudulent activities in a timely manner. However, the rise of machine learning has introduced powerful tools that leverage large datasets and advanced algorithms to improve these processes. This research paper investigates the application of machine learning techniques in credit risk assessment and fraud detection within financial transactions. The paper begins by emphasizing the importance of accurate risk assessment and fraud detection in the financial sector and introduces machine learning as a solution to the limitations of traditional methods. A thorough literature review examines existing methodologies, algorithms, and trends, highlighting the advancements in this field. The discussion covers data acquisition and preprocessing techniques, underscoring the necessity of clean and relevant data for effective model training. Additionally, feature engineering strategies are explored to extract valuable insights from financial transaction data, enhancing the predictive power of machine learning models. The research analyzes various machine learning algorithms, such as logistic regression, decision trees, random forests, support vector machines, and neural networks, as well as ensemble methods. Model evaluation metrics, including accuracy, precision, recall, and ROC-AUC, are employed to assess the performance of these algorithms. The paper presents case studies and experimental results to demonstrate the practical application of machine learning models in real-world scenarios, showcasing their effectiveness in improving credit risk assessment and fraud detection. Furthermore, the research explores challenges such as imbalanced datasets, model interpretability, and regulatory compliance, offering insights into potential solutions and future research directions. The integration of behavioral finance, Bayesian networks, and optimization methods is also discussed, highlighting how these modern approaches, combined with big data analytics, can enhance predictive accuracy and decision reliability. In conclusion, this research underscores the transformative potential of machine learning in credit risk assessment and fraud detection within financial transactions. By adopting advanced algorithms and data-driven approaches, financial institutions can significantly improve their risk management strategies, mitigate potential risks, and protect against fraudulent activities. This ultimately contributes to a more secure and resilient financial ecosystem, enabling institutions to maintain a competitive edge in an ever-evolving market.

Institutional model of the financial services market and its development

In the paper, the institutional model of the financial services market in Ukraine is defined as a complex system that ensures the interaction of its various subjects, regulates their activities and contributes to the stable and effective functioning of the financial sector based on taking into account the role and relationships of public and private organizations, legal and regulatory frameworks, as well as socio-economic factors that affect the functioning of the financial services market. Three stages of the development of the financial services market in Ukraine are highlighted, their characteristics, achievements and challenges are given. The main components of the institutional model of the financial services market are defined. It is shown that high-quality infrastructure and effective debt settlement institutions are critical for maintaining the financial stability of credit institutions. The purpose of the reform of state regulation based on the model of a single regulator is determined, which consists in increasing the efficiency, transparency and stability of the financial market. The advantages of a single regulator based on the NBU are: consolidation of functions, improvement of efficiency, reduction of administrative costs, improvement of coordination, increase of transparency, reduction of duplication. The challenges are: the difficulties of the transition period, the need to maintain specialization and the implementation of management changes. It is shown that the financial ombudsman plays an important role in the system of institutions for professional regulation of financial services markets. At the initial stage of implementation of the said institute, its role as a mediator is critically important for creating an effective mechanism for resolving conflicts and ensuring trust in the financial market. It has been established that the financial ombudsman performs the functions of: an independent mediator based on the principles of neutrality and confidentiality; supports the resolution of conflicts based on the analysis of the situation and the proposal of solutions, improves communication by organizing meetings and ensuring a clear exchange of information; ensures transparency and fairness by clarifying rights and obligations, creating standards for mediation; increases confidence in the financial market on the basis of reducing conflicts and improving the reputation of the financial market.

Cognitive microfoundations and social interaction dynamics. The implications of complexity for institutional theory

AbstractThis paper investigates the intersection of cognitive sciences and social network theory and its counterpart, the complexity sciences, aiming to shed light on the compatibility and potential integration of these frameworks into institutional theory. Institutional scholars have for long selectively adopted notions linked with the cognitive sciences and complexity sciences, such as the notion of path dependence, without exploring the broader implications of systematically integrating such perspectives into institutionalism. This paper aims to advance such a comprehensive theoretical integration, by investigating the effective combination of these approaches and their significant implications. It shows how the complexity sciences contribute to dissolving the barriers between the cognitive and social realms and illustrates how this impacts notions of human agency and reflexivity. Theoretical integration also involves acknowledging considerable diversity in individual human agency, which in turn prompts a reconsideration of how notions of institutional stability, change, diffusion and adaptation are understood. Furthermore, the paper addresses the epistemological challenge presented by the complexity sciences, before it highlights the general relevance of institutional theory in analyzing complex social phenomena. Finally, the paper explores implications for research methodology, proposing that a fusion of institutional theory and the complexity sciences provides a metatheoretical framework for assessing the contextual suitability of different theoretical and methodological approaches.

The effect of ESG scores on bank stability: Islamic vs. conventional banks

ABSTRACT This paper examines the impact of ESG (Environmental, Social, and Governance) factors on the stability of banks across different continents, focusing on both conventional and Islamic banking institutions. The empirical analysis indicates a positive influence of ESG activities on the stability of these financial institutions. Notably, the study finds that ESG scores significantly enhance the stability of both conventional and Islamic banks. The environmental pillar score, especially within the conventional banking sector, shows highly positive and statistically significant results, highlighting the benefits of environmentally responsible practices. In contrast, the social pillar is positively correlated with stability in the Islamic banking sector, suggesting that active involvement in community service and social responsibility initiatives leads to improved stability. Overall, the study emphasizes the transformative potential of ESG activities in enhancing the stability and valuation of banks by positively influencing both their external perception and internal operations.

Sustainability of the Urban System Planning in Shu City, Kazakhstan: An Evaluation through Residents’ Perception

It is important to consider the local people’s evaluation in increasing the effectiveness of the sustainable planning process in urban system planning. In this work, the sustainability of urban system planning in Shu city of Kazakhstan is evaluated according to the defined dimensions, which play a key role in determining the population’s living standard, and the indicators of each dimension are compared. The data are obtained mainly through the household questionnaire survey, field observations, in depth interviews, and focus group discussion. In total, 832 representative respondents were surveyed with five-point Likert scale questions in this paper. The study used 42 indicators based on six dimensions: environmental, social, cultural, economic, religious/spiritual, and institutional dimensions. The results of this analysis show that the sustainability level of urban system planning in Shu city is at a low level in all six dimensions. The results of the indicator analysis show that the people of this region are generally not satisfied with the solution of some environmental, social, and economic problems in Shu city. At the same time, residents rated the indicators of institutional stability as better, on the contrary, they rated cultural and religious/spiritual indicators relatively high. As a result, we initially asserted that the sustainability of the urban system planning in Shu city is not satisfactory considering the existing possibilities. To eliminate this shortcoming, the authorities responsible for planning the urban system should jointly develop a project policy for sustainable development with all interested parties.

THE APPROXIMATION OF THE ALBANIAN PROCUREMENT LEGISLATION WITH THE EU LEGISLATION

Public procurement is a process performed by the Contracting Authorities which select the Economic Operators through a public competition, to enter into public contracts for the provision of goods, services, or works, against payment from public funds. The area of public procurement is very important in the management and spending of public money because public procurement is the environment where public money is filtered to have the least possible misuse, and financial stability of state institutions so that they are more consistent in the functioning and development of professional activities.Therefore, in this context, the present paper will analyze the Albanian perspective on public procurement to comprehend its alignment with EU legislation. This paper is coherent with the integration process requirements imposed on Albania and will demonstrate the positive achievements reached and the long path ahead to become a member of the European Union family.

The Montenegrin Olympic Committee: exploring issues in Sports Governance

ABSTRACT The recent doping scandal in Montenegro waterpolo team during the World Aquatics Championships in Qatar this year, yet again opened the debate on a number of sports-related governance issues. The foundation of these challenges lies in the very essence of how the sports ecosystem is structured, organized, and operated. The major outputs of the contemporary studies confirmed that the politicization of relations within the sports ecosystem plays a principal role, in shaping, directing, and utilizing sports for non-sporting objectives. The results indicate that this constellation has been facilitated through the transformation of informal practices into regulatory regimes or bypassing, when needed, existing legislative frameworks in order to contribute to institutional stability. The politicization represents a joint determinant of the closed, vertically structured governing bodies and decision-making system with long-lasting individuals in decision-making positions without any internal or external control in practice. The internal regulations facilitate no restrictions on conflicts of interest, measures aimed to tackle corruption, or to provide a check and balance system between governing bodies. Furthermore, following the public service culture, the Montenegro Olympic Committee maintains its closed and exclusive composition of governing bodies rests on discretionary power and a decision-making approach with a democratic deficit.

Comparison of machine learning models in credit risk assessment

Crdit risk plays an important rol in financ. In a sns, crdit risk rflcts th stability of financial institutions and th protction of invstors. Du to th impact of th pidmic on th world conomy, w nd to rassss th crdit risk. For a long tim, machin larning and dp larning in statistics hav bn vry ffctiv in prdicting crdit risk. But in machin larning and dp larning, whn prdicting crdit risk, w citd four modls, namly XGBoost, Dcision Tr, Random Forst and Convolutional Nural Ntwork (CNN) modls. Analyz th advantags and disadvantags of ths modls: XGBoost can optimiz th tr modl and prvnt ovrfitting through rgularization, but XGBoost has poor intrprtability. Dcision Tr has strong xplanatory powr, but it is prone to overfitting. Compared with th dcision tr, Random Forsts incras accuracy and rduc th probability of overfitting, but Random Forsts consum mor tim and computing rsourcs. Although Convolutional Nural Ntwork has a high accuracy rat, it abandons intrprtability. Thrfor, in our xprimnts, w found that ths modls ar not prfct and hav thir own dfcts. So, in futur rsarch, w will mak an intgratd modl to includ th advantags of th modl and discard som dfcts, so that th intgratd modl will hav bttr gnralization and accuracy.