The Covid-19 pandemic has not only posed significant challenges to public health but has also profoundly impacted various aspects of society, including education. In Bangladesh, students have faced unprecedented disruptions to their academic, social, and psychological well-being due to the pandemic-related restrictions. This study aims to assess the socio-psychological impact of the Covid-19 pandemic on students in Bangladesh. Through surveys, interviews, and qualitative analysis, we explore the experiences, challenges, and coping mechanisms of students during the pandemic. Our findings highlight the multifaceted nature of the pandemic's impact, including academic setbacks, social isolation, mental health concerns, and economic hardships. Additionally, we identify resilience factors and support systems that have helped students navigate these challenges. By understanding the socio-psychological landscape, policymakers and educators can develop targeted interventions to support students' well-being and foster resilience in the face of future crises.

This paper presents a conceptual framework to evaluate the impact of fraud risk management and risk culture on the performance of the banking sector. The framework integrates key components of fraud risk management, including detection, prevention, and response strategies, with the elements of a robust risk culture, such as ethical behavior, risk awareness, and organizational values. By examining the interplay between these factors, the framework aims to provide insights into how banks can enhance their performance through effective risk management practices. The study underscores the importance of a proactive risk culture in mitigating fraud and highlights the potential performance gains from a comprehensive approach to fraud risk management. This conceptual framework serves as a foundation for future empirical research and practical applications in the banking industry.

The banking industry's metamorphosis through digitalization has unquestionably revolutionized accessibility and convenience for customers worldwide. However, this paradigm shift has ushered in a new era of challenges, most notably in the realm of cybersecurity. Conventional rule-based fraud detection strategies have struggled to keep pace with the rapid evolution of cyber threats, prompting a surge of interest in more adaptive approaches like unsupervised learning. Furthermore, the COVID-19 pandemic has exacerbated the issue of bank fraud due to the widespread transition to online platforms and the proliferation of charitable funds, which present ripe opportunities for exploitation by cybercriminals. In response to these pressing concerns, this study delves into the realm of machine learning algorithms for the analysis and identification of fraudulent banking transactions. Notably, it contributes scientific novelty by developing models specifically tailored to this purpose and implementing innovative preprocessing techniques to enhance detection accuracy. Utilizing a diverse array of algorithms, including Random Forest, K-Nearest Neighbor (KNN), Naïve Bayes, Decision Trees, and Logistic Regression, the study showcases promising results. In particular, logistic regression and decision tree models exhibit impressive accuracy and Area Under the Curve (AUC) values of approximately 0.98, 0.97 and 0.95, 0.94, respectively. Given the pervasive nature of banking fraud in our digital society, the utilization of artificial intelligence algorithms for fraud detection stands as a critical and timely endeavor, promising enhanced security and trust in the financial ecosystem.

This article explores the diverse range of state support measures available to small businesses in Uzbekistan. By analyzing these initiatives and their impact, it seeks to provide insights into how government policies are shaping the small business landscape and fostering an environment conducive to entrepreneurship. Understanding these dynamics is crucial for policymakers, business owners, and stakeholders aiming to promote sustainable economic development and inclusive growth in Uzbekistan.