It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
After the global financial crisis, the topic of corporate governance has been gaining momentum in accounting and finance literature since it may influence firm and bank management in many countries. Corporate Governance and Its Implications on Accounting and Finance provides emerging research exploring the implications of a good corporate governance system after global financial crises. Corporate governance mechanisms may include board and audit committee characteristics, ownership structure, and internal and external auditing. This book is devoted to all topics dealing with corporate governance including corporate governance characteristics, board diversity, CSR, big data governance, bitcoin governance, IT governance, and governance disclosure, and is ideally designed for executives, BODs, financial analysts, government officials, researchers, policymakers, academicians, and students.
Fostering Innovation and Competitiveness with FinTech, RegTech, and SupTech provides emerging research exploring the theoretical and practical aspects of technologically innovative mechanisms and applications within the financial, economic, and legal markets. Featuring coverage on a broad range of topics such as crowdfunding platforms, crypto-assets, and blockchain technology, this book is ideally designed for researchers, economists, practitioners, policymakers, analysts, managers, executives, educators, and students seeking current research on the strategic role of technology in the future development of financial and economic activity.
Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.
In today's financial market, portfolio and risk management are facing an array of challenges. This is due to increasing levels of knowledge and data that are being made available that have caused a multitude of different investment models to be explored and implemented. Professionals and researchers in this field are in need of up-to-date research that analyzes these contemporary models of practice and keeps pace with the advancements being made within financial risk modelling and portfolio control. Recent Applications of Financial Risk Modelling and Portfolio Management is a pivotal reference source that provides vital research on the use of modern data analysis as well as quantitative methods for developing successful portfolio and risk management techniques. While highlighting topics such as credit scoring, investment strategies, and budgeting, this publication explores diverse models for achieving investment goals as well as improving upon traditional financial modelling methods. This book is ideally designed for researchers, financial analysts, executives, practitioners, policymakers, academicians, and students seeking current research on contemporary risk management strategies in the financial sector.
Black money and financial crime are emerging global phenomena. During the last few decades, corrupt financial practices were increasingly being monitored in many countries around the globe. Among a large number of problems is a lack of general awareness about all these issues among various stakeholders including researchers and practitioners. Theories, Practices, and Cases of Illicit Money and Financial Crime is a critical scholarly research publication that provides comprehensive research on all aspects of black money and financial crime in individual, organizational, and societal experiences. The book further examines the implications of white-collar crime and practices to enhance forensic audits on financial fraud and the effects on tax enforcement. Featuring a wide range of topics such as ethical leadership, cybercrime, and blockchain, this book is ideal for policymakers, academicians, business professionals, managers, IT specialists, researchers, and students.