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Catalogue complet

Nabil Nakbi

Assessing Credit Default Risk Using Logistic Regression. A Transparent Approach to Scoring with the UCI Dataset and SPSS

Springer Nature Proceedings excluding Computer Science

José C. Matos

Paulo B. Lourenço

Daniel V. Oliveira

Jorge Branco

Dirk Proske

Rui A. Silva

Hélder S. Sousa

IPW 2024

20th International Probabilistic Workshop

Tamilla Javadi

Tesla, Inc. Strategic Expansion and Value Creation through the Gigafactory Berlin-Brandenburg

Master Financial Risk Management and Protect Your Future

Financial risk is unavoidable, but understanding and managing it effectively can mean the difference between financial stability and crisis. From market fluctuations and credit defaults to liquidity shortages and operational failures, individuals and businesses face a range of challenges that can impact financial health and long-term success.
This book breaks down key financial risks, including market, credit, liquidity, operational, and systemic risks, while offering practical strategies to assess, mitigate, and manage them effectively. Learn how to navigate interest rate volatility, foreign exchange fluctuations, regulatory changes, and unforeseen global events with proven risk management techniques like hedging, diversification, credit analysis, and crisis planning.

With real-world examples, expert insights, and actionable strategies, this guide is an essential resource for investors, business leaders, and financial professionals looking to minimize losses and maximize financial security.

Prepare for the unexpected, mitigate risk, and make smarter financial decisions-because a strong risk management strategy is the key to financial success.

Identifying, Assessing, and Mitigating Uncertainty for Stability and Success

Financial Risk Management Modeling [AI]

The increasing relevance of&nbsp;ESG (Environmental, Social, and Governance) in financial research and practice is driven by&nbsp;materiality,&nbsp;investor demand, and&nbsp;regulatory developments. Since ESG initiatives often entail (high) costs for companies, the question arises whether such investments “pay off” in terms of higher performance or lower risk. Previous research has primarily focused on the&nbsp;shareholder value perspective. More recent studies examine ESG from a&nbsp;risk perspective, mainly equity-based. However, studies exploring the relationship between ESG and&nbsp;credit risk&nbsp;remain scarce, especially in the&nbsp;European context. From a&nbsp;principal-agent theory&nbsp;perspective, it can be assumed that&nbsp;creditors&nbsp;evaluate ESG investments differently than&nbsp;owners. Creditors are primarily concerned with the servicing of their claims from the company’s cash flow and generally favor&nbsp;less risky investments. The aim of this study is to provide a&nbsp;comprehensive overview&nbsp;of the existing empirical literature and to&nbsp;expand it through an original empirical investigation.The AuthorDr. Anna Gappmaier 
 works at the Department of Corporate Finance, at Johannes Kepler University Linz. Her research focuses on issues related to sustainability and ESG from a corporate finance perspective.
 The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. 
 This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

An Analysis of European Corporate Bonds

The Influence of ESG on Credit Risk

Melanie Tippel

Finanzpolitik in der Bundesrepublik Deutschland. Theorie und Praxis am Beispiel der Schuldenbremse und des "Sondervermögens Bundeswehr"

Integrating Artificial Intelligence for Next-Generation Financial Services

Deep Learning in Banking

Springer Proceedings in Business and Economics

Proceedings of the World Finance & Banking Symposium, Brno – Czech Republic 2025

Advances in Banking and Finance

Economics and Finance (R0)

Chris DeLong

Andrew McKenzie

Thomas Meierotto

Core Concepts and Real-World Scenarios

Physical Grain Trading

 Anonymous

Central Bank Digital Currency. Eine kritische Analyse der ökonomischen und gesellschaftlichen Folgen

&lt;p&gt;In recent years, macroeconomic dynamics, social transformations, technological innovations, and regulatory developments have caused significant changes in the banking industry, but most especially the need to integrate ESG factors into corporate strategies. Exploring&amp;nbsp;the commitment towards sustainable business as not only a regulatory compliance obligation but as a value creation opportunity, this book explores ESG factors and sustainability issues in the banking sector and proposes a holistic approach to ESG risks. It&lt;strong&gt;&amp;nbsp;&lt;/strong&gt;presents useful suggestions and guidance for the promotion of further development and practical initiatives on ESG in banks, and will be of interest to researchers, government regulators, supervisor authorities, and policymakers in banking and financial services.&lt;strong&gt;&lt;strong&gt; &lt;/strong&gt;&lt;/strong&gt;&lt;/p&gt;


Elisa Menicucci

Navigating Regulatory Frameworks and Strategic Challenges for Financial Institutions

ESG Integration in the Banking Sector

A comprehensive and practical collection of tools and frameworks for risk governance at banks, insurance firms, asset managers, and other financial organizations In Risk Framework Design in Practice: Getting Risk Governance and Limits Right for Financial Institutions, veteran portfolio and risk manager, Michelle Beck, delivers a robust and functional approach to risk governance that's perfect for financial institution managers and executives. Beck skips the high-level bromides, &nbsp;avoids narrowly considering only one type of asset class or financial institution, and instead offers practical guidance for leaders across the full scope of the industry seeking to answer critical risk management questions: What types of risk limits are necessary? How many of them does my organization need? How should they be set? Are minimum regulatory standards sufficient to safeguard my company's interests? Risk Framework Design in Practice provides an effective structure for enterprise risk limits in different types of firms, including banks, asset managers, insurers, and corporate pensions. It explains how these types of firms should establish risk appetites, the essential pieces of their governance structures, and how to ensure the right information is in the right hands at the right times. It also includes: <ul> <li>Deep dives into the relevant limits for market, credit, and operational risks, including the implications of using alternative methods</li> <li>Detailed discussions of contemporary approaches to limiting economic capital, value at risk, stress tests, exposures, liquidity, concentrations, stop-losses, and drawdown limits</li> <li>Approaches to operational risk that avoid the expensive trap of attempting to police business efficiency, and instead focus on control strength for truly dangerous risks</li> </ul> Risk Framework Design in Practice is an effective resource for chief risk officers and professionals working in enterprise risk departments at banks, broker dealers, insurance companies, asset managers, and hedge funds.&nbsp; Also perfect for board members at banks and insurance companies, in-house counsel at financial firms, and bank and securities regulators.

Getting Risk Governance and Limits Right for Financial Institutions

Risk Framework Design in Practice

Bachelor Thesis from the year 2023 in the subject Economics - Finance, grade: 100, University of Applied Sciences Bern (Bern university of applied sciences), course: Digital Business Management, language: English, abstract: The financial sector is undergoing a profound transformation driven by digitalization and technological advancements. In this dynamic landscape, financial institutions are reassessing their strategies to stay competitive. The integration of smart technologies and the pursuit of customer-centric business models are key elements in this transformative journey.As technology reshapes traditional paradigms, the financial industry experiences a seismic shift towards digital transformation. Fintech's emergence and the importance of smart services redefine operations, challenge business models, and create avenues for innovation. This literature review explores the theoretical framework of digital transformation, dissecting definitions, and explaining its impact on finance.The review investigates future business models in finance, emphasizing their digital aspects and the delicate balance between replication and innovation. Shifting focus to customers, it explores the evolving concept of customer-centricity and the role of customers as co-creators in business models. Integration of customers with smart technology becomes a critical aspect, examining technology acceptance and the role of empathic AI.Methodologically, the review outlines a systematic approach, including the identification of relevant research databases, search keywords, and meticulous study selection. The results section uncovers gaps, perspectives, and recommendations in existing literature, providing a foundation for discussion.The discussion navigates barriers hindering customer acceptance of smart technology, explores factors in implementing customer-centric business models, and delves into building trust in the digital era. The paper concludes by outlining future research directions and offering practical insights for financial institutions.In essence, this review serves as a compass through the complex terrain of digital transformation in finance, unraveling future business models, customer-centricity, and the integration of smart technologies. It contributes valuable insights to academics, practitioners, and decision-makers in the financial industry.

Houssem Gharbi

Successful Digital Transformation in Finance. Customer-Centricity and Future Business Models Beyond Smart Technologies

Assessing Credit Default Risk Using Logistic Regression. A Transparent Approach to Scoring with the UCI Dataset and SPSS

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