Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
323,269
result(s) for
"Credit Management"
Sort by:
Credit risk
Modelling credit risk accurately is central to the practice of mathematical finance. This volume of the Mastering Mathematical Finance series offers a comprehensive and accessible introduction to the subject tailored specially for master's students. The book focuses on the two mainstream modelling approaches to credit risk, namely structural models and reduced form models, and on pricing selected credit risk derivatives. Balancing rigorous theory with real-world examples from the post-credit crisis financial markets, it takes readers through a natural development of mathematical ideas and financial intuition. Students, practitioners and researchers alike will benefit from the compact presentation and detailed worked examples, exercises and solutions.
Book
The handbook of credit risk management
Discover an accessible and comprehensive overview of credit risk management
In the newly revised Second Edition of The Handbook of Credit Risk Management: Originating, Assessing, and Managing Credit Exposures, veteran financial risk experts Sylvain Bouteillé and Dr. Diane Coogan-Pushner deliver a holistic roadmap to credit risk management (CRM) ideal for students and the busy professional.
The authors have created an accessible and practical CRM resource consistent with a commonly implemented risk management framework. Divided into four sections—Origination, Credit Assessment, Portfolio Management, and Mitigation and Transfer—the book explains why CRM is critical to the success of large institutions and why organizational structure matters.
The Second Edition of The Handbook of Credit Risk Management also includes:
* Newly updated and enriched data, charts, and content
* Three brand new chapters on consumer finance, state and local credit risk, and sovereign risk
* New ancillary material designed to support higher education and bank credit training educators, including case studies, quizzes, and slides
Perfect for risk managers, corporate treasurers, auditors, and credit risk underwriters, this latest edition of The Handbook of Credit Risk Management will also prove to be an invaluable addition to the libraries of financial analysts, regulators, portfolio managers, and actuaries seeking a comprehensive and up-to-date guide on credit risk management.
eBook
Credit Risk Analytics
The long-awaited, comprehensive guide to practical credit risk modeling
Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics.
SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models.
* Understand the general concepts of credit risk management
* Validate and stress-test existing models
* Access working examples based on both real and simulated data
* Learn useful code for implementing and validating models in SAS
Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
eBook
SHAP Stability in Credit Risk Management: A Case Study in Credit Card Default Model
The rapid growth of the consumer credit card market has introduced substantial regulatory and risk management challenges. To address these challenges, financial institutions increasingly adopt advanced machine learning models to improve default prediction and portfolio monitoring. However, the use of such models raises additional concerns regarding transparency and fairness for both institutions and regulators. In this study, we investigate the consistency of Shapley Additive Explanations (SHAPs), a widely used Explainable Artificial Intelligence (XAI) technique, through a case study on credit card probability-of-default modeling. Using the Default of Credit Card dataset containing 30,000 consumer credit accounts information, we train 100 Extreme Gradient Boosting (XGBoost) models with different random seeds to quantify the consistency of SHAP-based feature attributions. The results show that the feature SHAP stability is strongly associated with feature importance level. Features with high predictive power tend to yield consistent SHAP rankings (Kendall’s W = 0.93 for the top five features), while features with moderate contributions exhibit greater variability (Kendall’s W = 0.34 for six mid-importance features). Based on these findings, we recommend incorporating SHAP stability analysis into model validation procedures and avoiding the use of unstable features in regulatory or customer-facing explanations. We believe these recommendations can help enhance the reliability and accountability of explainable machine learning framework in credit risk management.
Journal Article
The Impact of Corruption on SMEs’ Trade Credit Management Effectiveness
The continued rise in SMEs’ corruption-related activities results in uncertainty around their ability to sustainably contribute to economic growth, leaving SMEs financially fragile and exposed to problems associated with trade credit management resulting in business exits. Given that little research has been conducted on how corruption affects smaller businesses while corruption’s impact on SMEs’ trade credit management effectiveness remains largely unexamined, the study aims to determine the impact of corruption on SMEs’ trade credit management effectiveness. By addressing this unanswered research gap, SMEs could be better equipped to understand how corruption affects their trade credit management in support of their overall finances. The study employed a quantitative research design with purposive sampling using a survey by administrating 10450 online questionnaires tested by a sample of 450 SMEs across South Africa. The result aligns with expectations around corruption being detrimental to SMEs’ trade credit management effectiveness while also indicating, unexpectedly, SMEs’ willingness to partake in corruption, given that SMEs benefit from increased effectiveness in managing trade credit. The study adds to the existing literature on corruption and SMEs’ trade credit management while also providing anti-corruption recommendations to SMEs that are dependent on trade credit. In so doing, SMEs could be better equipped to understand how corruption affects their trade credit management to support their overall finances contributing to improved SME creation rates and fostering entrepreneurship as a pivotal mechanism for improving South Africa’s sustainable development goals.
Journal Article
Improving Financial Sustainability Through Effective Credit Risk Management and Human Talent Development in Microfinance Institutions
This paper explores how credit risk management and human capital development sustain financial stability in microfinance institutions. Both qualitative and quantitative research methods allow this study to investigate credit risk management strategies while examining policies for inclusivity plus incentive plans along with debt portfolio selection efficiency. This research emphasizes that financial operations depend on skilled employees who require motivating interventions alongside training programs while developing ethical practices. The research discovers that organizations with strong credit risk management frameworks along with dedicated personnel achieve enhanced financial performances and reduced default incidents. This study confirms that microfinance institutions need both superior risk management along with human resource development systems to achieve sustainable development. This study enriches economic development research by demonstrating that implementing an equal mixture of financial and human resources produces successful economic results.
Journal Article