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Ifrs 9 And Cecl Credit Risk Modelling And Validation

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IFRS 9 and CECL Credit Risk Modelling and Validation

IFRS 9 and CECL Credit Risk Modelling and Validation Book
Author : Tiziano Bellini
Publisher : Academic Press
Release : 2019-01-15
ISBN : 0128149418
Language : En, Es, Fr & De

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Book Description :

IFRS 9 and CECL Credit Risk Modelling and Validation covers a hot topic in risk management. Both IFRS 9 and CECL accounting standards require Banks to adopt a new perspective in assessing Expected Credit Losses. The book explores a wide range of models and corresponding validation procedures. The most traditional regression analyses pave the way to more innovative methods like machine learning, survival analysis, and competing risk modelling. Special attention is then devoted to scarce data and low default portfolios. A practical approach inspires the learning journey. In each section the theoretical dissertation is accompanied by Examples and Case Studies worked in R and SAS, the most widely used software packages used by practitioners in Credit Risk Management. Offers a broad survey that explains which models work best for mortgage, small business, cards, commercial real estate, commercial loans and other credit products Concentrates on specific aspects of the modelling process by focusing on lifetime estimates Provides an hands-on approach to enable readers to perform model development, validation and audit of credit risk models

Reverse Stress Testing in Banking

Reverse Stress Testing in Banking Book
Author : Michael Eichhorn,Tiziano Bellini,Daniel Mayenberger
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2021-05-10
ISBN : 3110647907
Language : En, Es, Fr & De

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Book Description :

Reverse stress testing was introduced in risk management as a regulatory tool for financial institutions more than a decade ago. The recent Covid-19 crisis illustrates its relevance and highlights the need for a systematic re-thinking of tail risks in the banking sector. This book addresses the need for practical guidance describing the entire reverse stress testing process. Reverse Stress Testing in Banking features contributions from a diverse range of established practitioners and academics. Organized in six parts, the book presents a series of contributions providing an in-depth understanding of: Regulatory requirements and ways to address them Quantitative and qualitative approaches to apply reverse stress testing at different levels – from investment portfolios and individual banks to the entire banking system The use of artificial intelligence, machine learning and quantum computing to gain insights into and address banks’ structural weaknesses Opportunities to co-integrate reverse stress testing with recovery and resolution planning Governance and processes for board members and C-suite executives Readers will benefit from the case studies, use cases from practitioners, discussion questions, recommendations and innovative practices provided in this insightful and pioneering book.

Deep Credit Risk Chinese

Deep Credit Risk  Chinese  Book
Author : Harald Scheule,Daniel Rösch
Publisher : Deep Credit Risk
Release : 2021-07-22
ISBN : 9780645245202
Language : En, Es, Fr & De

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Book Description :

- 了解流动性,房屋净值和许多其他关键银行业特征变量的作用; - 选择并处理变量; - 预测违约、偿付、损失率和风险敞口; - 利用危机前特征预测经济衰退和危机后果; - 理解COVID-19对信用风险带来的影响; - 将创新的抽样技术应用于模型训练和验证; - 从Logit分类器到随机森林和神经网络的深入学习; - 进行无监督聚类、主成分和贝叶斯技术的应用; - 为CECL、IFRS 9和CCAR建立多周期模型; - 建立用于在险价值和期望损失的信贷组合相关模型; - 使用更多真实的信用风险数据并运行超过1500行的代码... - Understand the role of liquidity, equity and many other key banking features - Engineer and select features - Predict defaults, payoffs, loss rates and exposures - Predict downturn and crisis outcomes using pre-crisis features - Understand the implications of COVID-19 - Apply innovative sampling techniques for model training and validation - Deep-learn from Logit Classifiers to Random Forests and Neural Networks - Do unsupervised Clustering, Principal Components and Bayesian Techniques - Build multi-period models for CECL, IFRS 9 and CCAR - Build credit portfolio correlation models for VaR and Expected Shortfal - Run over 1,500 lines of pandas, statsmodels and scikit-learn Python code - Access real credit data and much more ...

Intelligent Credit Scoring

Intelligent Credit Scoring Book
Author : Naeem Siddiqi
Publisher : John Wiley & Sons
Release : 2017-01-10
ISBN : 1119279151
Language : En, Es, Fr & De

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Book Description :

A better development and implementation framework for credit risk scorecards Intelligent Credit Scoring presents a business-oriented process for the development and implementation of risk prediction scorecards. The credit scorecard is a powerful tool for measuring the risk of individual borrowers, gauging overall risk exposure and developing analytically driven, risk-adjusted strategies for existing customers. In the past 10 years, hundreds of banks worldwide have brought the process of developing credit scoring models in-house, while ‘credit scores' have become a frequent topic of conversation in many countries where bureau scores are used broadly. In the United States, the ‘FICO' and ‘Vantage' scores continue to be discussed by borrowers hoping to get a better deal from the banks. While knowledge of the statistical processes around building credit scorecards is common, the business context and intelligence that allows you to build better, more robust, and ultimately more intelligent, scorecards is not. As the follow-up to Credit Risk Scorecards, this updated second edition includes new detailed examples, new real-world stories, new diagrams, deeper discussion on topics including WOE curves, the latest trends that expand scorecard functionality and new in-depth analyses in every chapter. Expanded coverage includes new chapters on defining infrastructure for in-house credit scoring, validation, governance, and Big Data. Black box scorecard development by isolated teams has resulted in statistically valid, but operationally unacceptable models at times. This book shows you how various personas in a financial institution can work together to create more intelligent scorecards, to avoid disasters, and facilitate better decision making. Key items discussed include: Following a clear step by step framework for development, implementation, and beyond Lots of real life tips and hints on how to detect and fix data issues How to realise bigger ROI from credit scoring using internal resources Explore new trends and advances to get more out of the scorecard Credit scoring is now a very common tool used by banks, Telcos, and others around the world for loan origination, decisioning, credit limit management, collections management, cross selling, and many other decisions. Intelligent Credit Scoring helps you organise resources, streamline processes, and build more intelligent scorecards that will help achieve better results.

Expected Credit Loss Modeling from a Top Down Stress Testing Perspective

Expected Credit Loss Modeling from a Top Down Stress Testing Perspective Book
Author : Mr.Marco Gross,Dimitrios Laliotis,Mindaugas Leika,Pavel Lukyantsau
Publisher : International Monetary Fund
Release : 2020-07-03
ISBN : 1513549081
Language : En, Es, Fr & De

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Book Description :

The objective of this paper is to present an integrated tool suite for IFRS 9- and CECL-compatible estimation in top-down solvency stress tests. The tool suite serves as an illustration for institutions wishing to include accounting-based approaches for credit risk modeling in top-down stress tests.