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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 : 2019-02-08
ISBN : 012814940X
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

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

Credit Risk Analytics

Credit Risk Analytics Book
Author : Bart Baesens,Daniel Roesch,Harald Scheule
Publisher : John Wiley & Sons
Release : 2016-10-03
ISBN : 1119143985
Language : En, Es, Fr & De

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Book Description :

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.

Credit Risk Modeling using Excel and VBA

Credit Risk Modeling using Excel and VBA Book
Author : Gunter Löeffler,Peter N. Posch
Publisher : John Wiley & Sons
Release : 2007-04-30
ISBN : 0470510749
Language : En, Es, Fr & De

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Book Description :

In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.

Rating Based Modeling of Credit Risk

Rating Based Modeling of Credit Risk Book
Author : Stefan Trueck,Svetlozar T. Rachev
Publisher : Academic Press
Release : 2009-01-15
ISBN : 9780080920306
Language : En, Es, Fr & De

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Book Description :

In the last decade rating-based models have become very popular in credit risk management. These systems use the rating of a company as the decisive variable to evaluate the default risk of a bond or loan. The popularity is due to the straightforwardness of the approach, and to the upcoming new capital accord (Basel II), which allows banks to base their capital requirements on internal as well as external rating systems. Because of this, sophisticated credit risk models are being developed or demanded by banks to assess the risk of their credit portfolio better by recognizing the different underlying sources of risk. As a consequence, not only default probabilities for certain rating categories but also the probabilities of moving from one rating state to another are important issues in such models for risk management and pricing. It is widely accepted that rating migrations and default probabilities show significant variations through time due to macroeconomics conditions or the business cycle. These changes in migration behavior may have a substantial impact on the value-at-risk (VAR) of a credit portfolio or the prices of credit derivatives such as collateralized debt obligations (D+CDOs). In Rating Based Modeling of Credit Risk the authors develop a much more sophisticated analysis of migration behavior. Their contribution of more sophisticated techniques to measure and forecast changes in migration behavior as well as determining adequate estimators for transition matrices is a major contribution to rating based credit modeling. Internal ratings-based systems are widely used in banks to calculate their value-at-risk (VAR) in order to determine their capital requirements for loan and bond portfolios under Basel II One aspect of these ratings systems is credit migrations, addressed in a systematic and comprehensive way for the first time in this book The book is based on in-depth work by Trueck and Rachev

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.

Deep Credit Risk

Deep Credit Risk Book
Author : Harald Scheule,Daniel Rösch
Publisher : Unknown
Release : 2020-06-24
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Deep Credit Risk - Machine Learning in Python aims at starters and pros alike to enable you to: - 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 Shortfall- Run over 1,500 lines of pandas, statsmodels and scikit-learn Python code- Access real credit data and much more ...

Credit Risk Modelling

Credit Risk Modelling Book
Author : David Jamieson Bolder
Publisher : Springer
Release : 2018-10-31
ISBN : 3319946889
Language : En, Es, Fr & De

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Book Description :

The risk of counterparty default in banking, insurance, institutional, and pension-fund portfolios is an area of ongoing and increasing importance for finance practitioners. It is, unfortunately, a topic with a high degree of technical complexity. Addressing this challenge, this book provides a comprehensive and attainable mathematical and statistical discussion of a broad range of existing default-risk models. Model description and derivation, however, is only part of the story. Through use of exhaustive practical examples and extensive code illustrations in the Python programming language, this work also explicitly shows the reader how these models are implemented. Bringing these complex approaches to life by combining the technical details with actual real-life Python code reduces the burden of model complexity and enhances accessibility to this decidedly specialized field of study. The entire work is also liberally supplemented with model-diagnostic, calibration, and parameter-estimation techniques to assist the quantitative analyst in day-to-day implementation as well as in mitigating model risk. Written by an active and experienced practitioner, it is an invaluable learning resource and reference text for financial-risk practitioners and an excellent source for advanced undergraduate and graduate students seeking to acquire knowledge of the key elements of this discipline.

Stress Testing and Risk Integration in Banks

Stress Testing and Risk Integration in Banks Book
Author : Tiziano Bellini
Publisher : Academic Press
Release : 2016-11-26
ISBN : 0128036117
Language : En, Es, Fr & De

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Book Description :

Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the stress testing process. An introduction to multivariate time series modeling paves the way to scenario analysis in order to assess a bank resilience against adverse macroeconomic conditions. Assets and liabilities are jointly studied to highlight the key issues that a risk manager needs to face. A multi-national bank prototype is used all over the book for diving into market, credit, and operational stress testing. Interest rate, liquidity and other major risks are also studied together with the former to outline how to implement a fully integrated risk management toolkit. Examples, business cases, and exercises worked in Matlab and R facilitate readers to develop their own models and methodologies. Provides a rigorous statistical framework for modeling stress test in line with U.S. Federal Reserve FRB CCAR (Comprehensive Capital Analysis Review), U.K. PRA (Prudential Regulatory Authority), EBA (European Baning Authorithy) and comply with Basel Accord requirements Follows an integrated bottom-up approach central in the most advanced risk modelling practice Provides numerous sample codes in Matlab and R

Credit Intelligence Modelling

Credit Intelligence   Modelling Book
Author : Raymond A. Anderson
Publisher : Oxford University Press
Release : 2022
ISBN : 0192844199
Language : En, Es, Fr & De

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Book Description :

Credit Intelligence and Modelling provides an indispensable explanation of the statistical models and methods used when assessing credit risk and automating decisions. Over eight modules, the book covers consumer and business lending in both the developed and developing worlds, providing the frameworks for both theory and practice. It first explores an introduction to credit risk assessment and predictive modelling, micro-histories of credit and credit scoring, as well as the processes used throughout the credit risk management cycle. Mathematical and statistical tools used to develop and assess predictive models are then considered, in addition to project management and data assembly, data preparation from sampling to reject inference, and finally model training through to implementation. Although the focus is credit risk, especially in the retail consumer and small-business segments, many concepts are common across disciplines, whether for academic research or practical use. The book assumes little prior knowledge, thus making it an indispensable desktop reference for students and practitioners alike. Credit Intelligence and Modelling expands on the success of The Credit Scoring Toolkit to cover credit rating and intelligence agencies, and the data and tools used as part of the process.

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.

Developing Credit Risk Models Using SAS Enterprise Miner and SAS STAT

Developing Credit Risk Models Using SAS Enterprise Miner and SAS STAT Book
Author : Iain Brown
Publisher : Unknown
Release : 2019-07-03
ISBN : 9781642953152
Language : En, Es, Fr & De

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Book Description :

Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications combines both theoretical explanation and practical applications to define as well as demonstrate how you can build credit risk models using SAS Enterprise Miner and SAS/STAT and apply them into practice. The ultimate goal of credit risk is to reduce losses through better and more reliable credit decisions that can be developed and deployed quickly. In this example-driven book, Dr. Brown breaks down the required modeling steps and details how this would be achieved through the implementation of SAS Enterprise Miner and SAS/STAT. Users will solve real-world risk problems as well as comprehensively walk through model development while addressing key concepts in credit risk modeling. The book is aimed at credit risk analysts in retail banking, but its applications apply to risk modeling outside of the retail banking sphere. Those who would benefit from this book include credit risk analysts and managers alike, as well as analysts working in fraud, Basel compliancy, and marketing analytics. It is targeted for intermediate users with a specific business focus and some programming background is required. Efficient and effective management of the entire credit risk model lifecycle process enables you to make better credit decisions. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications demonstrates how practitioners can more accurately develop credit risk models as well as implement them in a timely fashion.

Accounting for Derivatives

Accounting for Derivatives Book
Author : Juan Ramirez
Publisher : John Wiley & Sons
Release : 2015-01-23
ISBN : 111881794X
Language : En, Es, Fr & De

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Book Description :

The derivative practitioner’s expert guide to IFRS 9 application Accounting for Derivatives explains the likely accounting implications of a proposed transaction on derivatives strategy, in alignment with the IFRS 9 standards. Written by a Big Four advisor, this book shares the author’s insights from working with companies to minimise the earnings volatility impact of hedging with derivatives. This second edition includes new chapters on hedging inflation risk and stock options, with new cases on special hedging situations including hedging components of commodity risk. This new edition also covers the accounting treatment of special derivatives situations, such as raising financing through commodity-linked loans, derivatives on own shares and convertible bonds. Cases are used extensively throughout the book, simulating a specific hedging strategy from its inception to maturity following a common pattern. Coverage includes instruments such as forwards, swaps, cross-currency swaps, and combinations of standard options, plus more complex derivatives like knock-in forwards, KIKO forwards, range accruals, and swaps in arrears. Under IFRS, derivatives that do not qualify for hedge accounting may significantly increase earnings volatility. Compliant application of hedge accounting requires expertise across both the standards and markets, with an appropriate balance between derivatives expertise and accounting knowledge. This book helps bridge the divide, providing comprehensive IFRS coverage from a practical perspective. Become familiar with the most common hedging instruments from an IFRS 9 perspective Examine FX risk and hedging of dividends, earnings, and net assets of foreign subsidies Learn new standards surrounding the hedge of commodities, equity, inflation, and foreign and domestic liabilities Challenge the qualification for hedge accounting as the ultimate objective IFRS 9 is set to replace IAS 39, and many practitioners will need to adjust their accounting policies and hedging strategies to conform to the new standard. Accounting for Derivatives is the only book to cover IFRS 9 specifically for the derivatives practitioner, with expert guidance and practical advice.

Introduction to Credit Risk Modeling

Introduction to Credit Risk Modeling Book
Author : Christian Bluhm,Ludger Overbeck,Christoph Wagner
Publisher : CRC Press
Release : 2016-04-19
ISBN : 1584889934
Language : En, Es, Fr & De

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Book Description :

Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modelin

International Convergence of Capital Measurement and Capital Standards

International Convergence of Capital Measurement and Capital Standards Book
Author : Anonim
Publisher : Lulu.com
Release : 2004
ISBN : 9291316695
Language : En, Es, Fr & De

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Book Description :

Download International Convergence of Capital Measurement and Capital Standards book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Financial Risk Management

Financial Risk Management Book
Author : Jimmy Skoglund,Wei Chen
Publisher : John Wiley & Sons
Release : 2015-09-04
ISBN : 1119157234
Language : En, Es, Fr & De

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Book Description :

A global banking risk management guide geared toward the practitioner Financial Risk Management presents an in-depth look at banking risk on a global scale, including comprehensive examination of the U.S. Comprehensive Capital Analysis and Review, and the European Banking Authority stress tests. Written by the leaders of global banking risk products and management at SAS, this book provides the most up-to-date information and expert insight into real risk management. The discussion begins with an overview of methods for computing and managing a variety of risk, then moves into a review of the economic foundation of modern risk management and the growing importance of model risk management. Market risk, portfolio credit risk, counterparty credit risk, liquidity risk, profitability analysis, stress testing, and others are dissected and examined, arming you with the strategies you need to construct a robust risk management system. The book takes readers through a journey from basic market risk analysis to major recent advances in all financial risk disciplines seen in the banking industry. The quantitative methodologies are developed with ample business case discussions and examples illustrating how they are used in practice. Chapters devoted to firmwide risk and stress testing cross reference the different methodologies developed for the specific risk areas and explain how they work together at firmwide level. Since risk regulations have driven a lot of the recent practices, the book also relates to the current global regulations in the financial risk areas. Risk management is one of the fastest growing segments of the banking industry, fueled by banks' fundamental intermediary role in the global economy and the industry's profit-driven increase in risk-seeking behavior. This book is the product of the authors' experience in developing and implementing risk analytics in banks around the globe, giving you a comprehensive, quantitative-oriented risk management guide specifically for the practitioner. Compute and manage market, credit, asset, and liability risk Perform macroeconomic stress testing and act on the results Get up to date on regulatory practices and model risk management Examine the structure and construction of financial risk systems Delve into funds transfer pricing, profitability analysis, and more Quantitative capability is increasing with lightning speed, both methodologically and technologically. Risk professionals must keep pace with the changes, and exploit every tool at their disposal. Financial Risk Management is the practitioner's guide to anticipating, mitigating, and preventing risk in the modern banking industry.

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.

Effects of Bank Capital on Lending

Effects of Bank Capital on Lending Book
Author : Joseph M. Berrospide
Publisher : DIANE Publishing
Release : 2011-04
ISBN : 1437939864
Language : En, Es, Fr & De

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Book Description :

The effect of bank capital on lending is a critical determinant of the linkage between financial conditions and real activity, and has received especial attention in the recent financial crisis. The authors use panel-regression techniques to study the lending of large bank holding companies (BHCs) and find small effects of capital on lending. They then consider the effect of capital ratios on lending using a variant of Lown and Morgan's VAR model, and again find modest effects of bank capital ratio changes on lending. The authors¿ estimated models are then used to understand recent developments in bank lending and, in particular, to consider the role of TARP-related capital injections in affecting these developments. Illus. A print on demand pub.

Credit Risk Modeling using Excel and VBA

Credit Risk Modeling using Excel and VBA Book
Author : Gunter Löeffler,Peter N. Posch
Publisher : Wiley
Release : 2007-06-05
ISBN : 9780470031575
Language : En, Es, Fr & De

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Book Description :

In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.

Model Risk Management with SAS

Model Risk Management with SAS Book
Author : SAS
Publisher : SAS Institute
Release : 2020-06-29
ISBN : 1970170654
Language : En, Es, Fr & De

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Book Description :

Cut through the complexity of model risk management with a guide to solutions from SAS! There is an increasing demand for more model governance and model risk awareness. At the same time, high-performing models are expected to be deployed faster than ever. SAS Model Risk Management is a user-friendly, web-based application that facilitates the capture and life cycle management of statistical model-related information. It enables all stakeholders in the model life cycle — developers, validators, internal audit, and management – to get overview reports as well as detailed information in one central place. Model Risk Management with SAS introduces you to the features and capabilities of this software, including the entry, collection, transfer, storage, tracking, and reporting of models that are drawn from multiple lines of business across an organization. This book teaches key concepts, terminology, and base functionality that are integral to SAS Model Risk Management through hands-on examples and demonstrations. With this guide to SAS Model Risk Management, your organization can be confident it is making fact-based decisions and mitigating model risk.