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2020 | Book

Credit Analysis and Credit Management Read chapter Read first chapter

The Practice of Lending

A Guide to Credit Analysis and Credit Risk

Authors: Terence M. Yhip, Bijan M. D. Alagheband

Publisher: Springer International Publishing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Wirtschaft"

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About this book

This book provides a comprehensive treatment of credit risk assessment and credit risk rating that meets the Advanced Internal Risk-Based (AIRB) approach of Basel II. Credit risk analysis looks at many risks and this book covers all the critical areas that credit professionals need to know, including country analysis, industry analysis, financial analysis, business analysis, and management analysis. Organized under two methodological approaches to credit analysis—a criteria-based approach, which is a hybrid of expert judgement and purely mathematical methodologies, and a mathematical approach using regression analysis to model default probability—the book covers a cross-section of industries including passenger airline, commercial real estate, and commercial banking. In three parts, the sections focus on hybrid models, statistical models, and credit management. While the book provides theory and principles, its emphasis is on practical applications, and will appeal to credit practitioners in the banking and investment community alongside college and university students who are preparing for a career in lending.

Table of Contents

Frontmatter

The Criteria-Based Approach to Credit Assessment and Credit Rating

Frontmatter
1. Credit Analysis and Credit Management
Abstract
This introductory chapter outlines the processes of originating credit and managing credit. Credit origination involves loan underwriting, assessing the creditworthiness of a borrower, determining a borrower risk rating (BRR), and structuring the loan. Credit administration involves monitoring credit quality, covenants, and loan documentation, and taking actions to avoid loan loss. The chapter introduces the two-dimensional risk-rating system that separates the BRR from the facility risk rating, though they jointly determine the expected loss on a loan. The chapter reviews the traditional “Five Cs” method of credit analysis and its derivative, the criteria-based methodology to assign a BRR. Because a credit rating is essential to lending, loan pricing, and capitalisation, the chapter highlights the adverse effects on risk rating due to information asymmetry.
Terence M. Yhip, Bijan M. D. Alagheband
2. Financial Statement Analysis
Abstract
This chapter provides fundamental financial analysis based on ratio analysis, a powerful tool to assess the performance of a firm over a period, or to compare risk and return of firms of different sizes. The discussion centres on the income statement, the balance sheet, the statement of shareholders’ equity, and the cash flow statement and the capitalisation of off-balance obligations. These provide the credit analyst with information to calculate the ratios, which are usually grouped into four categories: profitability, asset utilisation and efficiency, liquidity, and debt and solvency. The ratio examples are based on actual financial reports. Calculated accurately and analysed carefully, financial ratios are revealing and predictive. But financial statements can also mislead with window dressing and fraudulent reporting. The chapter provides examples.
Terence M. Yhip, Bijan M. D. Alagheband
3. The Criteria-Based Approach to Credit Risk Assessment and Credit Risk Rating
Abstract
This chapter gives a general description of the framework of a risk-rating system that meets the requirements of the AIRB approach. The structure consists of a standard risk-rating scale that maps risk grades against probability of default. Consistent with the risk-rating scale, the criteria-based model, as represented by a borrower risk rating (BRR) scorecard, calculates a composite score and assigns a corresponding BRR based on the risk criteria, risk factors, risk elements, and descriptors appropriate to the industry under review. Thus in principle there can be as many BRR scorecards as there are industries in a loan portfolio. An important feature of the criteria-based approach is its override functionality. The chapter explores a method to capture information asymmetry or fraudulent financial reporting in the BRR.
Terence M. Yhip, Bijan M. D. Alagheband
4. The Building Blocks of Credit Analysis and Credit Risk Rating
Abstract
This chapter fleshes out the borrower risk rating (BRR) components, and demonstrates the calculation of component and composite BRRs. A BRR scorecard would usually have four main building blocks: Industry Risk, Business Risk, Management Risk, and Financial Risk. Each block is usually defined by a set of Risk Factors and a set of Risk Elements, all weighted. The chapter discusses methods to dampen point-in-cycle effects on the BRR and the conditions that require the use of projected financial statements instead of current for more accurate BRR determination. The chapter provides a framework for creating descriptors/characteristics (for a given risk factor/risk element) to differentiate between risk ratings effectively and consistently. The monotonicity between descriptor and BRR is a necessary condition of a predictive risk-rating system.
Terence M. Yhip, Bijan M. D. Alagheband
5. How It All Fits
Abstract
This chapter unites the abstract discussion on principles and techniques of the criteria-based approach in a case study using the financial statements of a fictional airline company named AY Intercontinental Airways. Through the case study the reader applies, in one go, the background knowledge to construct a borrower risk rating (BRR) scorecard with the necessary building blocks, create descriptors, apply point-in-cycle adjustment, prepare pro forma financial statements, construct a cash flow model for stress testing “what if” scenarios, apply overrides, and determine the final risk rating. Comparing the BRR based on current financials to the BRRs, the PIT adjustments temper the risk rating as expected. The risk assessor may execute the adjustments in Business Risk, or alternatively in Financial Risk using projected financials.
Terence M. Yhip, Bijan M. D. Alagheband
6. Credit Risk Analysis and Credit Risk Rating of Commercial Real Estate
Abstract
This chapter applies the criteria-based risk-rating methodology to a stabilised income producing real estate (IPRE) asset. In rating a commercial real estate entity, the assessment is not on the property owner but on the IPRE, and the building blocks of the borrower risk rating (BRR) scorecard reflect this key difference. The BRR scorecard consists of just Business Risk (defined by tenant quality, lease maturity, and condition) and Financial Risk (defined by debt service coverage and loan-to-value ratio). The chapter explains how to set up a spreadsheet to forecast net operating income and the balance sheet, and offers a framework to create the descriptors, which drive the BRR. The chapter explains valuation methods and the capitalisation rate, and shows the sensitivity of property valuations to various assumptions.
Terence M. Yhip, Bijan M. D. Alagheband
7. Bank Credit Risk Analysis and Bank Credit Rating
Abstract
This chapter applies the criteria-based approach to the banking industry. Commercial banks are different from other enterprises in their core activities and thus the variables that determine bank failure are different. A commercial bank earns the bulk of its income from long-term loans funded by shorter-term retail deposits and wholesale borrowings—a process called maturity transformation. The chapter provides the conceptual framework to analyse a bank’s financial statements and to narrow the focus to the business environment, quality of management (including risk management) and governance, and financial strength. This last includes a comprehensive and thorough examination of asset quality, and the adequacy and quality of liquidity and capital. The chapter explains important metrics such as Basel III capital ratios, economic capital, and Value at Risk.
Terence M. Yhip, Bijan M. D. Alagheband

Statistical Methods on Credit Scoring

Frontmatter
8. Statistical Methods of Credit Risk Analysis
Abstract
This chapter represents a big leap from expert-judgement modelling to purely quantitative/statistical modelling. The two approaches are vital and complementary tools in a bank’s risk assessment toolbox. The chapter examines the structure of the linear probability model and probit and logit analysis, shows the similarity and differences, and applies the methods to a sample of companies. It also provides step-by-step guidance to formulate a logit model, and explains how to perform a logit regression using actual data and interpret the logit regression results. As with all models, including expert-judgement models, the stability or reliability of the estimated parameters, descriptors, and weights is not a constant, which makes model validation necessary and essential. Poor validation can be costly to a lender.
Terence M. Yhip, Bijan M. D. Alagheband
9. Statistical Methods of Predicting Country Debt Crisis
Abstract
This chapter discusses discriminant analysis, a statistical method for handling classification problem, and applies the analysis to predict sovereign debt crisis by differentiating two groups, “Default” and “Non-default”, based on certain quantitative and qualitative country characteristics. The model is tested on a new country to determine which of the two groups it belongs, and the model correctly predicts default. With the same characteristics for the discriminant function, the logit function, which measures the odds of default in relation to such characteristics, is also estimated. For classification purposes, discriminant analysis uses normal distribution, whereas the logit model assumes a distribution with fatter tails compared to normal distribution, thus making logit analysis more relevant in the presence of abnormal and extreme values in the population.
Terence M. Yhip, Bijan M. D. Alagheband

Credit Management

Frontmatter
10. Credit Monitoring and Compliance
Abstract
This chapter shifts the spotlight away from credit origination to credit management, which essentially ensures that a borrower stays in compliance with the loan agreement and that any signs of credit quality deterioration are handled promptly. The chapter outlines the reasons for credit monitoring and discusses best practices that well-managed banks have in place, such as monitoring loan covenants, loan documentation and collateral, reviewing the borrower risk rating and credit exposures, and implementing a watch list process to flag deteriorating accounts. The chapter discusses the requirements of an effective monitoring system (e.g., enterprise-wide centralised data, accuracy, and timeliness) and the benefits from automating the process, one of which is detecting deteriorating credit trends for individual borrowers and for a loan portfolio.
Terence M. Yhip, Bijan M. D. Alagheband
11. Problem Loan ManagementProblem Loan Management
Abstract
This chapter concludes the book with an examination of problem loans, something that is unavoidable in lending and therefore has to be properly managed. The chapter starts with an examination of the costs that a lender faces because of problem loans. The biggest costs are lost principal, lost interest income, and the administrative expenses such as a specialised group and the resources to manage and recover the problem loans. The chapter discusses the reporting structure banks have in place to manage problem loans and the strategies to recover losses (e.g., remarketing the loan, rehabilitation, and liquidation). Also discussed is troubled debt restructuring, the pros and cons of the loan-recovery strategies, debt write-off, loan loss provisioning, and the time-value of money.
Terence M. Yhip, Bijan M. D. Alagheband
Backmatter
Metadata
Title
The Practice of Lending
Authors
Terence M. Yhip
Bijan M. D. Alagheband
Copyright Year
2020
Publisher
Springer International Publishing
Electronic ISBN
978-3-030-32197-0
Print ISBN
978-3-030-32196-3
DOI
https://doi.org/10.1007/978-3-030-32197-0