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For over twenty years. W. S. Foster Associates has provided quality in-house training programs to a wide variety of U.S. and international institutions. The courses are for entry level as well as experienced investment bankers and financial professionals. W. S. Foster Associates' role as seminar leader has greatly enhanced the judgment and analytical skills of participants from hanks, investment hanks and rating agencies. Clients include:

Standard & Poor \s
Fannie Mae
National Australia Bank
Credit Suisse First Boston
Federal Reserve Bank of NY
Merrill Lynch
Bank of England

Jack Foster, primary instructor of W. S. Foster Associates, has unique qualifications to design and lead credit seminars. Over the past 20 years, he has conducted over 200 week long Corporate and Bank Credit Rating Seminars in over 15 countries including Saudi Arabia, Egypt, I long Kong, China, South Korea, Japan, Singapore, Indonesia, Australia, Mexico, Sweden, Switzerland, Germany, England, France, and the U.S. He started and was Chairman of the Rating Committee at JP Morgan for five years and served at JP Morgan for 20 years (1974-1994). He was the primary instructor for Standard and Poor’s internal and external Bank and Corporate Credit analysis Seminars for eight years (1995-2003). He is a graduate of Williams College and the Harvard Business School.

Book Description (Synopsis)

Describes current approach to credit analysis for Rating Agencies, Regulators, Banks and Derivative Risk Managers. Book based on my experience as Chairman of the Rating Committee at JPMorgan for five years and as primary internal and external instructor for Standard and Poor’s credit analysts and clients.

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Back Cover Description

Describes current approach to credit analysis for Rating Agencies, Regulators, Banks and Derivative Risk Managers. Book based on my experience as Chairman of the Rating Committee at JPMorgan for five years and as primary internal and external instructor for Standard and Poor’s credit analysts and clients.

Author's Book Dedication

To all who trained and supported me through the years.

Story Keywords

credit, analysis, finance,

Estimated Word Count

35000

Book Completion Date
Acknowledgements
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Team Member Editor
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W. S. Foster Associates (WSF) takes a different approach to credit training than is usually employed.

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Chapter 1:
Introduction
My name is Jack Foster. For five years, I was Chairman of the Credit Rating Committee at JP Morgan and was responsible for supervising all credit training. For seven years after JP Morgan, as a financial advisor, I was the primary instructor for credit analysis for Standard and Poor’s (S&P). During that period, I taught over 100 week-long internal and external credit analysis courses for future S&P analysts and clients.
My approach to credit analysis and credit ratings is, therefore, based on these experiences and the examples I use are from my experience at JP Morgan and S&P.
A term often used today to describe institutional risk is “enterprise risk”. Some analysts use enterprise risk because our increasingly complex financial world has increased the importance of other risk factors such as legal, operational, market and country risk. I have retained the term ’’credit risk” because I believe it better captures the fundamental importance of ethics in banking in particular and capitalism in general. I discuss this further in Chapter 7, Conclusion.
Development of Credit Analysis Skills:
We develop credit analysis skills in four stages. We can remember the four stages from the acronym DEEP - D for the Descriptive Stage, E for the Explanatory Stage, E for the Evaluative Stage and P for the Prescriptive Stage.
Descriptive Stage: The descriptive stage is about clarifying facts such as Company A is in the XYZ industry, its sales were $500 million and its net income was $50 million, etc.
Explanatory Stage: The explanatory stage provides reasons for the facts. Sales increased by 10% but only 7% was due to volume increases, the other 3% was due to price increases. Net income declined $5 million due to an extraordinary litigation charge. Debt declined $5 million due to a reduction in cash, etc.
Evaluative Stage: The evaluative stage integrates facts to clarify the most important factors that determine the credit rating. Debt to Earnings before Interest, Taxes,

Depreciation and Amortization (Debt to EBITDA ratio) decreased to 200%. Operating margins and net margins continued to increase at the same time sales and market share increased. The Company is planning large debt financed capital expenditures that we expect to increase Debt to EBITDA in the future, etc.
Prescriptive Stage: The prescriptive sage clarifies opportunities for extending credit or purchasing bonds. The plans for increased capital expenditures requires debt financing that we can help underwrite. We can help structure the financing so that the Company can maintain its credit rating. The bond offers an attractive yield for a BBB credit that has a positive outlook, etc.
While this book includes descriptive, explanatory and prescriptive aspects of credit analysis, it will primarily focus on the evaluative aspects. It will focus on how to evaluate the most important strengths and weakness of any company loan or bond.
Credit is the fuel of capitalism and is essential to a growing economy. Credit is the process of taking money from savers (who do not know how to invest) and lending it to financial intermediaries and borrowers who can invest the money in a way that contributes to economic growth.
The objective of this book is to clarify this process in its most simple terms. Therefore, the book will focus on the key factors, not the details of credit analysis. It will focus on the three to five-year evaluation of bond and loan credit risk, not short-term credit risk or market risk.
The most important aspects of credit analysis is objectivity and integrity - a methodical and honest evaluation of the facts. This may seem obvious but the experiences of the recession of 2008/2009 demonstrates that it is easy for many bankers, investment bankers and borrowers to put their short-term economic benefits ahead of long-term interests of their clients and their long-term ability to repay debt. (See Chapter 7, Conclusion.)
The aim will be to demonstrate how economics and politics, capitalism and democracy, competence and fairness, ethics and morality and our political party system affect credit analysis. In other words, the aim will be to demonstrate how credit analysis fits in as a part of the all the other factors in our life.
In credit analysis, we have three levels of certainty - facts we can know beyond all doubt, decisions we can make beyond a reasonable doubt and decisions we can make based upon the preponderance of evidence. For example, in legal analysis for civil cases, we only need to demonstrate our case by a preponderance of evidence. In legal analysis for criminal cases, we need to demonstrate our case beyond a reasonable doubt. In scientific proofs, we need to demonstrate our case beyond all doubt. In credit analysis some things we know beyond all doubt - for example accounting rules; some things we know beyond a reasonable doubt - for example financial statement analysis, and cash flow analysis; and finally some things we only know based upon the preponderance of evidence — for example credit analysis and credit understanding. Credit analysis is an art not a science, it comes up with probabilities for decision making under conditions of uncertainty.
The question is “How do we evaluate those conditions of uncertainty?” The generally accepted standard for evaluating individual credits is the methodology used by the rating agencies. The recession of 2008/2009, however, raised questions about this methodology.
Therefore, it is first necessary to review what went wrong with the rating agency methodology in 2008/2009 to identify its limitations. After clarifying these limitations, we can then use the rating agency methodology as the standard for evaluating credit from the perspective of an individual loan or security. We will then look at how the regulators look at evaluating credit risk in the banking system from the perspective of U.S taxpayers. Next, we will look at how banks evaluate their own credit risk across a portfolio of loans from the perspective of shareholders. Finally, we will look at how to evaluate derivative credit risk from the perspective of derivative traders and bank management.
The objective of this review is to integrate credit risk standards from different perspectives as a means of clarifying analytical techniques and increasing critical thinking.
The first way to evaluate credit risk is from the perspective of the probability of default. The second is from the probability of loss.
Risk of Default - PD or Probability of Default: Default is the failure of timely payment of principal and interest and we express the likelihood of that default in percentage terms. For example, the percent likelihood of default for a BBB credit over 1 year, 5 years, 10,years, etc.
Risk of Loss - LGD or Loss Given Default: Loss is the difference between the face value of a loan or security relative to principal and interest received discounted back to the date of default. For example, the percent likelihood of loss for a BB credit once a default has occurred.
The two perspectives result in two different types of ratings. The first type of rating is the issuer rating from the perspective of the probability of default. The second type or rating is the issue rating from the perspective of the probability of default and the expected loss given default.

Issuer Ratings - Default Risk Ratings of Corporates, Counterparties and Sovereigns: Rating agencies base issuer ratings on the capacity and willingness of borrowers to meet financial commitments on time.
Issue Rating — Loss Risk Ratings of specific financial obligations: Rating agencies base issue ratings on the default risk rating but also include an assessment of the ultimate recovery prospects after default due to seniority in the capital structure, guarantees, collateral, covenants etc.
Rating agency ratings also include two additional ratings - Outlook Ratings and Credit Watch Ratings.
Outlook Ratings: Rating Agencies assign Outlook Ratings to all long-term issuer ratings. They assess the potential long-term direction of the rating over a time horizon of up to 3 years. They are not necessarily a precursor to a rating change. The four types of outlook ratings are Positive, Negative, Stable and Developing.
Credit Watch Ratings: Rating Agencies assign Credit Watch Ratings selectively to long-term Issuer Ratings. They focus on the short-term direction of the company due to changes in fundamentals or significant events such as a large acquisition. The time horizon is usually 90 days or less while the Rating Agency is able to obtain the additional information necessary to complete the rating process. There are three types of Credit Watch Ratings - Positive, Negative and Developing.
The rating scale for both long-term Issuer and Issue ratings for S&P runs from AAA to D.
Rating Agency Short-Term Ratings: In addition to long-term Issuer and Issue ratings the rating agencies also rate short-term debt with a maturity of one-year or less such as commercial paper or certificates of deposit. The four categories of short-term ratings for S&P are A-1+, A-l, A-2, A-3 and B. A company’s short--term ratings is largely determined by its long-term rating. For example, a company with a long term S&P rating of AAA to A+ receives an A-l+ short term rating, A+ to A- an A-l short-term rating, an A+ to BBB an A-2 rating, a BBB to BBB- an A- 3 rating and a BB+ to BB- a B short term rating. Whenever there are overlaps, S&P gives the higher or lower rating depending upon the Company’s liquidity, i.e. its amount of cash, committed credit facilities etc. Rating Agency Ratings are relevant to banks and investors because they provide a short cut for less sophisticated investors to choose more or less credit risk and implicitly, more or less market volatility. Historically, higher quality investment grade companies rated BBB- or better have had substantially less frequent rating changes, market volatility and loss than lower quality non-investment grade credits rated BB+ or lower.
Rating Agency ratings are highly respected. Their ratings have historically been viewed as independent (the Rating Agencies are paid a fixed fee and have nothing to gain from whether their rating is higher or lower). There has been a close correlation between ratings and default and the Rating Agencies have been transparent about their rating criteria.
However, the recession of 2008/2009 revealed weaknesses in the methodology for rating mortgage backed structured finance transactions. Like almost everyone else, the rating agencies underestimated the cyclicality of real estate. In 2008, their historical ability to predict defaults of corporate obligors over the previous 30 years had been extremely accurate over any time-period. Over one-year the approximate average annual default rate for S&P was 0.0% for AAA rated credits, 0.2% for BBB rated credits and 26.4% for CCC rated credits. Over 5 years the average cumulative default rate for S&P was 0.4% for AAA rated credits, 2.0% for BBB rated credits and 46.3% for CCC rated credits. Even over 10 years the average cumulative default rate for S&P was approximately 0.7% for AAA rated credits, 4.0% for BBB rated credits and 50.7% for CCC rated credits.

S&P Corporate Default Risk by Rating*
Average Cumulative Default Rates 1981-2015 (%)
Year# AAA AA A BBB BB B CCC/C
1 0.00 0.02 0.07 0.20 0.76 3.88 26.38
2 0.03 0.07 0.16 0.57 2.35 8.80 35.58
3 0.14 0.13 0.27 0.98 4.23 12.97 40.67
4 0.24 0.24 0.41 1.46 6.06 16.22 43.77
5 0.36 0.35 0.57 1.95 7.71 18.70 46.28
10 0.74 0.82 1.51 4.06 13.74 25.91 50.73
15 0.98 1.19 2.32 5.84 16.77 29.49 53.38

*S&P Annual Corporate Default Study 2015, Table 24
In other words, if S&P rates a credit AAA, the one-year possibility of default should be should be less than one-in-a-thousand i.e. the financial markets expect the borrower to pay interest and principle on time 99.9% of the time, i.e. beyond all doubt. If S&P rates a credit BBB the one-year possibility of default should be about one-in-500 i.e. the financial markets expect the borrower to pay interest and principle on time 99.8% of the time i.e. within a reasonable doubt. If S&P rates a credit, C the one-year possibility of default should be about one-in-two i.e. the financial markets expect that the borrower will repay interest and principle on time 50% of the time i.e. there is an even chance that the borrower will repay interest and principle on time. In fact, in the previous 34 years there has been only one large “corporate” that has been rated investment grade i.e. BBB- or higher at the time of default and that was Lehman Brothers.

Largest Corporate Defaults*
(2001-2015, US$ Billions)
Amt. Year Rating**
Lehman Brothers Holdings Inc. $144 2008 A
• Ford Motor Company $ 71 2009 CC
General Motors Corporation $ 53 2009 CC
• GMAC LLC $ 46 2008 CC
• Energy Future Holdings $ 48 2010 CC
• WorldCom Inc. $ 34 2002 B
• Texas Competitive Electric Holds $ 32 2011 B-
• Lyondell Basell Industries (Dutch) $ 24 2008 B-
Harrah’s Entertainment Inc. $ 24 2008 CC
• Chrysler $ 23 2009 CC
* Includes Distressed Exchanges
** At time of default
It is not hard to see from this table what a shock it was to the financial markets for the Federal Reserve to allow Lehman Brothers to go into default. As a result of this event and other factors:

• The interbank market was frozen and the Fed had to replace that market with its discount window. (The discount window permits banks to provide investment grade loans as collateral and receive cash from the Federal Reserve in return.)
• The largest 19 banks had to accept equity infusions from the Troubled Asset Relief Program. (It was later estimated by a congressional committee that only one of those 19 banks (JP Morgan) would have survived without the Troubled Asset Relief Program).
• The commercial paper and money fund markets were frozen and, in effect, the Fed had to guarantee them.
• The Department of the Treasury and the Fed put Fannie Mae and Freddie Mac into conservatorship and began purchasing a large portion of their securities.

People began blaming other people for the crisis.

• “The problem was not a lack of regulation, but firms’ poor judgment.” Alan Greenspan, former Chairman of the Federal Reserve to the Financial Crisis Inquiry Commission. April 7, 2010.
• “The incessant broad based vilification of the banking industry isn’t fair and it is damaging. Punishing whole industries, whether you were reckless or not, just isn’t the way to do things.” James Dimon, Chairman and Chief Executive of J. P. Morgan Chase & Co. Wall Street Journal April 7, 2010.
• “Letter to shareholders increases from 4 pages in 2008 to 9 pages in 2009 justifying activities during crisis.” Lloyd Blanfein, Chief Executive Officer, Goldman Sachs.

In fact, everyone was to blame for the crisis. The crisis was a one in a hundred years event. To use the highway analogy, “Everyone was driving too fast for conditions.” Government, Business, Consumers. Some people were driving faster than others, but all traffic was moving too fast, i.e., there was too much leverage, too much optimism, too loose credit standards. “Buy the largest house you can possibly afford and it will appreciate in value.” Everyone was living off the asset inflation bonus. An asset inflation bonus makes everyone feel wealthier because their homes, stocks, bonds, etc. are worth more.

Corporate credit quality had been declining for years. On average, from 1984 to 2004, S&P downgraded many more companies each year compared to the number of corporates they upgraded.


The Long Term Decline in Corporate Credit Quality
Downgrade-to-Upgrade Ratio Global 1981-2015
S&P 2015 Annual Corporate Default Study Table 6
Downgrades/Upgrades

Household Sector Net Assets

(Current $ in Trillions)

2003 $46
2004 $52
2005 $58
2006 $62
2007 $67
2008 $56
2009 $58
2010 $62
2011 $63
2012 $70
2013 $80
2014 $84
2015 $87

(Inflation Adjusted -- $84 in 2015 dollars)*

There was a deflation in Household Sector wealth. Household Sector Net Assets declined 16% in 2008.


In 2008, approximately $28 Trillion of Household Total Net Assets were in homes compared to mortgage debt of $10 trillion.
Trillions
• Household Total Income (GDP) $10
• Household Total Net Assets $28
• Household Mortgages debt $14
• Total Net Assets in homes $56

In 2008 GDP was $ 14 trillion versus total asset values of $56 trillion i.e. asset values were very high relative to cash flow (GDP). The important point to remember, however, is that a systemic crisis hurts everyone.
Losses in $ billions
• The Consumer (Decline in Net Asset Value) $12,000
• The Economy (2009 Reduced GDP) $ 500
• The Government (2009 Deficit) $ 1,500
• Goldman Sachs 2009 Net Income $ 13
• Goldman Sachs Increased Taxes $ ?
• Goldman Sachs Increased Regulatory Restrictions $ ?
• Goldman Sachs Pensions, Houses etc. $ ?

The question is how do we effectively evaluate credit after learning the lessons from the 2008/2009 crisis? How can we make the next panic less severe? In order to understand how to make the next panic less severe it is necessary to understand the myths that caused the 2008 liquidity panic. Only by understanding these myths can we better understand how to evaluate credit and the reasons for the recent regulatory changes.
There were three myths that caused the crisis of September 2008.
• Real estate loans are like any other loans. (80% of the cause).
• Credit derivatives are like any other derivatives. (10% of the cause).