\chapter{Introduction}
\label{ch:intro}


\section{Credit Risk Methodology}


\hspace{.25cm} In recent months more emphasis has shifted to the modeling and evaluation of credit risk. There are several forces behind this trend. First, credit markets have grown steadily and the credit derivatives market (CDS) has grown exponentially. Second, credit risk is still a developing field.  The understanding and the methodologies in managing and measuring other market risks, including interest rate risk, currency risk etc., have matured and are now assessed based on widely accepted principles.  


\hspace{.25cm} Credit markets are implying significant levels of of default over the next twelve months, but rating agencies, such as Moody's or Standard and Poors, downgrades and realized defaults have yet to follow suit.  This is apparent in the latest sub prime bubble bursts and the more recent defaults such as Lehman Brothers that have surprised the economy.  Therefore, in order to stay afloat in the financial, one needs to become more active in credit risk management to avoid substantial losses in any position.

\hspace{.25cm}  Any approach to credit risk management has o balance many often competing requirements.  Objectivity, accuracy, and stability are all important, but not at the expense of timeliness.  Last, but not clear, coverage is important for consistent decision-making across large portfolios.  Given these requirements, the approach to credit risk is to steer a course between market signals and fundamental creditworthiness, but mixing financial statement and equity market data together within a credit scoring framework.  By using financial statements, which will focus on the internal factors that drive company credit risk, and the inclusion of equity market signals adds timeliness, recognizing (as Merton did in 1974) that equity prices and equity volatility will be useful factors for the a measurement of riskiness of an issuer's debt.  In this paper, have collected a database of risk factors and risk measures of individual companies to identify a either company level, or an industry level, probabilities of default using statistical models and analysis.  



