Credit risk management in a Financial Institution starts with the establishment of sound lending principles and an efficient framework for managing the risk. Policies, industry specific standards and guidelines, together with risk concentration limits are designed under the supervision of Risk Management Committee.
These policies, standards and procedures also govern how credit risk is measured, monitored, reported and controlled. As market conditions change rapidly, adequacy and effectiveness of internal controls should be reviewed at least quarterly.
The diversity of the business and economic conditions has led to the development of highly sophisticated tools and models to measure the exposure of a Financial Institution to Credit Risk. In case of an individual loan portfolio, the Probability of Default, Loss Given Default or credit rationing are the most commonly used ones to measure the exposure to Credit Risk. The invention of various credit scoring models that use observed loan applicants characteristics either to calculate a score representing the applicant's probability of default or to sort borrowers into different risk classes bring the ability to address Credit Risk on a new level. In particular, the Linear Probability, Logit, and Linear Discriminant models are used to evaluate mortgages and consumer loans and help to numerically establish the most important factors in explaining default risk, improve the pricing of the default risk, better screen out bad loan applications, and help calculating the reserves needed to meet the expected loan loss es.
However, there are no universal models, perfectly covering Credit Risk. Thus, it's possible for institutions to create their own credit scoring models in order to capture the risks that are specific to their segment, country or business areas.
The employment of various concentration limits - by industry or sector, country or credit rating help to better manage the concentration risk exploiting the diversification benefits and establishing the exposure limits. Financial Institutions also often use migration analysis which tracks the movement of a loan portfolio from one credit rating to another, based on the historical relative frequency.
Besides strict limits regulations, Financial Institutions also mitigate risk through credit derivatives that are aimed at transferring the risk to a third party. But the fact that some loans are sold can't eliminate credit risk at all, as the buyer of the derivative can also fail to pay. Thus credit derivative instruments can't fully remove credit risk, but they can help to diversify the portfolio.
But we have to understand, that even diversification is not a panacea. In normal market conditions, default of one partner is easily absorbed by the provisions and covered by profits from other clients. But as soon as market enters a major crisis, non-payment of one client can cause a chain reaction. Very soon liquidity dries up and all previous estimates are not valid any more. To model sustainability under severe downturn conditions Financial Institutions employ modern portfolio theory, stress-testing models, etc.
The peculiarity of the Credit Risk management is that with all sophisticated models at their disposal, Financial Institutions still depend on knowledge, experience, and judgment to provide input to these models. Thus a human factor remains key element in the successful risk management.