Credit risk modeling for better credit quality
As an institution’s portfolio grows, it can be easy to get away from the basics. Effective risk identification starts with the evaluation of individual credits through solid credit risk modeling. This doesn’t necessarily require the licensing of oftentimes expensive, statistically-driven models and databases, which could be overkill or ill-suited for institutions that don’t have the volume of data to support a model.
Rather, credit risk modeling describes the analytical due diligence a bank performs to assess risk of borrowers. And since this risk is dynamic, the model must examine the ability of a potential borrower to repay the loan as well as non-financial considerations such as character, management ability, environmental conditions and factors.
Some financial institutions evaluate entire loan relationships, others prefer to rate each facility, and still others rate both relationships and facilities. Whichever approach the financial institution chooses, the following considerations are necessary for developing the credit risk model:
Credit risk factors could vary slightly, institution to institution, depending on the portfolio size, concentration, borrower composition, loan types, location, etc. As such, each of the following should influence the credit risk model.
• Determining risk factors.
• Understanding credit quality (risk grading/risk rating).
• Likelihood that a business/borrower/relationship may default on its financial obligations.
• Accommodating different types of loans as well as industries (different industries require different capital structures).
Global Cash Flow Analysis
A complete picture of the financial condition of a small business requires a careful review of income statement and balance sheet information for both the guarantor and the business. Personal assets are often pledged against the debt of the business, and business and guarantor financial assets are typically intermingled.
Credit risk doesn’t end with the loan decision at origination; rather, risk profiles of borrowers can change throughout the year and the relationship. To identify risk within the portfolio, credit risk models should include an annual review of loans. A minimum review period should be set that allows for continual monitoring and reassessing of risk.
Companies rarely remain in a static condition. However, far too often, the decision to grant a loan relies on cash flow analysis only, which examines a company at a point or period in time. It does not include a trend analysis, showing whether the company’s performance is improving, stable or declining. Although extremely important, cash flow cannot be the only determinant in credit quality. Credit analysis is much too complex to rely on just a single indicator, hence the suggested use of related factors.
At a given point in time, the business may have positive cash flow. The grey dashed line represents a cutoff debt service coverage ratio (DSCR) of 1.25. A loan decision based only on the DSCR threshold of 1.25 would be unwise in the case of the deteriorating business. Instead, an analysis should use trend data to determine if the business is growing or deteriorating.
A more comprehensive risk analysis based on the 5 Cs of Credit would include this type of longitudinal analysis and capture risk from externalities. Another element to consider is industry comparisons. Performance ratios are more meaningful when viewed in context of the borrower’s industry.
For more information on the 5 Cs of Credit and how to improve your credit quality, watch the on-demand webinar: The Real Price of Risk.