Risk Ratings
How do you develop a risk rating model that blends judgment and automation?
Risk ratings at many institutions are inconsistent, untested, and ineffective from a competitive standpoint. The risk rating techniques at many institutions need review urgently.
Today one of the biggest questions that banks are asking as they review their rating systems is should the rating be applied to the borrower or should ratings also be assigned for each facility. Currently many systems factor in collateral as part of the borrower rating. Banks who want more granular views into the overall risk of a borrower and each extension of credit are developing systems with ratings applied separately.
Many banks are obtaining a competitive advantage and superior risk management by adopting quantitative techniques. While not as straightforward as using a consumer credit score as the basis for credit decisions the availability of quantitative data on both public companies and private firms is changing the way banks rate their borrowers.
Define the rating scale with more precision
One of the first steps in developing a risk rating system is defining what each risk rating category means to your institution. Commonly used rating systems may have a 10 point or 12 point scale; simplified 7 or 8 point scales are also prevalent although most banks are moving toward more granularity in risk ratings rather than less.
Once a bank has decided on the correct scale it is important that each category be well defined. Defining a 4 rating to mean, “Better than Average risk: borrower has elements of strength in liquidity with stable cash flow and a diversity of assets – strong management and better than average collateral coverage,” lacks precision and risks inconsistency in daily use.
Consistent application of the ratings starts with a common understanding of their meaning.
Transform qualitative information into quantitative inputs
Credit write ups for loan review committees often include a significant amount of narrative text about the borrower, industry, or collateral. For example, “Donald Ash, chairman, founded Sweet Birch Industries in 1972. Mr. Ash is a mechanical engineer who has been in the manufacturing industry since 1963. He has served as president and CEO of the company from 1972 until present.”
There is useful quantitative information hidden in this qualitative quip: Age of the Company (# years), Years under present management, Total Industry Experience (# years).
Using a quantitative scorecard, instead of a paragraph, is (a) faster in the sales process, (b) more reliable in credit analysis, and (c) available for trend analysis.
Automate financial factors
The best risk rating models will blend qualitative factors (after we transform them into quantitative inputs, of course) with quantitative factors. That means pulling in liquidity ratios, debt-to-equity ratios, or ratio derived from a borrower’s financial statement. It also includes data from third party credit score providers.
Assuming that the financial analysis solution that the credit analysts is fully integrated with the risk rating system and the loan origination system, then the next step is to automate the risk rating process, by drawing the relevant data from the financial analysis application.
Once the risk rating model has the quantitative information and the qualitative information from the scorecard, then we can weight the factors based on proprietary and/or statistical formulas.
Alternative Solution
If your institution already has a sophisticated risk rating model and you retest its statistical validity, then your next step may be to integrate that model with your loan origination system and portfolio management system so that lenders and portfolio managers can respond better to the market.
On the other hand, if your bank uses a simplified rating technique, then it may be time to review the competitive and regulatory climate to determine if changes will drive your bank to improve its risk rating techniques.
We invite you to attend our Risk Ratings Webcast, where you can learn specific ways to improve your risk rating system.
CreditQuest's Credit Manager is a complete solution for managing, reviewing and analyzing commercial credit applications, significantly reducing commercial application turnaround times while improving credit risk mitigation.
