Credit rating is an evaluation of the credit risk of a prospect (an individual, company or government), predicting their ability to pay back the debt. This is a forecast of the likelihood of the debtor defaulting, which means not being able to pay back the debt.
The challenge is there are several agencies that provide rating systems. They do not attach a hard number of probability to default. So in a credit risk determination, those ratings of different agencies must be standardized for a particular product and specific financial organization.
Financial institutions require the standard credit risk rating combining multiple rating of agencies in a standard model to validate whether or not to give an individual or a company a line of credit, e.g. loan, credit card, insurance, etc.
The Standard Ranked Credit Rating
Companies such as Moody’s, S&P, and Fitch Rating are not the only agencies to provide credit ratings. Depending on the financial institutions, they may use multiple of agencies, and they will need to create a standardized system to combine the rating from different agencies.
This decision to “Determine Standard Ranked Rating” is consisting of three main parts:
- Standard Credit Rating: Mapping and Combining the Credit Rating of multiple agencies to a “Standard Rating”
- Credit Rating Rank: Ranking “Standard Rating”
- Selecting the “Standard Credit Rating” based on the Rank
Combining the Credit Rating
At this step of the decision, we combine the rating of multiple agencies in a simple DecisionGraph, As this can be a more complex decision itself for each long-term and short-term rating:
To establish a standardized rating system from the different types of ratings provided by various agencies, we map their rating against a “Standard Rating”. In the below DecisionTable, we show the mapping for S&P.
For the rest of the agencies we will have a similar Decision Table based on their own “Native Rating”.
The other approach is to combine all the agencies in one Decision Table, but it makes it hard to update and alter as each agency has its own Long-term and Short-term rating.
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Ranking the Standard Rating
Standard ratings can be ranked by using a simple ranking algorithm. The ranking enables comparison between different types of agencies. For instance, an investment with a AAA rating from S&P produces a numerical value against the standard rating scale that compares the BBB rating from Moody's.
For this scenario, we use a model that ranks credit ratings on a scale of 0 (lowest) to 22 (highest) highest rank as below DecisionTable:
Since this ranking logic is separate from the standardization of ratings, it can be managed separately and reused in other scenarios.
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Standardization of credit rating in financial institutions enables them to combine and rank the rating of different agencies, and use a standard rating across the organization. Hence this standardization gives them the flexibility of using multiple agencies, in addition, it will enable them to mix the score with their own custom credit rating based on individual products and scenarios.
By framing business decisions, we can break down complex decisions such as Standard Ranked Ratings into simpler, easier-to-understand decision units. Then, each decision unit can use different techniques and models to implement the logic i.e. DecisionGraph and DecisionTable. Even in some scenarios, you can use other technologies, such as Machine Learning or Process modes, to satisfy a specific decision unit as part of the larger decisioning scenario.
Last updated November 23rd, 2022 at 03:42 pm, Published October 12th, 2022 at 03:42 pm
CEO and the founder of FlexRule – He is an expert in architecture, design, and implementation of operational decisions, business rules, and process automation. Created Decision-Centric Approach, a methodology that brings People, Data, Rules, and Processes together to automate operational business decisions.
This approach is recognized by Gartner as the missing link to provide business value to organizations.