What Default Correlation means
Default correlation tells us how likely two different companies or people who owe money (we call them obligors) are to stop paying their debts around the same time. Think of it as a number that shows if one company has trouble paying its debts, how likely another company is to have similar troubles.
How It Works
When companies do business together or operate in the same industry, their financial health often moves together. A default correlation of 1.0 means two companies always default together. A correlation of 0 means their defaults happen completely independently. Most real-world default correlations fall somewhere between these numbers.
Examples Make It Clear
Here’s a real-world example: Picture two car parts makers that sell mainly to Ford. If Ford cuts back orders sharply, both suppliers might struggle to pay their debts simultaneously, and there would be a high default correlation.
But now, think about a car parts maker and a restaurant chain. They work in totally different industries with different customers. If one has money problems, it probably won’t affect the other much. Their default correlation would be low.
Banks Care About This
Banks and lenders pay close attention to default correlation. They want to avoid lending too much money to companies that might all run into trouble at once. It helps them spread out their risk.
Measuring Default Correlation
People who study credit risk use complex math and look at lots of data to figure out default correlations. They check things like:
- What industry the companies are in
- Where they do business
- Who are their main customers are
- How the overall economy affects them
This helps predict how likely companies are to default together.
Making Smart Lending Choices
Lenders use default correlation to make better decisions about who to lend to. A bank might be okay lending to both a farming company and a software company since they have a low default correlation. But they might think twice about lending to two farming companies in the same region.
