What it means
When a manager bundles hundreds of loans into one vehicle, it matters whether those borrowers sit in the same industry. If a dozen are all oil companies, a drop in oil prices could hurt them all at once.
A diversity score condenses that concentration into a single figure. The best-known method comes from Moody's, a credit rating agency.
It groups borrowers by industry, assigns each group an equivalent number of independent, equally sized exposures, and adds the results. Because the method relies on published lookup tables, practitioners use the agency's own documentation to calculate it.
The score effectively answers: how many truly independent, equally sized exposures does this pool behave like? A pool with a score of 60 is treated as behaving like 60 independent borrowers, even though it may hold far more loans.
The score then feeds into how much protection the rating agency requires for the senior investors in the vehicle. Managers often have to maintain a minimum diversity score in their contracts.
If trading or defaults push the score below the minimum, they may be restricted from buying certain loans until it recovers. This keeps portfolios from drifting into heavy concentration.
The concept also appears in less formal ways. Analysts sometimes create their own proxy, such as the inverse of the sum of squared portfolio weights, to measure concentration.
These simple versions are easy to calculate but are not the same as an official rating agency score. Critics note that the approach has limits.
Industry groupings are broad, so two companies in one group may behave very differently, while companies in different groups may still depend on the same economic driver. Practitioners therefore treat the score as one input alongside other measures such as geographic spread and single-name limits.
In practice
Real-world examples.
Example
A loan fund manager sees that her diversity score has fallen because she bought several loans in the same sector. She sells one and buys a loan in a different industry to restore the minimum required by her investors. Doing so keeps the vehicle compliant with its documents and avoids restrictions on trading.
Example
A rating analyst reviews two otherwise similar loan pools. The one with the higher diversity score receives more favourable treatment because defaults are less likely to cluster. The agency then requires less protection for senior investors in the better spread pool.
Example
A bank treasury team compares its own corporate loan book with a published benchmark. It finds that 40% of exposure sits in two industries and decides to set tighter lending limits. The review also leads the team to look at geographic spread, not only industry.
Formula
Calculation
The official method uses agency lookup tables, so the figure below is a simplified proxy, often called the effective number of holdings:
Effective number of holdings = 1 / (sum of each weight squared)
Worked example: A loan pool of $100,000,000 is split across industries as follows: software 50%, healthcare 30%, retail 20%.
Squared weights: 0.50 x 0.50 = 0.25; 0.30 x 0.30 = 0.09; 0.20 x 0.20 = 0.04.
Sum = 0.25 + 0.09 + 0.04 = 0.38.
Effective number = 1 / 0.38 = 2.63 (rounded).
The pool behaves like about 2.6 equally sized industries. If the same pool were spread equally across 5 industries (20% each), the sum would be 5 x 0.04 = 0.20, giving 1 / 0.20 = 5, which is clearly more diversified.
Treat the result as a rough guide to spread rather than a measure of credit quality. A pool of weak loans can still show a high score.Case study
Seen in the real world.
Kestrel Credit Partners is a fictional manager of a pool of corporate loans. Its contract required a minimum diversity score, which it monitored monthly.
When one of its favourite sectors offered high yields, the team bought heavily and the score drifted close to the limit. In this illustrative case, a downturn in that sector then caused several loans to be downgraded together.
Because the manager had been forced by the minimum to keep other sectors in the pool, losses stayed within the protection built into the vehicle. The illustrative lesson is that the score acts like a speed limit on concentration. The manager now reports the score to investors every month, alongside its largest industry weights.
Watch out
Common mistakes.
- Reading a high score as meaning low risk overall. The score only measures spread across industries, not how risky each borrower is. A pool of poor quality loans can still have a high score.
- Treating a simple proxy as the official score. Rating agencies use their own tables, so results will differ. Tables, groupings and treatment of related borrowers differ, so the proxy is only a rough guide.
- Ignoring other forms of concentration, such as geography or a single large borrower. A pool can have a good score and still be exposed in those ways. A pool can look varied by industry and still be exposed to a single region or a few large names.
Questions
People also ask.
Who uses diversity scores?
Mainly rating agencies, CLO managers and investors in structured credit vehicles. It is also a useful reference for banks and analysts reviewing concentration in a loan book.
Does a higher score always mean better returns?
No, it only describes the spread of risk, and returns depend on many other factors. Returns depend on loan pricing, defaults and costs, not only on diversification.
Can the score change over time?
Yes, it moves whenever loans are bought, sold, repaid or defaulted. Even a small trade can alter the industry mix and therefore the figure.
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