A pool can look diversified until the top customers, channels, or end markets are mapped correctly.
By Noah Green CPA CFE, Sheepdog Prosperity Partners LLC
Why diversification claims usually overstate diversification
A receivables portfolio’s concentration is rarely what its account count suggests. A seller with 2,000 obligors will describe the portfolio as diversified. The borrowing-base concentration limits in the credit agreement will key off the top-obligor face. The investor or lender doing the math will conclude that no single account represents more than two or three percent of the portfolio. The diversification looks real.
It is real along the dimension being measured and absent along the dimensions that are not. A portfolio of 2,000 invoices to entities that operationally depend on the same regional supermarket chain is concentrated. A portfolio of 1,500 small-business customers all selling into a single industry vertical is concentrated. A portfolio whose largest 50 obligors are subsidiaries of three holding companies is concentrated. Each of those concentrations is invisible to a standard cut by obligor name and visible to a different cut performed for the purpose of finding it.
The diligence work on concentration is therefore not “is this portfolio concentrated” — it almost always is, somewhere. The work is “along which axes.” Each axis has its own analytical approach, its own evidence requirements, and its own implications for structural protection. A portfolio that has been properly concentration-analyzed is a portfolio whose concentrations have been named, sized, and routed to the structural lever appropriate for each one.
The article that follows takes the four concentration axes in sequence. The first is the standard cut everyone runs. The other three are the cuts where concentration usually lives and the cuts that diligence files usually miss.
Part 1 — Obligor face concentration: the necessary baseline
The first axis is obligor face concentration — the share of total receivables attributable to each named obligor, ranked by exposure. This is the standard cut. Every credit agreement keys off this measurement. Every concentration limit is calibrated against it. Every reporting package shows it.
The diligence questions about face concentration are straightforward. What is the top obligor by face value as a percentage of the portfolio? Top 5? Top 10? Top 20? What is the implied effective number of obligors (the Herfindahl-Hirschman concentration index for those familiar with the calculation)? How has the concentration changed over time, and is the seller’s customer-acquisition trajectory consistent with the concentration trend?
The diagnostic from face concentration is whether the seller’s reported diversification matches the calculated reality. A seller that describes its portfolio as “diversified across 2,000 customers” while running 35 percent concentration in the top 10 is not describing the same portfolio the math describes. The diligence work is not to question the seller’s wording — it is to confirm what the credit decision is actually being made against.
A subtle face-concentration question is the stability of the top-tier exposure. A portfolio with 25 percent concentration in the top 5 obligors that has been stable for years is one risk profile. A portfolio with the same concentration today driven by three obligors that were added in the last 12 months is a different risk profile — the diversification benefit of the historical base is being eroded by recent customer concentration. The diligence work is to age the top-tier exposure: how long have the top 5 obligors been in the portfolio?
Face concentration is the necessary baseline. It is not sufficient. It is the cut against which the credit agreement’s concentration limits operate, but it usually understates the real economic concentration in the portfolio. That understatement is what the next three axes correct for.
Part 2 — Economic concentration: the related-party cut
The second axis is economic concentration — the share of the portfolio attributable to obligors that are economically related to one another, regardless of legal name. Economic concentration is where face concentration most often misleads.
The first form of economic concentration is parent-subsidiary structure. A receivables portfolio that names 25 separate corporate obligors may have 8 of those obligors owned by a single parent company. From the seller’s billing-system perspective, those 8 are distinct customers; from the credit-risk perspective, a financial event at the parent affects all 8 simultaneously. The diligence work is to obtain the seller’s customer list with parent-company affiliations identified — if the seller doesn’t track parent affiliations, the diligence team builds the mapping from public sources or commercial databases for the top 50 obligors.
The second form is common-control structure. Two entities with different parent companies may be controlled by the same individuals through holding-company structures, private equity ownership, family offices, or trust arrangements. These structures are less legible than parent-subsidiary affiliations but produce similar concentration effects. The diligence work for high-exposure obligors is to identify ultimate beneficial ownership, which may require regulatory filings, public-records searches, or direct inquiry.
The third form is supply-chain or commercial-relationship dependency. Two entities with no ownership relationship may depend on the same upstream supplier, downstream customer, or commercial counterparty in ways that link their financial outcomes. A receivables portfolio of independent restaurants all sourcing from a single regional foodservice distributor is concentrated against the distributor’s health. A portfolio of independent retailers all leasing space in the same shopping-mall operator’s properties is concentrated against the mall operator. These commercial-relationship concentrations require industry-specific diligence to surface.
Labels are not mechanics. A portfolio described as “diversified across independent obligors” is a label. The mechanics are whether those obligors are economically independent, and economic independence depends on ownership, control, and commercial relationships, not just legal-entity separation. Diligence work that stops at the seller’s customer-name list is accepting a label as evidence of mechanics.
Part 3 — Industry, geographic, and counterparty-relationship concentration
The third axis is concentration along dimensions other than obligor identity — industry exposure, geographic exposure, and dependence on shared counterparties.
The industry-concentration question requires accurate industry classification of each obligor. The seller’s classification is rarely sufficient. Sellers often classify customers by what they sold to them rather than by what the customers actually do (a custom-printing shop might be classified as “manufacturing” by the seller and as “professional services” by industry-standard classifications). The diligence work is to classify the top 100 obligors using a consistent industry taxonomy (NAICS at the 4-digit level is standard) and compute industry concentration against the resulting cut. A portfolio with 35 percent of its receivables face exposure to a single 4-digit NAICS code is concentrated to that industry’s cycle, regardless of how many obligors are in the portfolio.
The geographic-concentration question is similar but typically measured against where the obligor operates rather than where it’s billed. A seller billing a customer’s headquarters in one city while the customer operates in a different region creates geographic ambiguity in the concentration analysis. The diligence work is to identify the obligor’s operating geography — for customers with multiple locations, weighted by the location concentration of the receivable activity — and compute geographic exposure against that. A portfolio with 40 percent of its face exposure operating in a single metropolitan area is concentrated to that area’s economic cycle.
The counterparty-relationship question is the most often missed of the three. Many receivables portfolios in specific industries (consumer products, automotive parts, food service) have all of their customers selling into the same downstream anchor — a national retailer, an automotive OEM, a major restaurant chain. The portfolio looks diversified by direct obligor but is economically concentrated against the anchor’s financial health. The diagnostic question for the seller: who buys what your customers sell? If the seller cannot answer that for the top 20 obligors, the counterparty-relationship concentration has not been analyzed.
A useful drill-down: name the largest single end-market customer for each of the top 20 obligors and compute how many of those 20 obligors share end-market customers. A portfolio where the top 20 obligors share fewer than 5 distinct end-market customers is a portfolio with significant counterparty-relationship concentration that the standard cut does not capture.
Part 4 — Stress-correlated concentration: the concentration that activates together
The fourth axis is the most consequential and the hardest to measure: concentration along dimensions that activate together under stress. This is concentration in correlation rather than in single-dimension exposure.
The concept is that two obligors that look uncorrelated under normal conditions can become highly correlated under specific stress conditions. A receivables portfolio of small-business customers across diverse industries may all be highly correlated against a regional bank-credit-availability shock, because most small businesses depend on the same revolving-credit infrastructure to manage working capital. A portfolio of mid-market customers in different industries may all be highly correlated against an interest-rate shock, because all of them carry floating-rate debt that compresses operating cash flow under tightening. These correlations are invisible during benign conditions and decisive under stress.
The diligence work for stress-correlated concentration is to identify the specific stress factors the portfolio’s obligors share exposure to, beyond industry and geography. Common factors include: regional bank dependence for working capital, exposure to a specific supplier or supplier category, dependence on a regulatory regime that could change, exposure to a single regional or national policy mandate, dependence on a specific commercial infrastructure (a payment processor, a logistics provider, a software platform).
For each identified factor, the diligence work is to compute the portfolio’s exposure (what fraction of obligors have material dependence on the factor) and to identify whether that exposure clusters in particular face-concentrated obligors. A portfolio where the top 20 face-concentrated obligors all share dependence on a single regional bank for working-capital financing has a concealed concentration that face-by-face analysis will not surface.
This axis is also where industry- and geography-concentration concerns are sharpened. Industry concentration matters because it identifies a single set of cyclical and regulatory factors that affect all the concentrated obligors together. Geographic concentration matters because it identifies a single set of local economic conditions that affect all the concentrated obligors together. Stress-correlated concentration takes the question one level deeper: what specific stress factors, beyond industry and geography, link the obligors’ outcomes?
A useful diagnostic question for the seller: in the most recent local or industry stress (a regional economic event, a sector downturn, a regulatory change), how did your portfolio’s delinquency and dispute rates respond? If the seller has no data on portfolio-level response to a recent stress event, the stress-correlated concentration is unmeasured. The portfolio has not yet been stressed in a way that would reveal it, but the portfolio still has it.
What the concentration limits are supposed to do
The structural lever for managing concentration risk is the combination of obligor-level concentration limits in the borrowing base, industry- and geographic-concentration limits, and discretionary triggers tied to stress-correlated factors. Control matters because cash flow without control is an expectation, not protection. Each concentration axis maps to a corresponding structural protection.
Face concentration maps to obligor-level eligibility caps and step-down advance rates as concentration increases. Economic concentration maps to related-party look-through provisions that aggregate exposures across parent-subsidiary and common-control groups for limit purposes. Industry, geographic, and counterparty-relationship concentration map to sector-level caps and to trigger events that step down the advance rate when sector exposure exceeds defined thresholds. Stress-correlated concentration maps to discretionary triggers that allow the lender to step down advance rates when identified stress factors materialize.
The diligence work is to confirm the structural lever responds to the concentrations the diligence has actually found, not to a generic concentration framework. A credit agreement with sophisticated face-concentration limits and no industry or counterparty-relationship limits has structured for the easy concentration cut and left the harder ones unprotected. The diligence file should map each surfaced concentration to a specific structural protection.
Structure manages uncertainty; it does not eliminate it. A well-designed concentration framework cannot rescue a portfolio whose actual concentration is wider than the framework anticipated. It can compress the lender’s exposure as concentration drifts. The work is in the diagnosis; the structure responds.
A diligence sequencing recommendation
Concentration diligence has a sequence that produces signal and a sequence that produces comfort. The signal sequence starts with the customer list and the parent-affiliation mapping, not with the seller’s diversification narrative.
In order: first, obtain the customer list with face exposures and verify against billed-and-collected history. Second, map parent-subsidiary and common-control relationships for the top 50 obligors. Third, classify the top 100 obligors by 4-digit NAICS and by operating geography, and compute concentration along each cut. Fourth, identify the counterparty-relationship and stress-factor concentrations the portfolio carries. Only after the four axes have been independently analyzed should the diligence team compare the findings to the seller’s reported concentration metrics.
When concentration analysis has done its job
A receivables portfolio’s concentration has been underwritten when the diligence team can state, for each of the four axes, what the concentration is, what the trend has been, what stress would activate it, and what structural protection responds to it. If the team cannot make those four statements for each axis, the concentration analysis has not been done. The portfolio’s diversification has been described, not measured.
A pool is diversified when its obligors are economically independent across the dimensions the credit decision depends on. Concentration analysis is the discipline of identifying those dimensions before deciding whether the diversification claim survives them.
Practical diligence checklist
- Compute face concentration for the top 5, top 10, and top 20 obligors as a percentage of total receivables — measure the Herfindahl-Hirschman index and effective number of obligors.
- Age the top-tier exposure — identify how long each top-5 obligor has been in the portfolio and what fraction was added in the last 12 months.
- Map parent-subsidiary and common-control relationships for the top 50 obligors — compute economic concentration on the aggregated cut.
- Classify the top 100 obligors by 4-digit NAICS using a consistent industry taxonomy — compute industry concentration against the resulting cut.
- Identify the operating geography for each top-50 obligor and compute geographic concentration — confirm the seller’s billing-address concentration matches the operating-address concentration.
- For the top 20 obligors, identify the largest single end-market customer — measure counterparty-relationship concentration.
- Identify the specific stress factors (regional bank dependence, regulatory exposure, supplier dependence) the obligors share — compute the fraction of the portfolio exposed to each factor.
- Map each surfaced concentration to a specific structural protection in the credit agreement — face limits, related-party look-through, sector caps, stress-factor triggers.
Red flags to escalate
- The seller describes the portfolio as “diversified” but cannot produce parent-subsidiary affiliation data for the top 50 obligors.
- Face concentration in the top 5 is stable but has been driven by recent obligor additions while older obligors have been declining — diversification benefit is eroding.
- Industry classification differs materially between the seller’s categorization and a standard NAICS-based cut — concentration may be present in industries the seller does not recognize as such.
- The portfolio’s top 20 obligors share fewer than 5 distinct end-market customers — counterparty-relationship concentration is high and unmeasured.
- The seller has no data on how the portfolio responded to the most recent local or industry stress — stress-correlated concentration has never been observed and cannot be ruled out.
- The credit agreement contains sophisticated face-concentration limits but no industry-, geographic-, or counterparty-relationship limits — the structural lever addresses only the easiest concentration cut.
This article is for educational purposes only and does not constitute legal, investment, accounting, tax, or credit advice. Examples may be simplified or fictionalized composites unless otherwise identified as public-source case studies. Author byline: Noah Green CPA CFE, Sheepdog Prosperity Partners LLC.