A practitioner's reference. Who supplies credit intelligence, how their business models differ, who consumes the data — and how to decide which providers belong in your RFP, and why.
Everyone draws on the same public-record substrate — statutory filings, published accounts, insolvency and court records, ownership structures. The differentiation is the proprietary layer each category adds on top, and the decision it is built to support.
Three different jobs, not three rungs. These categories are not a quality ranking. A capital-markets rating and a trade-credit score answer different questions for different buyers. The "O2C relevance" marker on each group shows how central it is to a day-to-day credit or order-to-cash function — which is the inverse of how the capital markets would rank them.
Two of the three provider groups barely change across the globe — capital-markets ratings are a worldwide oligopoly, and the major credit insurers are global. The trade-credit bureau layer is the exception: a patchwork of entrenched national champions. A global O2C operating model is therefore a multi-bureau model, orchestrated — not one global vendor.
Who you actually use for trade-credit data, by region and country. Bold marks the provider that leads that market. The names in the capital-markets and insurer groups stay the same everywhere; only this layer shifts.
| Country | Market leader | Also present |
|---|---|---|
| United States | Dun & Bradstreet | Experian Business, Equifax Business |
| Canada | D&B Canada, Equifax | TransUnion |
| Country / sub-region | Market leader | Also present |
|---|---|---|
| UK & Ireland | Creditsafe, Experian | D&B, Equifax |
| DACH (DE / AT / CH) | Creditreform | CRIF (Bürgel), D&B, KSV1870 (AT) |
| France | Altares (D&B partner) | Ellisphere, Coface |
| Benelux | GraydonCreditsafe | Atradius / Iberinform, D&B |
| Italy | CRIF, Cerved | D&B |
| Iberia (ES / PT) | Informa D&B, Iberinform | CRIF, Einforma |
| Nordics | Bisnode / D&B Nordic | Creditsafe, UC |
| Central & Eastern Europe | CRIF, Creditreform | Coface, CreditInfo |
| Sub-region | Market leader | Also present |
|---|---|---|
| Gulf & Middle East | Dun & Bradstreet (Dubai / DIFC) | SIMAH (Saudi), Al Etihad Credit Bureau (UAE), Coface |
| South Africa | TransUnion, Experian | XDS, CreditInfo |
| Rest of Africa | CreditInfo, D&B | TransUnion Africa, CRB Africa |
| Country / sub-region | Market leader | Also present |
|---|---|---|
| Japan | Teikoku Databank, Tokyo Shoko Research | — |
| Greater China | Local platforms + PBoC registry | Sinosure (insurance), Huaxia D&B |
| India | CIBIL (TransUnion), CRIF High Mark | Experian, Equifax |
| Australia & NZ | illion, Equifax (ex-Veda) | CreditorWatch, D&B |
| Southeast Asia | CRIF, Experian, local bureaus | Credit Bureau Singapore, D&B |
| South Korea | KED / NICE | KIS |
| Country / sub-region | Market leader | Also present |
|---|---|---|
| Brazil | Serasa Experian | Boa Vista (Equifax), SPC, Quod |
| Mexico | Buró de Crédito (TransUnion), Círculo de Crédito | D&B Mexico |
| Andes & Southern Cone | Experian (DataCrédito), Equifax | TransUnion |
Same underlying data, very different ways to package and sell it. The model determines how you pay, what you can rely on, and where each provider's incentives sit. Each card reads the same way: what it is, why it's built that way, what you gain, what you give up.
All three stand on the same public-record base — financial statements, payment behaviour, filings, ownership. They diverge on the proprietary layer they add, the decision they're making, and how they consume the data.
"Should I ship this order?"
Sales wants every order approved; credit wants security. The agency data is the neutral arbiter — objective cover for an unpopular decision.
A bad-debt write-off on the invoice — direct hit to the AR ledger.
"Is this bond priced correctly for its risk?"
The issuer-pays model creates a conflict of interest. Sophisticated analysts discount agency ratings and use them as one of several inputs.
A mispriced trade — capital loss on the position or missed return.
"Does my model correctly predict who defaults across 50,000 obligors?"
Data quality, coverage gaps, and survivorship bias are existential problems. A gap in the input corrupts the model output.
A regulatory-capital miss — under-provisioning, IFRS 9 breach, or supervisory challenge.
The same dimensions across all three personas, for quick reference.
| Dimension | Credit controller | Capital markets analyst | Risk model builder |
|---|---|---|---|
| Employer context | Corporate AR / O2C team | Bank, fund, or broker | Bank, insurer, or RegTech |
| Counterparty | Trade debtor | Bond / loan issuer | Portfolio of obligors |
| Core decision | Extend credit? How much? | Buy / sell / hold? | Is the model calibrated? |
| Time horizon | 30–90 days | 1–10 years | Through-the-cycle |
| Volume | High (hundreds to thousands) | Low-medium (focused) | Very high (entire portfolio) |
| Data freshness | Real-time / daily | Periodic + event triggers | Historical depth + snapshot |
| Preferred format | Dashboard, traffic light, alert | Report, rationale, model | Raw feed, API, scored dataset |
| Key metric used | Credit limit, DSO impact | Spread, migration, rating | PD, LGD, EAD, correlation |
| Primary provider | GraydonCreditsafe, D&B, Experian | S&P, Moody's, Fitch | Moody's Analytics, S&P MI |
| Consequence of error | Bad-debt write-off | Mispriced trade / capital loss | Regulatory-capital miss |
| The question | "Ship the order?" | "Right price for the risk?" | "Does the model predict?" |
The individual consumes the data; the company signs the contract. Each card reads the same way: who buys, how the deal is structured, what's negotiable, and the one contractual risk that matters most.
Agencies disclaim liability for credit decisions made on their data. The contract buys information, not an opinion you can sue over.
Limit withdrawal. Cover can be cut precisely when a buyer weakens — leaving you exposed on the receivable you most wanted insured.
A published rating is a legally protected opinion. The contract gives access — not any warranty on rating accuracy.
Model dependency. If the vendor changes its scoring methodology mid-contract, your internal model breaks. Fight for version-stability and change-notification windows.
| Employer type | Buys | From | Relationship driver |
|---|---|---|---|
| Corporate (O2C) | Trade credit data & monitoring | Trade bureau (D&B, GraydonCreditsafe, Experian) | Operational efficiency + bad-debt reduction |
| Corporate (Treasury) | Receivables insurance + a credit decision | Insurer (Atradius, Allianz Trade, Coface) | Risk transfer + financeable receivables |
| Issuer (corporate) | A published credit rating | Big Three (S&P, Moody's, Fitch) | Capital-market access & investor confidence |
| Investor / analyst firm | Research platform access | Big Three or redistributors (Bloomberg) | Investment decision support |
| Bank / insurer | Raw data feeds + model inputs | Analytics arms (Moody's Analytics, S&P MI) | Regulatory capital & IFRS 9 compliance |
Orientation reference for credit and O2C professionals. Provider categories describe the job each does, not a ranking. Product names, scores and ownership reflect publicly reported information at the time of writing and may change — verify current coverage and terms directly with each provider before an RFP.
We turn this landscape into a shortlist that fits your O2C operating model. A 30-minute call, no deck, no pitch.