How Amazon Can Build a World Class B2B Credit File – Post I

Every sale made by a company of any reasonable size that is done on some extended payment terms is a credit decision.   All businesses grant credit to their customers in the form of payment terms. In order to do this, they develop credit limits to how much they can have outstanding to a customer at any one time. Whether a company has a dedicated process for credit lines with their buyers or does it in some haphazard fashion, the receivables are exposed, particularly the longer the sales terms.  See Even Sellers must manage Credit Risk like Banks

Sales organizations need reliable data to make customer credit decisions. Purchasing organizations need reliable data to assess supplier financial risk.

Both areas are can be involved in data gathering to do credit analysis which leads to an opinion on risk. In the case of Purchasing, its supplier financial risk.  In the case of Sales, it's can this customer pay me back.  There is nothing worse than have $2M in sales to a customer that never get paid due (or partially paid) after a bankruptcy event.

Most Sales and Procurement departments don’t have the horsepower to do this internally.  Data gathering leads to credit analysis, which leads to a credit opinion.  This is not a trivial exercise.  Therefore, many outsource the need to assess B2B counterparty risk to one of three players:

  • Experian, which gathers information from firms that have loaned a company money or extended credit. It also uses third party data such as legal filings, liens, judgments or bankruptcies.
  • Dun & Bradstreet, who has a product called PAYDEX which indicates a company’s credit worthiness by an analysis of a company’s one-year payment history, together with a credit score and a financial stress score, all courtesy of Dun & Bradstreet. The company must be able to draw data from at least four vendors to develop a PAYDEX report.
  • Equifax, which employs public records and payment history, as well as personal credit of a small business owner.

Why the Traditional Models Need Improved

The current credit bureaus suffer from a lack of real-time information, adverse selection, and very incomplete credit files, especially on private companies.

  • Real-time information - one only has to look to the Latin American economies in places like Brazil and Mexico where the government has real time data on domestic shipments and in some cases also in payments. But you don't have to go as far as South America to see what some specialty finance companies are doing in North America, accessing payroll information from companies like Paychex combined with big data combined with social media data to present a far more comprehensive picture then the credit bureaus can provide in their delayed world, which relies on accessing information from customers the old-fashioned way
  • Adverse selection – Credit bureaus can cherry pick a small number of vendors out of thousands to vouch for a company, providing information that could be misleading.
  • Incomplete information – probably the biggest challenge is the fact credit bureaus lack very important information to build a credit file on private companies – including legal ownership structure, contracting parties, parental guarantees, common payment terms, etc.

When we look at banks, they risk score every business to estimate the probability of default by their customer over the life of the facility, and also estimate the amount of loss they would suffer in the event of default.  They have this data but this data is not shared and certainly not sold as a service.

Ultimately the credit opinions companies take with their Sales departments providing customer credit limits, or banks providing loans must be matched against outcomes, ie, what losses were experienced. Even for international trade transactions, we have this problem where there is no readily available loss data.  Today, any data on trade finance losses is highly qualified, as pointed out by this recent article explaining how the ICC Trade Loss Registry is really a lobby tool, not a credible source for investors, see Fit for Purpose 

Tomorrow we will look at who can solve the problem of gathering the data and offering a service and can be disruptive in this space.

Jason and I see lots of opportunities here, and the changing dynamics of how credit is formed, underwritten and injected into supply chains is becoming pretty impressive compared to traditional methods. If you like to reach out to us, you can contact me at dgustin(at)

P.S. If you have a story, or a story idea, please email  All correspondence will be off the record.

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