Author Archives: David Gustin



About David Gustin

David runs a global research and advisory practice centered on helping financial institutions, vendors and corporations understand the intersection of trade services, trade credit, payments and the financial supply chain. His formal education includes an Information Systems and Economics degree from Carnegie-Mellon University, an MBA from Purdue, and a Chartered Financial Analyst designation.


What Happens When Machine Learning Finance Models Fail

These are some strange times. Look, we have $16 trillion of negative yielding bonds, that’s T, for trillion. I’m asked by non-financial people why anyone would want to buy negative yields (you pay to hold them, btw) and I reply, it’s not about income, it’s about trading that rates will fall further.

Which got me thinking: If we are in some liquidity trap world and negative interest rate environment, what does that do to all these invoice financial models being built using the latest and greatest in artificial intelligence and machine learning?

Dynamic Discounting: Backdrop, Definitions, and Enablers

finance

Editor's note: This is a refresh of our 2014 series on dynamic discounting, which originally ran on Spend Matters PRO.

This Spend Matters Plus brief provides a primer on one of the timeliest topics in receivables and payables finance: dynamic discounting. Note that by receivables financing we mean the selling or other leveraging of “receivables” as an asset on a supplying organization’s balance sheet to receive early payment. By payables financing, we mean the financing of early payment by a third-party (or the buying organizations’ balance sheet).

Even this subset of trade financing is a big and complicated topic, but in this analysis, we’ll discuss how dynamic discounting can reduce risk and create greater liquidity in the supply chain. If you’re in procurement or accounts payable and are new to the topic, this brief will be a useful first step in understanding what dynamic discounting is, how it can help, and which technologies and vendors can enable it.

Pricing Power and Playing with Payment Terms

savings

For many large companies, extending terms is the easiest way to hold on to cash and make working capital your suppliers’ problem. There are countless examples of large public companies with terms that seem to go beyond common sense.

Will this stop? Is this morally right? I’m not here to pass judgment, but what I would like to better understand is how will inflation impact a supplier’s ability to pass along price increases.

Why E-Invoicing Needs Machine Learning to Accelerate Invoice Finance

In the past, most procurement organizations would admit to doing a generally poor job of linking buying processes to the actual receipt of invoices, the invoice approval process and the subsequent payment to suppliers.

But in more recent years, corporations have moved to the cloud for document and data exchange around their source-to-pay processes, driven by factors including the rise of platform-based technologies that drive efficiency and effectiveness in the procurement and accounts payable areas as well as by government tax regulations.

Many invoices still come in via PDF and paper, and require some form of machine recognition. With machine learning, providing scanned documents and automatic extracting offers a way to make instant credit decisions for off-platform funding.

Supply Chain Finance: Gray Area Abounds on Early Pay Programs, Accounting

Whichever way you look at it and define it, supply chain finance has grown into a big number. And if you define it as using the balance sheet of a large company to offer early payment to some or all of its suppliers, it is has gained in popularity. Plus, it’s not only offered by large banks who can both originate and distribute large-scale programs for the likes of Unilever or Procter & Gamble, but also non-bank asset arrangers like Greensill, Seaport and others working together with source-to-pay platforms or directly with buyers to develop programs. And always in the background we have heard this whispering of accounting treatment. And by now, most people who have dabbled in this space know the issue: Is it trade payable or is it debt? Fewer understand the implications.

Why Platforms Need to Monetize Their Supplier Ecosystem

Because P2P solutions started giving away supplier portals, cash flow optimizers, analytics, support, etc., they closed a revenue door. Trying to build a sustainable business model when half your ecosystem is not monetized is very challenging, even as P2P platforms add features and functionality. Sure, many platforms are trying to figure out payments, and that is something that scares the bejeebers out of them due to regulations and compliance rules. (Don’t pay that blacklisted vendor or person, or else.) But payments is not a profitable business for platforms, it’s a service.

Post-Confirmation Dilution in an Uncertain Credit World

e-invoicing

How long has this benign credit cycle been going on? How about since 2008, when the Fed began dumping money into the economy to go way beyond its mandate as a last-stop liquidity gap. This has led to many distortions in the credit and capital markets, and one area where this is poorly understood is around “approved” invoices. Despite what many players in the space might believe, underwriting is necessary — even  critical. Even though the invoices that are on the platform are, by definition, approved for payment (i.e., highly de-risked), they are by no means risk-free.

Using Information Advantages to Finance B2B Transactions

We've all heard the stories around how supply chains are digitizing. A real transformation is underway, no doubt. But transformations don’t happen overnight. Likewise, traditional forms of financing supply chains still dominate. Many new models of lending have emerged over the last few years that rely on the approved invoices and third-party money, and while some models have generated volume, these pale in comparison with total B2B transactions. This is not to say there are not failures. In fact, the innovations that have been tried and failed lead to further innovation, piggybacking off of lessons learned.