By: Previse’s CEO, Paul Christensen, and Maya Bailey-Braendgaard, a Product Analyst.
Buy now, pay later (BNPL) offerings have become a well-established part of today’s purchasing experience. Driven by advances in financial technology and e-commerce, consumers now have the choice to pay after the point-of-sale, offering the consumer market (B2C) a more flexible payment process than ever before. All consumers have to do is choose their items, navigate the checkout as normal and opt to pay in future instalments.
Such flexibility is yet to feed into the business market (B2B), where BNPL is already the norm, but not in the way that we understand for consumers. In B2B, where the buyer is a corporate, the default process is typically a “credit” transaction, meaning corporates almost always buy now, pay later – with payment terms of up to 30, 60, 90 or 120 + days. Why is that?
Firstly, BNPL is seen by corporates to give them a financial advantage, enabling them to hold on to cash. Secondly, it gives them the chance to check that the goods and services are acceptable.
Sellers in B2B would love to have the option of an instant “cash transaction”. With the technology now available, it is straightforward to facilitate a “sell now, paid now” (SNPN) option, without impacting the two reasons why Buyers insist on BNPL.
SNPN solutions can be financially beneficial to both sellers and corporate buyers. Although holding onto cash is often seen as a “free loan” by corporates, this short-term gain is saddled by the long-term impact of the higher cost of goods sold by paying for the suppliers’ finance cost. BNPL is also financially damaging to the supplier, as the money doesn’t reach the supplier until the buyer has accepted the goods or services which typically takes weeks or months.
In B2C, if I buy a pair of shoes on the internet, money flows in a “cash” transaction, and if I ultimately choose not to accept the shoes, then the transaction can be unwound on an exception basis.
Until now, this hasn’t existed in B2B. With machine learning, however, it is possible to precisely assess the probability of recovering any overpayments and identify the very small number of transactions likely to be problematic. There is no longer any need for a B2B payment to be contingent on the buyer accepting the goods or services. B2B can be just like B2C.
By using machine learning to accurately predict future revenues and price risk, it is possible to automatically screen B2B transactions at the point of sale and allow them to be unwound on an exception basis. This means that every seller can have the choice to be paid when they sell, not later. Data makes it possible.