The world of consumer financing completely changed several decades ago with the invention of the credit card. These days, most people pay for everyday purchases with a plastic card, and hardly give a thought to the reality that they aren’t exactly paying…they are accessing instant, frictionless financing.
In the world of business to business (B2B) transactions, that sort of seamless credit access hasn’t quite arrived yet. When it comes to small business that primarily serve other small businesses (also called SMB2Bs), credit primarily comes in the form of trade credit or “net terms.” Essentially, today, B2Bs often have little choice but to act like banks, extending credit terms to customers to facilitate transactions.
There are a number of reasons for this. In our guest post this month for the Lendio blog, we give an overview of how consumer credit came to be so convenient, and how business transactions got left behind:
One of the main reasons that SMB2B buyers rely so heavily on having additional time to pay, is that they are largely financially underserved. Even though small businesses comprise the majority of businesses in the U.S. and account for half of all private-sector employment, they often hit obstacles when attempting to access credit through conventional channels.
Small businesses are tremendously diverse in their size, business activities, and needs, and therefore a one-size-fits-all financial approach simply doesn’t work. With incomplete metrics and manual underwriting processes, traditional credit models are simply insufficient to serve the needs of small businesses. Yet banks still rely on incomplete consumer models and metrics such as business owners’ personal FICO scores to be the main factor in credit decisions.
How AI is changing SMB2B commerce
The good news for business owners is that technology has recently driven tremendous innovations in this area.
Alternative lenders like Fundbox, have begun to change the status quo. They’ve done so by using machine learning to build more sophisticated risk models that take into account more facets of business health and performance in order to make fast, sound lending and credit decisions:
Nontraditional fintech lenders, using artificial intelligence and sophisticated risk models, can now use data sources, such as accounting software and business bank accounts, to achieve a more complete and realistic understanding of the health and performance of a small business. […] Since modern underwriting processes are AI-driven and do not rely on manual labor, lenders can also drastically increase the speed of decisions, often transferring funds to approved businesses within a single business day.