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How Jack Dorsey stumbled onto the key insight behind Square

Name: How Jack Dorsey stumbled onto the key insight behind Square
Uploaded: 2024-01-26T15:49:38+00:00
Duration: 2 min 15 s
Channel: Lorenzo
Description: This transcript records Jack Dorsey and another speaker describing how Square evolved from a hardware card-reader idea into a payments platform by…

26 Jan 2024 · 2 min

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2:15

This transcript records Jack Dorsey and another speaker describing how Square evolved from a hardware card-reader idea into a payments platform by reframing fraud/eligibility assessment. They discovered many small businesses were denied by banks because of credit checks; instead, Square built software risk models that evaluate behavior at the transaction level. As a result, they increased the percentage of applicants accepted from roughly 30–40% to about 99%, enabling broader access for entrepreneurs with limited credit history.

Questions this video answers

About 30–40%.

Approximately 99%.

Chapters

We weren't expecting this at all when we started.
We thought we were just building a piece of hardware to enable people to.
Plug it into their phone and swipe a credit card.
And then as we talked with people who actually tried to accept credit cards in the past, we found a consistent theme which many of them weren't even allowed to process credit cards.
And we dug a little bit deeper, again asking that question. And we found that a lot of.
Them would go to banks or these merchant acquirers, and waiting for them was a credit check and looking at a FICA score.
And many of the businesses that we.
Talk to and many small businesses, they don't have good credit or a credit history.
They're entrepreneurs who are just getting started, taking a lot of personal risk, financial risk.
And it just felt ridiculous to us that for, for the job of being able to accept money from people, you had to get your credit checked. And as we dug deeper, we realized.
That wasn't the intention of the financial.
Industry, but it's the only tool they had available to them to understand authenticity, intent, predictor of future behavior.
So that's the first thing we actually looked at, and that's where the software really came in in terms of risk modeling.
So when we entered the space, only.
About 30 to 40% of the people.
Who applied to accept credit cards would.
Actually get through the system. We took that number to 99%.
And that's because we reframed the problem, we built credible models and we had this mindset of we're going to watch.
Not at the merchant level, but we're going to watch at the transaction level.
So come in, perform some transactions, and.
As long as you're doing things that.
Feel high integrity, credible, and don't look suspicious, we'll continue to serve you. If we see any interestingness in how you use our system that will be bubbled up to people to review, to.
Figure out if there's something nefarious going on, and that's when we might ask you to leave.
So the change in the mindset led to the technology that we needed to.
Enable more people to get through and to enable more people to access the system.