The Real Revolution is in the Data, Not the Hype
The promise of embedded finance, especially as it’s delivered through vertical SaaS (vSaaS) platforms, is seductive. The basic idea – specialized software handling core business operations, then seamlessly offering financial services – makes intuitive sense. We’re talking about platforms like Boulevard for salons, Slice for pizza shops, Housecall Pro for home service pros. These aren't just generic tools; they're purpose-built. And that specialization, proponents argue, unlocks access to better financial products.
The core argument hinges on data. vSaaS platforms, unlike horizontal solutions like QuickBooks, capture incredibly granular, real-time transaction data. "At their core, they are point-of-sale systems," the article states, "taking payments. Which means they have access to the most valuable thing of all: live, transaction-level business data." It's this "contextual data" that supposedly allows these platforms to offer tailored financial services that traditional banks can't match. The claim is that insights gleaned from daily operations like scheduling, inventory, and customer interactions provide a "nuanced picture of an individual business," leading to better credit decisions and more relevant financial products. As explained in Contextual Banking: How Vertical SaaS Cracks the Code of Embedded Finance, this nuanced picture is the key to unlocking embedded finance.
But let's pump the brakes for a second. Access to more data doesn't automatically equate to better financial services. It simply means access to more data. The crucial question is: how is this data being analyzed and translated into actionable financial insights? What algorithms are being used to assess risk? What's the default rate on loans originated through these platforms compared to traditional bank loans to similar businesses? These are the numbers that truly matter, and they're conspicuously absent. (I suspect because they are either not being tracked, or the people who track them, don't want to share).
Digging Deeper: The Black Box of vSaaS Finance
The article highlights Boulevard, a vSaaS platform for salons and med spas, as a prime example. It correctly points out the breadth of data Boulevard collects: payments, client booking, scheduling, customer communications, and marketing campaign data. All of this is true and it’s impressive. But the leap from data collection to superior financial service is a considerable one. What specific correlations have they identified between, say, customer loyalty program participation and loan repayment rates? What predictive models are they using to forecast revenue fluctuations based on appointment scheduling data? These are the questions that need answering, not just the assertion that they have a "nuanced picture."
And this is the part of the analysis that I find genuinely puzzling. The article emphasizes the "virtuous cycle of engagement and loyalty" that vSaaS platforms create. But isn't that just marketing speak for "we've locked customers into our ecosystem"? While customer loyalty is undoubtedly valuable, it doesn't inherently translate to lower risk for financial products. In fact, it could create a situation where businesses become more reliant on the platform, making them more vulnerable to economic downturns or changes in consumer behavior.
The implicit assumption seems to be that vSaaS platforms possess some kind of proprietary, unreplicable analytical advantage. That they're somehow able to extract insights from this data that traditional banks, with their armies of data scientists and decades of experience, can't. That seems unlikely, at best. Banks have access to different data sets, including credit scores, payment histories, and macroeconomic indicators, which provide a broader and perhaps more reliable picture of a business's financial health. The vSaaS data is highly specific—hyper-specific, even—but specificity doesn't always equal accuracy or predictive power.
The Illusion of Insight
The danger here is the illusion of insight. Because vSaaS platforms have access to so much operational data, there's a temptation to believe they have a superior understanding of risk. But correlation does not equal causation. Just because a salon uses Boulevard to manage its appointments doesn't mean it's automatically a better credit risk than a salon that uses a different system. It simply means it uses Boulevard. The platform could be just as easily amplifying existing financial vulnerabilities as it is identifying hidden opportunities.
Ultimately, the success of contextual banking hinges on transparency. We need to see the data behind the claims. We need to understand the algorithms, the risk models, and the actual performance of these embedded financial products. Until then, the "revolution" remains more of a marketing pitch than a data-driven reality.
So, What's the Real Story?
The promise of vSaaS and embedded finance is intriguing, but the lack of hard data is deafening. Until we see the numbers, it's hard to see past the hype.
