‘A Cambrian explosion of products and services’: The rising importance of payroll data with Plaid’s Ben White

The first era of next generation financial companies focused on the bank account as the store of information and value for consumers’ and business’ financial lives.

That’s changing, as fintechs and data aggregators go deeper into payroll data and payments. The topic is becoming more urgent since the PPP rollout earlier this year.

Ben White from Plaid’s policy team has recently authored a report on the value of payroll data and he joins me on the podcast to discuss what payroll data access is, why it matters, and the opportunity it presents for future fintech innovation.

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The following excerpts were edited for clarity.

Opening up payroll data

It’s interesting to think about these developments as sort of a time lag behind where the banking sector itself has moved. In 2018, 80% of payroll providers offered an online portal, which is sort of a precursor to data connectivity. The legacy method of providing consumers access to their data was giving them a downloadable PDF statement.

But the reason that 80% number is so fascinating is because 80% of banks offered online banking in 2006. So, 12 years later, the payroll industry had reached the same level of online offerings that the banking industry had reached. That’s pretty good penetration.

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Now that that infrastructure has been built, there is the opportunity for companies like Plaid to step in and say, okay, you’re providing consumers this access to their data on a one-off basis. How can we layer on top of that, using the models that we built in the banking sector, to give them the sort of data connectivity that can allow them access to the full suite of fintech products and services?

Fintech use cases for payroll data

The way that we broke it down in the white paper was a view to the impact that fintech can have on consumer lives in general, and the way that fintech companies go about building their products. There are really two ways that they do this. The first is by digitizing manual processes. So, innovation in the sense of taking things that were once manual and making them simpler by digitizing them and providing that connectivity with data.

For example, if you are applying for a mortgage, and you need to download your pay stub in order to share it with your mortgage lender, there could be products and services that, leveraging data connectivity, allow you to do that in one click. A colleague of mine purchased a house earlier this year during COVID, when everything was more highly scrutinized. For lenders, it was hard to verify employment — if you’re employed this week, you might not necessarily be employed next week with what’s going on in the economy. They were hitting my colleague up once a week to provide her employment verification. So every single week, she had to log into the payroll provider that we use, download that pay stub proof of employment and upload it to the lender. That is a pretty tremendous pain point in a consumers life to have to do a task repeatedly again and again.

The second element, which I think is even more exciting, is once you’ve opened up that space for connectivity to exist, you can really lean into customization. Looking at the credit space where I think this is really compelling: you can do things like cash flow underwriting for lending. Those types of models are still being built and continue to get better. The types of data that you can pull in from a consumer’s payroll helps answer how much they are contributing to their retirement accounts. How much are they putting into their FSA or their HSA? These are all really, really valuable data points for lenders who want to do things from personal loans to auto loans, all the way up to a mortgage loan.

Payroll companies rolling with the times

Plaid, and many companies like Plaid, have been operating in the banking space for a while. We’ve continued to get better and better about collaborating with data holders. We announced last week that our intention is to have three quarters of our traffic onto APIs by the end of next year.

What sets payroll apart from mainstream financial institutions is that they’re not already offering these products and services. There’s not really the competitive tension there for them. In fact, it’s really a pure value add. If you think about payroll as primarily a business to business model, they’re competing on features and on things like customer service, and how well they can meet the needs not just of the company that they’re providing services to, but increasingly of that company’s employees, as well. We’ve even seen some of the larger and more innovative payroll companies stand up some of these services in house.

Plaid has worked with Gusto to stand up some of their services like a mobile wallet to the employees of Gusto’s customers. Companies like ADP are offering a third party marketplace where it’s not just the B2B model, but increasingly a B2B2C, where the end user, the employer, the employee, at any company that’s using these payroll providers can have access to a much broader suite of services than might otherwise have have initially been offered. Payroll companies really stand to benefit by differentiating themselves.

Next generation fintech built on payroll data

What I find so exciting about my work is being able to look out at the policy horizon at changes that, if we were to establish this sort of data connectivity, could set off another sort of Cambrian explosion of products and services.

Parallel providers and employers themselves are recognizing this is where consumers’ financial lives begin. And if we want to give consumers not just sort of the full picture of their financial lives, but also position them in the best way to make the best decisions with all that information, then it’s really the best place to get people going with their finances.

From a policy standpoint, open finance describes a world in which consumers have access to all of their financial data, regardless of which institution it sits. So payroll is just another layer on top of that, where the combination of payroll data, in addition to things like transaction data, can become that much more powerful.