We tend to think of data in financial services in circular terms.
A 360-degree view of the customer.
This is such a common metaphor for thinking about data that A.) it would make an incredibly unsafe drinking game for those of us working in fintech and B.) it often confuses companies into believing that their end goal should be to acquire as much customer data as possible.
It shouldn’t. The goal isn’t to acquire data for data’s sake.1 The goal is to acquire data that can enable use cases that deliver value to customers.
We need a new visual metaphor. One that helps us understand the provenance and relative value of different data sources for different use cases within financial services.
Not a circle, but a waterfall.
What fascinates me about this view is the realization that, since the 1970s, we’ve been working backward to enable financial institutions to access this data in a programmatic, on-demand fashion.
We’ve been climbing up the waterfall.
Because of the way that programmatic data access has evolved in the financial services industry, some questions are more difficult to answer than they should be.
For example, over the last year, a critical question that banks and fintech companies have been focused on is what is the financial status of my customers? Obviously, COVID (and the associated public health restrictions) has had a significant impact on the financial status of consumers. Millions of people have lost their jobs, been furloughed, or had their hours cut back.
But how do you identify which of your customers are in financial distress?
It’s a tricky problem. You could look at delinquencies reported to the credit bureaus, but many consumers have been enrolled in loan forbearance programs and some lenders have abstained from reporting missed payments to the bureaus (at consumers’ requests). You could look at bank transaction data, which would get you closer to the truth. But even there, you get some confusing signals. Reductions in regular deposits might be offset by stimulus checks or unemployment insurance (both of which have been dispensed in a chaotic, haphazard manner).
The only fool-proof way of answering this question (and lots of other ones) is to look at payroll data.
APIs are Unlocking Payroll Data
Good news! We are starting to get programmatic, on-demand access to payroll data.2
A new generation of fintech infrastructure companies are building APIs that can facilitate consumer-permissioned access to the data held in payroll systems like ADP and Paychex.
Two trends are driving the emergence of this new category of fintech infrastructure:
Cloud. Much like bank transaction data in the late 1990s, API access to payroll data was only possible once the systems that held the data started to move to the cloud. Over the last ten years, legacy payroll system providers like Paychex (in trying to keep up with newer, cloud-native competitors) have moved to the cloud, which has enabled fintech infrastructure companies to start building on top.
Consumer familiarity. Every fintech company building APIs to access consumer-permissioned data owes a debt to Yodlee, MX, Finicity, and Plaid. The ubiquity of bank transaction data capabilities within B2C fintech apps has (as those apps have grown in popularity) helped familiarize millions of consumers with the process of giving a third party permission to access their personal financial data. It’s easy to forget, but 15 years ago this was a scary thing to do! Bank transaction data aggregators have made it feel safer, which gives payroll API providers a huge leg up.
For all the progress we’ve made though, it’s still very early. We’re just at the end of the first inning.
So, if we’re at the end of the first inning, what will the rest of the game look like?
I foresee three possibilities.3
Payroll system providers play ball.
A key difference between payroll data aggregation and transaction data aggregation is that, generally speaking, payroll API providers are not trying to empower a new generation of companies to compete with the established payroll system providers.
That’s not the case with Plaid and the banks.
Given this, payroll system providers should (in theory) be more willing to build direct integrations and business partnerships with payroll API providers than banks have been with transaction data API providers.
ADP and Paychex and the rest of them have an asset (payroll data) that they can and should want to monetize.
In fact, they already are. The dominant provider of employment and income verification services in the U.S. is Equifax, which sells a product called the Work Number. The Work Number is an extremely profitable and differentiated asset for Equifax, with coverage of roughly half of all U.S. non-farm payroll. Here’s Equifax CEO Mark Begor:
The Work Number database is Equifax's most unique and differentiated asset, particularly with the scale and currency of the database that can provide incremental value for our customers in today's challenging times, where there is so much income and employment uncertainty around consumers in the U.S.
It stands to reason that payroll system providers would benefit from more companies selling their data.
The challenge with this model is the inherent difficulty that fintech infrastructure startups like Argyle and Pinwheel will have in working with large legacy providers like ADP. On a technical level, building out an integration could take years, which would test even the most patient (and well-funded) fintech startup. On a business level, it seems likely that payroll system providers would insist on exerting a great deal of control over things like pricing and licensing in order to ensure that they don’t cannibalize their existing business with companies like Equifax. If you are selling income verification for mortgage lending to Equifax for $20 per transaction, you’re not going to agree to sell generic access to the underlying payroll data for $2 per transaction.
API providers keep hitting singles.
Alternatively, payroll API providers can focus on consumers and the fintech companies that are building payroll data-powered experiences for them.
This is the Plaid playbook. You sidestep the systems of record, via screen scraping, and focus on getting other companies to build really cool apps on top of your platform. The endgame is getting to a point of critical mass, where enough consumers rely on you to access their personal payroll data that it becomes untenable for incumbents (ADP, Paychex, etc.) to argue that the data (and the right to make money on it) belongs to them rather than to the employees.
If you are going down this path, you create stuff like an independent standards organization:
Payroll data is in disarray. Every payroll vendor stores, processes, and provides data to its clients in its own unique way. For an efficient system to operate with balance, this process should not be unique. Rather, there should be an established criteria that all participants abide by to level the playing field for workers.
Vendors who oppose the development of standards around the production and storage of payroll data have a motive. They don’t want to put in the work to fix their own systems. At Argyle we fix this. Just as the FASB has done with financial data, the OEDS provides a standard for the employment records.
But ultimately the pressure for change comes from the new, compelling use cases that the screen-scraped payroll data enables. Use cases like payroll-attached lending:
when loan repayments are pulled directly out of a consumer’s paycheck, called payroll-attached lending, it de-risks a loan significantly. It is akin to a loan that is securitized with a consumer’s income stream, or by factoring a consumer’s paycheck, rather than a true unsecured loan where the lender depends on the customer’s willingness to repay. This sort of “voluntary garnishment” can reduce losses for lenders and allow them to underwrite to a broader set of consumers. In addition, payroll-attached lending has the potential to reduce fraud, improve credit quality, and decrease charge-offs.
Plaid has run this playbook with great success, but it’s by no means easy.
First, screen scraping isn’t the ideal technical solution. There are legitimate concerns about data security, data accuracy, and performance and reliability. Additionally, when consumers are made aware of exactly what they’re agreeing to when they accept the T&Cs of transaction data aggregation via screen scraping, they aren’t super happy.
Second, and more importantly, reaching a critical mass of user adoption (both developers using your platform and customers using those developers’ apps) is really hard. Plaid, Finicity, and MX wouldn’t be where they are today if multiple waves of fintech founders hadn’t doggedly kept trying to make standalone PFM apps happen.4 The VC dollars funneled into building PFM apps and acquiring customers for them effectively subsidized the creation of the modern transaction data aggregation market.
What use case(s) will provide a similar boost for payroll data aggregation? My concern is that the top use cases that providers are currently focused on are either too infrequent (income & employment verification, direct deposit switching) or focused on areas that aren’t attractive to the majority of the market (payroll-attached lending is most valuable in subprime).
Employers get into the game.
Do you know who else might have good ideas for how to use payroll data to improve financial outcomes for employees? Their employers.
Employers are starting to take a broader look at their employees’ financial wellness. Here’s PayPal CEO Dan Schulman describing the results of a study on the financial wellness of PayPal employees from a couple of years ago:
In all of our call centers and among our entry-level employees—more than 10,000 people inside of PayPal—two-thirds of that employee base struggled to make ends meet. That was such a huge wake-up call for me
So Schulman took steps to make things better, spending tens of millions of dollars to lower the costs of employee healthcare, improve compensation, and provide financial education resources. And he’s happy with the results:
Employees were four times more engaged, and three times less likely to leave the company, … This idea that making a profit and having a purpose as a company are at odds with each other is fundamentally wrong. I actually think if you don't have a purpose as a company, you don’t see your workers as your most valuable asset and you minimize your profitability.
We’ve made substantial progress to increase the net disposable income of all our employees, and our work with Even will help drive further improvements. Together, we’ll help employees safely navigate cash flow challenges, stay on budget, build financial resilience, and reach long-term savings goals.
There are plenty of arguments for employers to embrace this “fintech as a benefit” trend — increased employee engagement, improved productivity, reduced attrition, lower costs, etc.5 However, convincing a majority of companies that these benefits are both realistic and worth investing in will be a major challenge. Not every CEO is as enlightened as Dan Schulman. Additionally, even a company that wants to make the investment will run into challenges in delivering “fintech as a benefit” (technical integrations, employee privacy & consent, etc.), especially if they are relying on partnerships with fintech companies.
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(Sourced from This Week in Fintech)
In-store is getting interesting
Affirm announced plans to launch a buy-now-pay-later debit card.
A new FIS study found that digital wallet payment volumes for in-person purchases eclipsed cash payment volumes for the first time ever in 2020.
Short take: Digital wallet payments overtaking cash for in-person transactions is a huge milestone and will mark the start of a new era of competition. E-commerce payment giants are already turning their eyes towards in-store transactions. Klarna offers a one-time virtual card for in-store transactions and now Affirm is rolling out a debit card (with BNPL capabilities) for in-store transactions.
Keeping track of BNPL
Basiq, an open banking platform, is introducing a new feature for lenders to aggregate outstanding consumer loans, including buy now, pay later debt, to get more visibility into customer liabilities.
Short take: According to research from Cornerstone Advisors, 43% of U.S. BNPL customers have been late with a payment and two-thirds of them said it was because they lost track of when the bill was due. Gaining insight into consumers’ use of BNPL, in the aggregate, and using that insight to help them make sound financial decisions is definitely needed.
Fixing the boring stuff
Self-driving personal finance startup Astra launched its automation platform. The platform enables banks and fintechs to let their customers create “routines” that move money to its most efficient use, and features no-fee 2-day ACH settlement.
Short take: Interesting fact — while the overall failure rate for ACH transaction is about 3%, that percentage can be up to three times higher for neobanks (due to, among other reasons, an inability to deal with fraud and return codes). This isn’t uncommon in fintech. Startups often struggle with the boring parts of financial services, but as fintech infrastructure (from providers like Astra) matures, the quality of consumer-facing fintech apps stands to dramatically improve.
Alex Johnson is a Director of Fintech Research at Cornerstone Advisors, where he publishes commissioned research reports on fintech trends and advises both established and startup financial technology companies.
It’s not actually oil! There’s no value in hoarding it.
Apologies for the terrible baseball puns in the next section. I couldn’t help myself.
“Gretchen, stop trying to make 'fetch' happen, it's NOT going to happen!”