Argyle’s powering complex banking decisions with employment data

People have much more control over their personal financial data than they realize. Younger companies are beginning to be more educative in that regard, creating ways in which people may feel more in control of their data. Argyle puts consumers’ payroll data in their hands, enabling them to attain better financial products and services.

“For an individual, things like where I work, how much money I make, and when I started working there, are core to who they are. And big businesses have been built on top of selling that data, often without consumer permission,” said Billy Marsden, COO and founder at Argyle, at Tearsheet’s DataDay Conference last week. “We believe that individual workers should be able to permission this data to where they believe it should be used and have control over that information.”

The first question that pops up in one’s mind is whether companies are even allowed to share their employees’ data without their permission. Well, yes, kinda, but it's not straightforward — it never is. Oftentimes when one starts a new job, they are given a bulky terms and conditions document to sign before they can start. Most people don’t really read them thoroughly, and when they sign off on them, they might be agreeing to grant their employer or a certain data processor control over their employment data. In the coming years, however, this practice will change, as the awareness about financial data privacy increases.

Having said that, employees did always have access to their data. A simple trip to HR would grant them access to things like a payslip and an employment certificate, which they can then send to whomever they want. Those processes were bureaucratic, lengthy, and created files worth of paper documentation. With today’s technology, however, those analog processes have been made simpler and more straightforward. In the digital realm, with  API and JSON formats, employees can get access to the entirety of their employment data on their phones, whenever and wherever they want. And with another click they can send it out wherever they wish — all verified.

Employment Data and Banking Decisions

Employment data serves a variety of purposes in decision-making for financial institutions. In lending situations, for example, such data is used to gauge the stability of an applicant’s financial standing. Today, with a wide variety of data points available and fully integrated into the ecosystem, the relationship between data and decision-making has become deeper.

Talking about lending decisions, in particular, Marsden found it helpful to divide how data is used into three buckets. The first bucket, he attributed strictly to compliance. Lenders need to make sure an applicant really is employed where they claim to be employed, even if just to check the box. 

The second bucket is a bit more complex. Here the purpose is not just to check a box, but also to gauge an applicant’s financial position. In the world of mortgages, originators often work with GSEs and are required to verify income and employment under a federal mandate. So they must verify that an applicant makes a certain amount of money for the loan to be underwritten. And this can get more sophisticated as the credit in question becomes larger – for instance, a mortgage originator will look more in-depth at income data than a provider of unsecured personal loans would. So the middle bucket is just income and employment verification.

The third bucket is where the new tech is really put to use. Innovative lenders are using their access to a variety of data points to really take decision-making to the next level.

“We're seeing some more sophisticated lenders starting to incorporate more detailed information into underwriting criteria. And this wasn't really possible before if you think about what sort of income and employment data a lender might have. We talked about the pay stub, they had one piece of data that [just] said I got a pay stub on this date, and I made this much money,” Marsden said.

It is really not surprising that lenders are getting creative or using this information to their advantage.

Argyle, for example, shows users access to a stream of their employment data, where they can review detailed data points. They can even generate a JSON for every paystub they’ve ever received working for their employer, all digitized. Some lenders, however, are getting more creative.

One of Argyle’s customers, a lender, decided they want to use the hiring date of an employee in deciding to lend them money and how much. While they had the data they needed for income and employment verification, these new data points helped them decide whether the applicant is reliable or not and whether they’ll actually be able to repay the loan or not. Marsden says that data from Argyle’s clients suggests there's actually nothing more predictive of the ability to repay than how long an applicant stays employed.

Additionally, new payroll technologies are helping lenders reduce costs, as margins get tighter. Streamlined and digital access to employment data helps them reduce reliance on call centers. Call centers are expensive in two ways – the first is obviously the cost of hiring for and maintaining one, and the second is inefficiency. Lenders relying on them are slow to review applications and consequently slow to respond to them — and that’s money. Just two days down the line, the applicant may even forget that they applied for a loan with a particular lender. The lender loses more customers, and that causes its acquisition costs to rise.

Payroll data brings more general benefits, too. 

“I think from a user experience perspective, what we see with our customers is it creates trust,” Marsden said. “‘Hey, you're gonna pass me this information, and here's how I'm going to use it’ just sounds a lot better than ‘enter your social security number, and we're going to ping some data brokers and see what we get back.’”

Consumers are beginning to catch on — they want to know with whom their data is being shared and what it’s being used for. Consumer-permissioned data builds trust with users from a user experience perspective.

API-based access also allows for quicker decision-making and instant verifications in processes like lending originations. This is what has enabled same-day funding or instant funding on a product. Otherwise, an applicant may have to wait for days, especially if the lender is using legacy employment verification systems. 

A look at the future, and where Argyle is headed.

Adoption, already growing, is expected to grow over time.

“Last year, there were some early adopters, and now this year, and, most venture-backed lenders are changing how they're accessing payroll data with Argyle,” Marsden said. “And I think the next step from here is crossing the chasm — a wide-scale adoption for this specific income and employment verification product.”

Furthermore, Argyle has begun to think of itself as a platform business, as clients continue augmenting their products and building new use cases on top of them. An example of these use cases is insurance products, where the company’s offering is being used to amp up income insurance. Gig workers’ compensation insurance is being underwritten based on how many shifts they’ve completed for, say Uber or Lyft, and when they completed them.

The primary focus for Argyle in 2022 is to build coverage and connect with more companies. They want to make it easy for anybody, regardless of their type of work, to verify how much money they make. This means going beyond Fortune 10 and other enterprise employers, as people are increasingly making money in a variety of ways.

“The industry is fragmenting, not consolidating. We want to be able to make it easier for somebody who makes money on Tik Tok or YouTube to be able to verify that, so we've built out coverage into those creative economy platforms,” Marsden said.

Secondly, the company wants to make it easy to verify income and employment by bringing together different functionality into a single platform. Currently, Argyle is like one tool in the chest, but not the only one. Their customers use multiple other services to fulfill different needs. That could be OCR or uploading documents that could be using the credit bureaus and repurposed datasets. And the firm wants to be the place where users can do all those things, where they can set up rules and orchestrate how they manage their income and employment data.