Imagine that you’re running a restaurant. It’s busy – there are different customers every week! But, you’ve got a good handle on your operating costs including rent, utilities, payroll, and insurance. You’re also aware of the inflows from food and beverage sales. Cashflow is well understood, standardized, and documented for businesses like these.
But what does cashflow mean for a person?
For an individual, it’s a lot murkier. Some basic questions:
- Does a secondary part-time consulting job that gets deposited via Zelle count as income?
- Is pet insurance an essential expenditure?
- How many expenses are regular or expected like utility bills vs. one-time expenses like an emergency doctor’s visit?
All of this context is buried across many different systems and thousands of row-level metadata that’s usually very messy, fragmented across different accounts, and hard to analyze.
The data’s there, but the infrastructure isn’t.
Let’s take a look at a specific example of how analyzing the cashflow of an individual comes into play.
Meet Maya, a 40-year-old Registered Nurse living in St. Louis, Missouri. Her primary checking and savings account is with Wells Fargo.
As a nurse, Maya’s work hours are in flux – some weeks she gets some additional shifts. She gets a direct deposit from her employer every two weeks, but the amount fluctuates. Banks and other lenders can see “flexible” schedules as “unstable” when performing a risk assessment on a mortgage or other type of loan, leaving Maya with few options to get access to credit when she needs it.
As a consequence, she isn’t being offered the best financial services to meet her needs.
This was the impetus for her to explore fintech solutions that take into account the context around her personal cashflow and financial profile. In the example below, we can see that her data is sitting across many different systems that each hold unique information about her financial situation.
The fintech apps she uses are a part of her daily livelihood.
- Maya maintains her primary checking and savings accounts at Wells Fargo, but finds it difficult to keep track of her income and expenses on a daily basis.
- Maya was swimming in credit card debt after an emergency car repair set her back on her payments. Her friend pointed her to Plannery, a credit app specifically designed for nurses and physicians. Plannery understands that a nurse’s job security is almost guaranteed due to the nursing shortage, and is able to offer nurses a debt consolidation option that is uniquely catered to nurses.
- Maya uses a digital bank called Lume which is also designed for nurses and offers special discounts and early payments.
- She manages her student loan payments on Lume via Payitoff, which also helps her see if she qualifies for reduced payments.
- Maya connected her bank data via Plaid and Ocrolus to Monarch Money, a personal financial management app that helps her track her spending, savings and investments.
The above is still only a fraction of the complexity of Maya’s financial life.
Why this matters
So why is there so much value in being able to get a complete picture of Maya’s financial profile?
Consumers today expect instant wages, transfers, liquidity, and credit decisions.
Like many consumers, Maya expects speed, convenience, and personalized offers for financial services when she needs them. She’s among the 60% of U.S. workers who want to get early access to their paychecks. She expects that apps will use the information she’s trusted them with to provide personalized and instant financial services like a financial plan optimized for her situation, loan offers, and help with managing her spending between paychecks.
All of these expectations require each fintech app she’s using to have a detailed understanding of Maya’s financial life.
The cost of acquisition for financial services is high
Acquisition costs are one of the biggest challenges for any lender. Today, companies spend millions of dollars buying targeted lists from the bureaus in order to identify people with an inclination to take on new credit. In 2020, fintechs in North America spent $985 million to acquire new customers.
Meanwhile, these companies are sitting on treasure troves of financial data that may contain signals around their customer’s willingness and ability to pay. However, they struggle to leverage this data due to difficulties in data cleaning and analysis in order to generate customers’ insights.
A growing number of consumers are underserved by FICO and traditional sources
The demographics of our country are changing. We have a growing immigrant population, and more people have multiple sources of income fueled by the creator and gig economy. In fact, 36% of the total U.S. workforce does freelance work. Minority groups as well as younger generations have inherent distrust in the traditional credit system. To put this into perspective, 57 million Americans are living with subprime credit. These consumers are left out, and a rapidly emerging fintech ecosystem is reinventing how new products are designed for underserved consumers.
Consumers are using more financial services
As more fintech players are joining the playing field, consumers are subscribing to more services to help them manage their financial lives. However, juggling multiple accounts can become burdensome. Late payments and overdrafts are just some of the factors that hurt consumers as a result of managing multiple accounts. Losing track of a bill due date was the reason behind 66% of BNPL users who had a late payment. As for overdrafts, half of Millennials with more than one checking account overdrew in 2020.
Solving the issue of understanding the complete picture of a person’s financial profile benefits both a financial service provider, as well as the end user. When a fintech company or bank can better understand a user’s financial profile, they can reduce their risk, approve and onboard more customers, as well as offer additional financial services to existing customers.
With a more comprehensive view of the customer, fintechs can help individuals understand their own financial profile, like how likely they are to default and when, and what specific actions they can take to improve their financial health.
How does Pave solve this?
For every company building a financial service, it’s a major effort to get a complete and accurate understanding of their customers’ financial lives. For the past 25 years, FICO has created and standardized scores built on credit bureau data. Today, the massive increase in data sources calls for the development of new infrastructure and standards for evaluating an individual’s cashflow and financial profile.
Rather than reinvent the wheel, Pave is building a solution to standardize how everyone views the cashflow and financial profile of a consumer.
We’re making it possible for developers and data scientists to connect all of their disparate data sources to Pave and get back a unified view of the end consumer’s financial life in order to provide increased access to credit and personalized financial journeys.
Check out our use cases for:
Contact us here to learn more about how you can use Pave’s Cashflow Insights