The Green Finance Podcast Ep. 6: The fight against financial discrimination with BetaBank founder Seke Ballard

Last week, we wrapped up our first Banking on the Planet conference – we had a great lineup and it was really a lot of fun. If you missed it, we uploaded all the session videos on Tearsheet’s YouTube channel, available to watch for free. 

And now, we're on to our next event, this time finally in person! We are holding Tearsheet's Power of Payments Conference on September 15th, 2022 at Current, Chelsea Piers, NYC.

We will bring together the top professionals and brands in the payments space to discuss the challenges and opportunities presented by an undeniable need to stay ahead of the curve of a rapidly changing landscape. We have a great lineup as well, so make sure to check it out here.

Moving on to today’s podcast episode, we are talking about financial equity and how today's system is simply still discriminatory. 

According to US law, lending discrimination occurs when a lender makes a decision during the loan application process based on a person’s race, color, sex, religion, familial status, nationality, age, receipt of public assistance or disability. 

Although fair lending laws are designed to protect borrowers from financial discrimination, it still happens – many people and businesses are treated differently, even in today’s technological world. A disproportionate majority of those refused capital in traditional banks are historically underrepresented and underserved groups. 

And sustainable finance means inclusive and non-biased finance, allowing equal opportunities for everyone, which is why I want to explore this topic today, especially with my guest Seke Ballard, who's got so many stories and experiences about this to share with us. Seke is the founder of BetaBank, a digital Black-owned bank built to serve SMBs equally and fill the gap left behind by traditional banks.

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The following excerpts have been edited for clarity.

Discriminatory practices are embedded into the current system, so you decided to build BetaBank to serve small to medium sized businesses with a mission to provide fair, accessible, and cost-effective deposit and lending services. How did you reach that mission?

Seke Ballard: I reached it through tragedy. My entrepreneurial journey began the summer of 2015, when a guy named Dylan Roof went into Mother Emanuel AME Church in Charleston, South Carolina, sat with the church corps for an hour before standing up and opening fire, killing nine innocent people in their place of worship. My mother's side of the family, they trace their roots to Charleston, South Carolina, Charleston and Georgetown, which are adjacent cities. I grew up in Wilmington, North Carolina, which is just a stone's throw away. And so, this hit pretty close to home for my family. My dad suggested that we take a road trip to the church to pay our respects to the victims. I was living in Seattle working at Amazon at the time, so I got on a plane, went to Wilmington, and we embarked on this 10-hour road trip. And the question that animated the majority of that drive was me asking my father, how did we get here as a country? My view was that we were regressing. We weren't taking steps forward. We weren't taking steps sideways, we were taking steps back.

My view is that democracy is fragile, that the society we live in is fragile, and there's absolutely nothing that stops it from regressing to becoming something different than what it is today. So frankly, I was afraid. And that's where my concern was coming from. That's where the question to my father came from. His answer to that question turned out to be pretty foundational for me. He said, African Americans (and really, you can create some brackets and insert any marginalized group of people but for the purposes of the question I was asking, African Americans) as a matter of pragmatism cannot expect to sustain social and political advances unless those social and political advances are built on a firm economic footing, and he believed that African Americans had not yet obtained that firm, secure economic footing. He also believed that this was the explicit unfinished work of Dr. Kane when he was assassinated during the Civil Rights Movement.

My father owned a pulp wood logging company, so people would pay him to clear commercial and residential property of the lumber. He would then take that lumber and sell it to the local paper mill. That was his business. That's how he fed our family. That's how he supported a number of families in our community. It was a successful business in North Carolina, and he wanted to grow this business to surrounding states. But he built it from scratch with hand-me-down equipment. He needed to invest in new equipment to be able to expand the business, so he went to a number of banks in the area, applying for loans. And he was denied not once, but 13 times. His view was that these denials had absolutely nothing to do with his business's capacity to take on and service debt. Instead, it had everything to do with the color of his skin. And I thought that this was an incredibly interesting claim.

The reason I thought it was an interesting claim is because I, as a student of business, understand very intimately the role banks play in an economy. They are absolutely central, I think of them as I think of the heart in a body – the heart is how blood is distributed throughout our body, if blood for some reason stops circulating to a limb, that limb atrophies, it dies. I believe the same thing is true for communities where banking is not present, or where banking is not offering them access to capital to be able to purchase businesses, grow businesses, purchase homes, etc.

When I went back to Seattle, I did some research on my father's claim and found that he'd hit the nail right on the head. If I go into a bank (for your listeners, I'm a black guy), and a white guy goes into a bank, and we have the exact same financial profile, same balance sheets and income statement, we are the same person apart from the color of our skin, I am 2.7 times more likely to be denied this loan. In the event that I receive it, I'm going to pay on average 180 basis points more in interest. Now, this research is from the Federal Reserve, this is the central bank in America saying this is a problem that we observe with respect to banking nationwide and that basic dynamic in terms of likelihood of denial, and paying more in interest. That's true across all forms of debt capital, whether you are applying for a business loan, a mortgage, a personal loan, a car loan, doesn't matter. It's true to varying degrees. It's also true for women, it's true for immigrants, it's true for poor working class white people. So there's a lot of intersectionality with respect to how banks are failing to serve small businesses across the nation. And my view is that this was a solvable problem.

Financial equity is a huge problem in the US – the system has racism and bias built into it, as you described, and perhaps we hoped that technology would alleviate that problem because it’s perceived to be unbiased, when in fact a lot of the times it’s just mirroring the same bias over and over again. Algorithms attempt to simplify things, to generate insights from data, but they can’t attach meaning or value to that result. That’s for actual people to decide. How did you navigate that equation?

Seke Ballard: I have maybe two responses to that. My finance professor in business school would always tell us, "Garbage in, garbage out," when building financial models. And what he meant by that is, if your assumptions are garbage, then the output of your model is going to be garbage. When training any algorithm, you are using data that is generated through human activity, and that data often reflects the bias of that human activity. So if you are not intentional about rooting out that bias in the human activity, then the output of your model is simply going to be the same thing that humans do, except it's going to be a black box, and no one can really tell what's happening in that black box.

We were really intentional about what factors we use to train the model and what factors we excluded from training the model. And for that reason, we have a high degree of confidence that the output of the model is not reflective of the sort of biases that you would have seen in that human-generated data. So that's part one.

Part two is that financials tell a story – you made the point about meaning and whether algorithms have the capacity to attach meaning. In this case, I think meaning is attached to it, because I believe financial statements tell a story. I can look at your debt utilization over the years and understand how that debt utilization has played a role and the operations of your company. If we rely on technology and data to understand the financial and operating profile of a company, that analysis in and of itself tells the story. And so what we try to do is leverage data and technology to gather information and to analyze that information, but we don't rely exclusively on the technology to decision alone, we are too new to rely exclusively on technology to decide it. So there will be a BetaBanker that is looking at that analysis, and ultimately deciding that loan. But really, the key is taking that first part of data aggregation and analysis, taking that from the banker, and really relying on technology to perform that analysis, and use the banker to evaluate the output of the algorithm. That, to me, is really what puts everybody on a level playing field.

So if you're a business owner from Gary, Indiana, for example, which is an economically troubled city, often overlooked with respect to banks and credit, and you're applying for a loan with BetaBank, that means you are telling us, what is your business's financial and operating profile? How that technology assesses the inputs is for that business in Gary, Indiana, is exactly the same way it would assess the inputs from a business applying from the loop in Chicago. If you're unfamiliar, the loop is the central business district in Chicago. So both of those businesses are now on equal footing with respect to the application and the analysis of that application. And so in this way, I think our approach to lending not only levels the playing field, but it allows for us to have a thorough picture analysis of that business, no matter where that business is, no matter who that business is run by.

It's really awesome and exciting to see folks like you thinking about using technology and data as a tool to help small businesses develop, especially in poorer areas, where that sort of a financial stimulus could really help build some momentum economically. But we’ve had these tools, like technology, data, algorithms, for a while now, and they built the unfair system we have to deal with today. So how can we make sure that technology doesn’t hinder us from creating an equitable banking system?

Seke Ballard: I was speaking to a colleague a few days ago, and she reminded me that the Community Reinvestment Act was passed 50 years ago, which is a piece of legislation that was introduced and passed to solve the problem of discriminatory lending, and we are still fighting the impacts of discriminatory lending.

Big banks across the nation are making 100 million dollar settlements with the Department of Justice, for discriminatory lending, Wells Fargo being a great example. And so I think your question is exactly the right one. How is it that we're still having the same discussions after so many efforts to address it, whether those efforts have been the regulatory framework, or whether those efforts have been the introduction of new technologies? And I don't have a great answer, to be completely honest, I don't know that there has been someone motivated in quite the way that I'm motivated. But here I am, I'm building this bank with the intention to solve these age-old problems in a small way. We will be a $250 million bank, that's a drop in the bucket. But I think, as our model grows, and hopefully becomes more ubiquitous, we can start to see that kind of change.

The last thing I'll say on it is that I believe market pressures are real. Whatever your opinions of capitalism are, I think the creative destruction that happens with capitalism is valuable. The reason I mentioned that is because the model that I'm building, I believe it is an incredibly scalable model. So as we attract more small businesses to bank with us, these are small businesses that either don't have a prior banking relationship, or they do have a prior banking relationship. And for those customers that do have a prior banking relationship, you can bet your bottom dollar that the bank they're leaving to come to BetaBank is going to take notice of the fact that they just lost a customer to BetaBank. And it's that process that I hope will force broader change. So if you have a model that is superior to the existing model, and superior particularly in its ability to generate profit and reinvest in the growth of that model, I think there are only really two choices for the old model. Either you adapt, or you die. Those are the two options available to them. And so when I look at the trajectory, and I'm not talking about one year, two years, I'm talking about 20 years, 30 years, 40 years. When I look at the trajectory, I hope that BetaBank can be the catalyst to that level of change.