Hispanics are an emerging American economic force, and demographic data shows they will be so for decades. Tricolor founder and CEO Daniel Chu has a plan to serve them.

According to McKinsey, Hispanic financial services revenue will triple from about $90 billion to $265 billion by 2030. If the more than 60 million Hispanics in the United States had their own economy, it would be the eighth largest in the world. world. Over 80% of workforce growth is accounted for by Hispanics; by 2060 they will represent 30% of the workforce. Their average age is three decades younger than that of whites.

(Chu stressed that this is not a border issue. The average Tricolor customer has lived in the United States for 15 years.)

Despite being at the bottom of the labor hierarchy, or perhaps because of it, Hispanics have weathered the pandemic in decent conditions. Chu said they benefited from the supply imbalance, emerging with higher incomes than before COVID-19. They are resilient, and with an average family size 2.5 times larger than that of non-Hispanic families, there are natural safeguards against collapse.

The lack of solutions facing Hispanics

The American economy has been slow to respond. Over 50% of Hispanics are dissatisfied with their financial services. A third party cannot access affordable credit.

“Hispanics are closing the income gap with the white population in the United States,” Chu said. If you look at overall educational attainment, Hispanics are perhaps 15 percent behind, but white family wealth is six times greater than that of Hispanics.

“So the real key is that Hispanics need to participate in homeownership. This is how the low-income population can ultimately accumulate wealth, and this fits our business perfectly. About 60% of our customers who don’t have a FICO score, don’t have a Social Security number, we can build a credit score as a result of our financing.”

The tricolor has thrived during the pandemic

Despite challenging economic times, Tricolor has seen annual growth rates of 40%, with 2024 revenue projections of $1.3 billion. Losses did not explode during the pandemic. Chu attributes this to Tricolor’s customer moat.

“Everyone else is chasing the same general market consumer. Once again, we are addressing a consumer who has this vast competitive moat around him,” she explained. “All the other models are really commoditized models, and their commodity is capital, the commodity is FICO data, and they have no ability to distinguish themselves.”

Tricolor’s technology is not proprietary, but Chu does not share it. Exclusivity and the 45 million unique data points that Tricolor has correlated over the years are key to its success, driving profitability from day one.

Philosophy also played a role. Chu said Tricolor has moved risk to the top of the funnel by using technology to segment early. This increases lead generation and improves underwriting.

The traditionally adverse relationship between car dealers and lenders drastically improves. Dealers seek profit maximization, while lenders want to underwrite a good loan.

“Because we have an integrated model, we can align marketing and risk,” Chu said. “We can use our data to say that this combination of attributes will score well and perform well. You can push them through social media with Facebook or other digital campaigns and we can work with clients who we know will perform.

“So, unlike the traditional model, where dealer and financier are adversarial, we market to customers who we know they want to finance. We align sales and marketing with risk and subscriptionand that is a powerful dynamic.

Alternative data improvements

“If we can segment that customer early and give them an offer, giving them an idea of ​​what they can qualify for early in the process, their chances of successfully moving through the funnel will increase.”

Advances in alternative data interpretation have aided this process. Two years ago, Chu said there was no benefit. Today there are multiple sources, even for customers outside of bank offices, which have a correlative value and can reduce fraud by up to 20 basis points.

Considerations on artificial intelligence

Chu’s biggest concern with AI is maintaining data integrity. All data incorporated into models must be collectible, verifiable and validated. Tricolor only uses previously validated data in credit decisions.

It is a successful method approved by regulators. Chu said they want to see vulnerable consumers like Hispanics have access to more and better financial services.

It’s best to stick to simpler bets, those with enough general data to help predict performance.

“We have been more consistent than any other issuer in subprime auto loans over the past four years,” Chu said. “This speaks to our ability to validate our model. If you don’t perform constant model validation in an unstable environment, you may be subject to some unintended consequence of a trend that everyone else misses.”

One such example is the masking effect of pandemic stimulus and tolerance. Chu said Tricolor conducted constant validations of the models that suggested they were on target.

“When we did model validations during the lockdown, we asked customers how many people lived in their household,” Chu said. “I mean, I don’t think this question is about a credit app, but we could see a big correlation. So we thought about it a little more.

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  Tony is a long-time contributor in the fintech and alt-fi spaces. Twice named journalist of the year at LendIt e winner in 2018, Tony has written more than 2,000 original articles on blockchain, peer-to-peer lending, crowdfunding, and emerging technologies over the past seven years. He has hosted panels at LendIt, the CfPA Summit, and DECENT’s Unchained, a blockchain expo in Hong Kong. Email Tony here.

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