Challenger Bank Klar, Overcomes The Pandemic With A Unique Approach To Credit

Can you provide us a short background on Klar and what makes Klar different from other providers?

Klar is a Mexican challenger bank working to democratize debit and credit in Mexico. We offer a 100% digital, transparent, free, and secure alternative to traditional debit and credit services. 

After raising $57.5 million in debt and equity seed funding, we acquired over 150,000 customers over the past few months.

What makes us different?

First, we have a different product offering. On debit, we offer one of the best accounts in México: a friendly app, no charge or commission on any transaction, and cashback on all purchases from 1- 4% (we are the only company offering cashback on a debit account).

On credit, we've developed a unique credit product that doesn’t take into account traditional data sources (FICO score). It only focuses on real-time customer behavior.

Second, we do not depend on 3rd-party enablers. We are proud to be the only fintech in Mexico with its own operational Mastercard primary license, our own core banking ledger, and our own regulatory charter (fintech license). Klar is also the first fintech in LATAM to be processing the last mile to the switch with Galileo, a world-class processor serving 90%+ of the fintech market in the US.

Third, we bet on the team. There is no doubt that we've assembled one of the best teams in LATAM, capable of building and operating a real bank. We have a 25+ engineering world-class tech team in our Berlin office, and our management team has relevant leadership experience in many successful organizations. That allowed us to reach operational excellence quickly: our NPS today is at 80%, three times better than the best local banks.

How has COVID-19 impacted your business and what has been your response?

We saw the pandemic as an opportunity to focus on our core product: credit. During this period of time, we’ve tripled our credit balance and registered our highest historical repayment rate in April. 

Our credit risk model is unique. It does not rely on traditional public data sources (FICO), instead we leverage real-time debit customer behavior from our debit product to underwrite credit. This unique machine learning model is more predictive and adaptable to conjuncture changes like COVID-19.

Has your product roadmap shifted due to COVID-19, and how?

Not really, we've kept the focus on product and customer experience first:

• We've improved the whole customer experience with a brand adjustment

• We've redesigned our onboarding process to increase our growth potential

• We've achieved regulatory and operational independence with our own Mastercard license and Galileo integration (April 25th!) 

• On productivity, our engineering team has been delivering products ahead of timeline

What type of opportunities does LATAM offer that we wouldn't see in other markets?

We are convinced that LATAM is the next big thing for fintech: it's the last remaining huge digital customer base with extremely low financial penetration. For instance, Mexico has a population of over 120 million, only 50% of adults have a bank account and only 15% of adults have credit cards (vs. 32% in Brazil at a similar GDP per capita). Despite the low penetration, big global banks make most of their money in Mexico due to a high commission structure and over-serving a small population segment.

However, smartphone penetration is above 100% of population… for example, Mexico is one of the top three global markets for companies like Spotify and Uber, and customers still don’t have a debit or credit card to pay for them.

Klar is well positioned to take over that opportunity, and that’s why Klar’s operational independence is so relevant. There is no alternative: challenger banks would need to build the full tech stack to seriously challenge the existing banking ecosystem. 

What is the long-term vision for Klar?

Transform the way Mexicans think and interact with their money.

What do you see as your plan going forward?

We’re a company that has been a provider of data, and that is at the core of what we do. I think the opportunity is for us to help our customers in a more intelligent way going forward, so that they can achieve their goals. We always want to be thinking in terms of customer outcomes.

Someone put it this way when I was working at my last company. They said, “You know you guys have tons of big data. The problem is making that big data into skinny meaningful data that we can use in the moment.”

Our customers do want to buy data from us, but in reality, what they really want is answers.

And what does that mean, to be thinking of customer outcomes and to be providing answers?

Customers want to know where to focus with data. So, depending upon the use case, we want to become a data management company from a platform point of view and continue to add value and enrich the data.

Increasingly, at the top end of the market, some of our larger customers are hiring data scientists, statisticians, and modelers to build out predictive models to tell them where they should focus their outbound efforts. Here's an example: You're a large asset manager, you've launched an annuity fund, and you want to make sure you're hitting the West Coast. You think that's viable, and it's most appropriate within your type of distribution mechanism, retail brokerage environment, or registered independent advisors. You build a model that says, “Okay, if this is what we're looking for, how do I focus my marketing?” And as data comes through that model, you can adjust your marketing plan.

And we're starting to talk to customers about how we can help them do exactly that. Because while the large firms, all the household names, have the resources to employ 10+ data scientists, the middle market segment does not have this capability. And it’s a big segment. We think we can help there.

We see a future opportunity where we develop diagnostic or analytical packages that can help all customers get to the answer faster and can automate their audience targeting. 

If you're recruiting, you can look at things like the propensity of a team to leave their firm and various attributes that make the most sense for you given registrations, licenses, and your hiring criteria. It means building predictive models so that as advisors move from firm to firm, you can get alerts that allow you to go and target them.

That's what we mean by a model-driven digital audience targeting. We can put together a package to help you with your hiring, distributing products, or running conferences.