David García Aceves: Startup Story, Funding & Lessons (2026)

The Two-Engine Rocket: Equity for Growth, Debt for Scale

Most founders think about funding as a single track: raise a seed, then a Series A, and so on. But if you’re building a lending business, you’re not building a typical SaaS company. You’re building a rocket that requires two different types of fuel.

David García Aceves’s journey with Digitt, raising $60 million in a mix of equity and debt, is a masterclass in this dual-capital strategy. He learned from two prior startup failures that you need more than a good idea; you need the right funding strategy for your specific business model.

The core lesson: Equity funds your machine. Debt funds your product.

Equity Capital (Pre-Seed, Seed, Series A): This is for your G&A. It pays for your engineers, your marketers, your office space, and the technology platform itself. This is risk capital from venture investors who believe in your team and vision. · Debt Capital (Credit Facilities): This is for your loan book. It’s the money you actually lend to your customers. This is lower-risk capital from debt funds or banks who care about your underwriting data, default rates, and unit economics.

Trying to fund your loan book with equity is a fatal mistake. You’ll dilute yourself to oblivion just to grow your lending volume. Conversely, you can’t raise debt on day one to pay salaries. You need both, and you need them in the right sequence.

First, Find a Problem You Can't Live Without Solving

Before you even think about capital, you have to find a mission that survives contact with reality. David’s first startup failed because he wasn’t passionate about the problem. When the inevitable struggles hit, he didn’t have the deep-seated motivation to push through.

His determination to fix the financial system in Mexico, born from his own upbringing, gave him the resilience to survive the entrepreneurial gauntlet. Investors don't just back an idea; they back a founder who is inextricably linked to the problem.

The Passion Litmus Test

Could you work on this for 10 years, even if it only ever paid a modest salary? · When you talk about the problem, do you get angry, frustrated, or energized? · Are you solving a problem you have personally experienced or seen up close?

If the answer is no, find a different problem. The road is too long and too hard to fake it.

Second, Find a Venture-Scale Market

Passion is necessary, but not sufficient. David’s second startup, in fraud prevention, had a passionate team but hit a wall: the total addressable market (TAM) in Mexico was too small. They had built a better mousetrap, but there weren't enough mice.

This is a classic, painful, and unfixable founder mistake. Before you write a line of code, you must pressure-test your market size.

How to Avoid the Small Market Trap

Bottom-Up Analysis: Don't rely on generic industry reports ("The LatAm fintech market is $50B!"). Calculate your potential from the ground up. (Number of potential customers) x (Annual revenue per customer) = Your realistic TAM. · Customer Discovery: Who, specifically, is your customer? How many of them are there? How much are they paying to solve this problem today? If you can’t find 20 people in a week who have the budget and pain point to use your hypothetical product, you have a market problem. · Gut-Check the "Why Now": Is there a technological, regulatory, or behavioral shift that makes this market suddenly viable and large? For Digitt, it was the rise of a prime consumer class in Mexico burdened by high-interest credit card debt.

The Outsider's Advantage: Reimagining Credit

David had no prior experience in finance. In an industry dominated by incumbents, this was his superpower. He wasn't burdened by the assumptions of how a bank "should" work. He could ask naive questions that led to fundamental breakthroughs.

He saw a system that used punitive fees and complex terms to trap good customers in debt. His "fresh perspective" wasn't just a nice-to-have; it was the entire premise of the business: what if you built a credit product designed to help prime customers get out of debt?

If you're entering a legacy industry, lean into your ignorance. Question everything. The dumbest questions often expose the most broken assumptions and the biggest opportunities.

Forced Scarcity Creates a Scalable Machine

Digitt didn't raise a massive seed round to start. Limited resources were a blessing in disguise. They couldn't afford a large underwriting team or expensive, off-the-shelf loan origination software. They were forced to build a lean, automated, and scalable operation from day one.

Your Scrappy Fintech MVP Playbook

Intake: Use Typeform or a simple web form to capture initial applications. · Automation: Use Zapier or Make to pipe application data into a Google Sheet. · Underwriting "Core": Your first credit model is a Google Sheet. You manually pull in data, check it against a simple ruleset, and make a decision. · Communication: Manually send emails or WhatsApp messages to applicants.

This sounds unscalable, but it's the only way to start. It forces you to be ruthlessly efficient and to understand every single step of your operation. You replace the spreadsheet with software piece by piece, only after you've proven the logic manually.

De-Risking the Business by Meeting Your First 100 Customers

The single most important asset for a lending startup is its underwriting model. The only way to build one is to underwrite your first loans yourself. David and his team met their early customers in person, looked at their documents, and heard their stories.

This qualitative, hands-on process is how you build the intuition that eventually becomes a quantitative, automated model.

Your first underwriting model isn't code, it's a conversation. You need to understand the human context behind the numbers before you can let an algorithm take over.

How to Manually Underwrite Your First Loans

Identity: Government-issued ID. Are they who they say they are? · Income: Bank statements and pay stubs. Is their income stable and sufficient to cover the new payment? A key metric is the Debt-to-Income (DTI) ratio. · Existing Debts: Credit bureau reports. What is their current debt load? Have they been delinquent before? · The Story: Get on a call. Why are they in debt? What is their plan to pay it back? You will be shocked at what you learn.

You log every data point and every decision in your spreadsheet. After 50-100 loans, you will have a rich dataset. You’ll start to see patterns. These patterns are the foundation of your V1 credit model and your key to unlocking real funding.

Putting It All Together: The Equity + Debt Flywheel

With a proven, data-backed underwriting process, Digitt was ready to scale. They had de-risked the business for both equity and debt investors.

Raise Equity: They went to VCs like Clocktower Ventures and FJ Labs. The pitch wasn't just "we have a great app." It was "we have a proven underwriting machine with a 1.5% default rate over 18 months, and for every dollar we lend, we generate a 20% net interest margin. We need your capital to hire more engineers and prepare for a Series A." · Raise Debt: With equity in the bank and a strong track record, they could now approach debt providers. Their pitch was different: "We have a stable, predictable portfolio of consumer loans. We need a $10M credit facility to grow our loan book. Here is our historical performance data."

This is the flywheel. The equity builds a better machine. The better machine produces better data. The better data unlocks cheaper debt. The cheaper debt improves your unit economics, which justifies the next equity round.

Common Mistakes Founders Make

Mixing funds: Using expensive equity to fund loans. Your VCs are expecting SaaS multiples, not bank-like returns. · Raising debt too early: Approaching debt funds with an unproven idea and no data. They will say no. · Ignoring the story: Failing to build a mission-driven brand that resonates with customers and investors. · Scaling before proving: Automating a bad underwriting process just pours fuel on the fire.

How to Apply This This Week

Stop theorizing and start executing. Here’s your plan for Monday morning:

Validate Your Market Size: Build a bottom-up TAM model in a spreadsheet. Is it big enough to be a venture-backed business? · Find 10 Customers: Identify 10 people in your target demographic. Email them and ask for 15 minutes to talk about their financial problems. Don't pitch; just listen. · Map Your "Scrappy MVP": Whiteboard the manual, Google-Sheet-and-Zapier version of your product. What are the exact steps from application to loan disbursement? · Define Your First Underwriting Checklist: What 5-10 data points would you absolutely need to see to feel comfortable lending a friend $1,000? Write them down. That's the start of your credit policy.