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Every industry has that moment when everything changes, when a new idea breaks through, and nothing works the same again. Finance is living that moment right now, as AI reshapes how money moves and how businesses grow.
Quietly but confidently, Felipe Cortés Bello is one of the people steering that change from behind the scenes: “AI isn’t here to replace people; it’s here to take the boring, repetitive work off our plates so we can focus on the decisions that actually move a business forward,” he explains. The transition, he explains, is unfolding far faster than most expect, and the companies that adjust early “will define the next decade of finance.”
This finance and AI expert blends the street-smart grit of Bogotá with the rapid-fire innovation of San Francisco, giving him an edge in an industry that never slows down. As Head of Finance at Domu Technology, a Y Combinator–backed startup building licensed AI debt collectors, Felipe helped secure $4.5 million in funding. He also turned voice-driven AI into a powerful recovery tool for lenders. At just 27, Felipe is more than a CFO—he’s the strategist behind the capital structures that push AI-fintech ideas from early prototypes into full-scale products.
Before joining Domu, Felipe had already been shaped by years of real, high-pressure finance work. At MD Banca de Inversión, he helped lead a US$13.5 million acquisition for a company earning around US$50 million a year, building financial models that showed exactly how the deal would create value. His career took off even further at Citibank, where he managed a fintech and startups portfolio that generated about US$9 million annually and reviewed deals for AI-driven lenders like Sempli.
He also took part in a US$60 million securitization for Credivalores through Citi’s Social Finance program. Moreover, at Hudson Murray, he developed the financial model and marketing materials and helped secure investors. These experiences gave him a front-row seat to how machine-learning models were already reshaping credit scoring, portfolio risk, and financial inclusion, long before “AI” became the buzzword it is today: “I saw early on how AI could speed up everything, from underwriting to decision-making, and it stuck with me,” he recalls.
That early exposure now shows up in how he works with founders, from early-stage fintechs to companies mixing AI with hardware. As he puts it, “Founders come to us thinking they need a perfect model. What they really need is clarity: what drives revenue, what drives costs, and what the data actually says about their business.”
His approach, combining classic valuation frameworks with real-time AI signals, has begun changing how early-stage startups prepare for fundraising. Several advisors and founders now adopt his “clarity-first modeling” style, where the goal isn’t theoretical perfection but actionable precision. This shift influences how pitch decks, forecast models, and M&A materials are built across AI-focused accelerators.
From Candy Hustles to Code Hacks: The Bogotá Blueprint
Felipe’s journey started long before the world of banks, term sheets, or AI. Growing up in Bogotá, he treated the schoolyard like a mini marketplace, selling candy, trading baseball cards, and even sketching for classmates. For him, these weren’t just small hustles; they taught him to offer value: “I’ve always liked the idea of creating something from scratch and seeing people find value in it; that was the first time I understood what building really meant,” he recalls.
By the time he turned 13, that same curiosity shifted toward tech. He was digging into video game files, modding gameplay, and teaching himself to code through trial and error. His YouTube channel, packed with homemade tutorials and game hacks, reached 500 subscribers before he even entered college: “I’ve always been very curious. When I see something interesting, I want to open it up and understand how it works,” he recalls. That instinct to take things apart and rebuild them never left: “Even with games, I just wanted to see what was behind the screen,” Felipe added.
This passion for deconstructing and re-engineering systems followed him into academia. At Universidad Externado de Colombia, Felipe graduated with a 4.4/5.0 GPA and ranked in the 99.5th percentile on the national ECAES exam. As head of the school’s Investment Banking Division, he helped students connect classroom theories to real-world finance, mentoring more than 500 students in valuation and risk. Felipe also worked as a teaching assistant for portfolio management, risk management, and financial analysis, strengthening the same analytical mindset he once used to tweak game code.
Outside of class, Felipe organized finance and tech conferences for students and took specialized courses in valuation, investment banking, and financial modeling. It was the same builder’s mindset from his childhood, just applied to capital markets instead of YouTube mods: “I loved breaking things down and rebuilding them. It didn’t matter if it was a video game or a financial model, I wanted to understand the mechanics,” he recalls.
Wall Street Grind: Mega-Deals in Emerging Markets
Felipe has always been someone who wants to understand how things work and then make them work better. This mindset naturally carried him into his early career in investment banking, where he learned to translate creativity into action and curiosity into results: “Banking forces you to become extremely structured. You can’t hide behind ideas; your numbers need to speak for you,” he explains. That discipline opened the door to the next phase of his journey.
At MD Banca de Inversión, this sought-after finance specialist worked on a $13.5 million buy-side acquisition for a meat processing company earning $50 million a year. He built the synergy models that guided the deal’s post-acquisition cash flows and crafted corporate presentations backed by deep financial analysis. Those early responsibilities became the foundation for the bigger, higher-stakes roles he took on later: “That was the first time I saw how modeling can literally determine the future of a company,” Felipe recalls.
At Citibank, he supported major deals, including a $550 million syndicated loan rollover for a 266-kilometer Colombian toll road and the management of a $9 million fintech and startups portfolio, with transactions such as a $6 million deal for AI lender Sempli and $60 million in securitizations. He also worked on Grupo Sura’s $300 million tender offer for Nutresa’s minority shareholders and contributed to Sura Asset Management’s $350 million refinancing plan for a $500 million note.
Much of his day-to-day work involved analyzing credit and repayment capacity, preparing materials for risk committees, and coordinating with senior bankers to secure capital-return approvals. As he puts it, “Citi was a battlefield… You have to be fast, accurate, and ready to defend your work to very senior people.”
Working in developing economies sharpened his instincts: “In emerging markets, nothing is clear, nothing is linear. You learn to plan for the worst-case scenario as the default,” Felipe shares. Instead of relying on assumptions, he learned to think in scenarios because the landscape demanded it: “You move capital to finance huge projects in third-world economies,” he added.
He often points to deals like the Covioriente loan rollover as examples: negotiations between banks and sponsors, stress testing, and repayment planning were never straightforward: “Those deals teach you to operate with uncertainty. You can’t wait for perfect conditions; they simply don’t exist,” he explained.
Those early years built the edge he now brings into tech: AI-powered credit scoring, predictive analytics, and tougher, more resilient portfolio decisions. The discipline he developed for evaluating secured lending opportunities and managing Citi’s fintech portfolio now fuels faster, data-driven judgment in the startup world: “Tech moves fast, but the fundamentals of assessing risk don’t change. My banking training is still the backbone of how I think,” Felipe shares.
YC CFO and $20M War Chest
In 2024, as interim CFO during Domu’s YC batch, Felipe led a $4.5 million seed round and then pushed the company’s Series A to $15.5 million, bringing total fundraising to $20 million by Q4 2025.
At Domu, his voice-AI collection agents: empathetic, compliant, and cost-efficient, boosted recovery rates by 25% while cutting operating costs in half, winning pilots with central U.S. banks. He also guided pricing strategy and rebuilt FP&A workflows to keep financial forecasts aligned with rapid user growth: “YC forces you to compress three years of growth into three months,” he shares. “You either adapt or you get left behind.”
The pace didn’t slow after the batch: “At Domu, every financial model I build has to keep pace with live data. The numbers change daily, and sometimes even hourly. That’s the reality of AI startups,” he explains. To stay ahead, he integrated AI tools into FP&A to refine revenue models, forecast user adoption, and maintain tight financial controls as the company scaled.
Santiago Rios Olaya met Felipe through a mutual connection, Nicolas Diaz , with whom Santiago had collaborated on projects at his former company, Cerebrum, as well as in Web3 and AI endeavors.
They have shared professional spaces on mutual projects, such as Salespresso (an SDR enhancement tool), and have advised Team 360 Staffing (part of Talent Source Solutions LLC). As co-workers at Domu, Santiago has known Felipe for approximately five years.
Santiago says: He played a crucial role in closing all of the company's funding rounds, maintaining investor relations, and managing the budget. Felipe’s general vision of the business helped us identify and exploit key points of leverage. He also took full ownership of the company’s cost center, personally communicating priorities and taking decisive action to reduce the costs of our main service providers."
He adds: "It is rare to meet someone with his level of expertise in banking and finance who also possesses the willingness to adopt AI technology into his daily workflow. Felipe shows a deep interest in the engineering side of the business and how technical decisions are made."
Emilio Gnecco, an Investment Banking Professional, met Felipe at Universidad Externado de Colombia in 2017, during their overlapping time as finance students. After graduation, they worked together on the same team
He says: “I learned about Felipe’s expertise by working directly with him on transactions that required advanced financial modeling, process automation, and data-driven analysis.
“However, what stands out most is his ability to combine strong traditional finance skills with a practical understanding of AI and technology. He worked on several projects, which included the full development of AI tools, and demonstrated his ability to apply technology in practical financial settings."
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“Felipe showed that he can move from financial theory to real, technology-driven solutions that create value."
In many ways, his balance of speed and discipline is the through-line of his entire story. It’s the same attitude that took him from the schoolyard hustle to Wall Street spreadsheets to the boardrooms of Silicon Valley. What changed were the stakes; what didn’t is the mindset: understand how things work, then make them work better. In his words: “AI lets you move faster, but finance keeps you honest. You need both if you want a company to survive the chaos of scaling.”
AI-Fintech Oracle: Why Cortés Bello's the Unicorn Whisperer
Felipe’s strength comes from pairing finance’s discipline with AI’s speed. At Domu, he uses FP&A to model LLM-driven yields and reduce risk under regulations like the FDCPA: “We’re changing the industry, replacing labor with evolution,” he said. For clients, that translates into collection cycles three times faster; for investors, it signals a scalable SaaS engine with 40% CAGR potential.
As Domu expands globally and AI continues to accelerate, he prepares himself for more high-level opportunities. His toolkit includes Bloomberg Terminal, Capital IQ, advanced Excel modeling, AI-augmented financial tools, and credentials like Bloomberg Market Concepts and JPMorgan’s IB virtual experience. These give him the analytical foundation to pair AI intuition with sound economic judgment.
He believes winning founders master both speed and discipline. “AI gives you speed, but discipline gives you longevity. AI isn’t here to replace finance people; it’s here to expose who actually understands the numbers. The ones who don’t adapt will disappear,” he explains.
From Wall Street fundamentals to Silicon Valley execution, Felipe embodies the emerging archetype: finance operators who also code. As automation reshapes every corner of the industry, he proves that the real edge isn’t choosing between humans and machines, but knowing how to leverage them together. Adapt early, execute fast, and bet on evolution over comfort, because the next generation of progress won’t be built by those who fear AI, but by those who learn to wield it. As he puts it: “The market rewards the bold; let’s evolve together.”
