Adapted from the first session of Insignia Ventures Academy’s Certificate in Venture Capital course on Thesis-Driven Investing and supplemented with relevant Insignia Business Review portfolio case studies

Venture conviction is often described as instinct. An investor meets a founder, sees a market shift, and decides quickly.

In practice, conviction is usually more deliberate than that. The best investors are not simply confident. They have a clear view of what is changing, why it matters now, what has to be true for a company to win, and what could prove them wrong. Conviction is structured judgment under uncertainty. [1]

That is a useful place to start for the first piece in our new Think like a VC series: where does conviction actually come from?

Conviction is not just gut feel

Instinct matters in venture, but a fund cannot run on instinct alone. A thesis is not something investors add after the fact to justify a decision. It is the framework that helps them compare opportunities, explain decisions to founders and LPs, and stay consistent when markets get noisy. [1]

That matters because instinct is hard to test. A framework can be debated, improved, and challenged. When investors say they have conviction, what they should mean is that they have enough evidence and market logic to support belief. Not certainty. Belief. [1]

Three possible ways conviction begins

Conviction does not start in the same place every time. In practice, investors can build an initial view through a variety of routes, including these three. [1]

The product-driven lens is easiest to see in consumer technology. TikTok mattered not because it was another social app, but because it changed how people consumed content. The signal became clearer when incumbents responded. In 2021, YouTube launched Shorts in the United States, showing that short-form video had become a durable product behavior. [1] [6]

The thematic lens is broader. Here the investor is less focused on one product feature and more focused on the shift beneath it. AI is the clearest example today, but the same logic applies in payments, regional brands, and cross-border financial workflows. A good thematic thesis is not just a big market story. It is a view on why multiple companies can be built on the same structural change. [1]

The opportunistic lens is where discipline matters most. Quick commerce is a good example. Customers clearly liked speed and convenience, but that did not make the model durable. In many markets, the model relied on subsidized delivery, small basket sizes, expensive last-mile logistics, and dense fulfillment networks that were costly to maintain. Demand was real, but margins were thin. Once funding tightened, the question became whether customers valued speed enough to pay for the full cost of the service, not just whether they enjoyed it. [1]

This is the first source of conviction: using the right lens. Many weak decisions come from looking at a company through the wrong one.

Conviction strengthens when evidence starts to stack

A framework is only the start. In practice, conviction often comes from a combination of sources rather than a single insight. The portfolio examples are most useful when read that way.

Finmo is a good example of conviction built from multiple sources at once. One was founder experience: this is a category where product alone is not enough, because treasury, payments, and cross-border workflows sit close to regulation and operational complexity. Another was licenses, which matter because trust, access, and compliance are built into the product from the start. The third was early go-to-market execution. The case for Finmo was not just that treasury workflows were fragmented, but that the company was already building the right ecosystem around the product to make adoption easier. [2]

StraitsX shows how conviction can come from both company-specific strengths and a broader market shift. At the company level, licenses mattered because they made it possible to build a wider ecosystem of products around stablecoin infrastructure and to form the right banking, custody, exchange, and network partnerships. At the market level, the shift toward stablecoin payment rails created both a thematic and opportunistic opening. Thematic, because payment infrastructure is evolving toward faster and more programmable rails. Opportunistic, because regulated players were in a better position to capture that shift as real use cases emerged. [3]

Surfin is a useful example of conviction built from theme, proof, and founder fit. One source was the broader shift toward AI infrastructure in financial services, where better data, underwriting, and decision systems can improve how financial products are delivered. Another was proof: the company had already shown traction and profitability across several markets, which made the thesis more credible than a purely forward-looking story. The third was founder experience in risk management and fintech, which matters in a business where underwriting discipline is central to the outcome. [4]

fileAI shows how conviction can form around a thematic gap in an industry that is already large but still poorly served. As more enterprises adopt automation, there is growing demand for a horizontal solution that can work across workflows rather than solve only one narrow use case. That is where fileAI fits. The opportunity is not just to participate in AI automation, but to build a best-in-class product for handling the messy document and data layer that many automated workflows still depend on. [5]

These examples point to a broader lesson. Investors do not build conviction by memorizing sectors. They build it by understanding which constraints are starting to break, and which companies are positioned to benefit when they do.

Timing matters, but so does form factor

A category can travel across markets without producing the same kind of winner in each one. That is why investors have to do more than copy a thesis from another geography.

E-commerce makes this clear. The category was obvious early. The winning operating model was not. Different markets rewarded different approaches depending on logistics, payments, merchant behavior, and consumer habits. The category repeated. The form factor changed. [1]

The same logic applies to newer sectors. Cross-border payments in Southeast Asia will not look exactly like treasury software in the United States. Stablecoin infrastructure in the region will not scale for the same reasons crypto markets grew elsewhere. AI companies in Southeast Asia will not win by following the same playbook as frontier-model companies in larger ecosystems. Conviction becomes sharper when investors understand not just the category, but the version of the category that fits the market in front of them. [1]

This is also why talent matters. Markets do not change through macro trends alone. They change through founders and operators who know what can travel and what needs to be rebuilt locally. In emerging ecosystems, that translation ability is often part of the moat. [1]

Conviction has to survive hard questions

Real conviction is not built by finding reasons to say yes. It is built by asking whether the case survives hard questions. [1]

The same logic applies in deep tech. Novelty is not enough. The more important question is whether the technology can move from technical promise to adoption and commercialization. In that sense, customer calls and market research are not secondary diligence. They are where conviction either gets stronger or falls apart. [1]

The same discipline appears in the discussion around Islamic fintech. The category can sound compelling on paper, especially in markets with large Muslim populations. But a good thesis cannot rely on elegance alone. It has to ask whether actual customer behavior supports the idea, or whether users mainly care about access, price, speed, and convenience. [1]

Even in AI, the same standard applies. The most investable companies are not always the most technically impressive ones. Often they are the ones that can be bought, integrated, and used inside real workflows. That is part of what makes fileAI a useful case study. It ties the AI discussion back to a concrete operational problem. [1] [5]

One example captures this clearly: passing on an autonomous code-testing platform after market checks suggested the pain was not acute enough yet. That is disciplined conviction in practice. Sometimes the right answer is simply “not yet.” [1]

Conviction must include the exit

There is one part of venture thinking that is less glamorous but just as important: conviction is incomplete if it does not include a view on how value may eventually be realized. [1]

That does not mean reducing every company to a spreadsheet. It means being clear about what kind of outcome is being underwritten. Is this a local winner or a global one? Is the market large enough for the ownership target the fund needs? Are there plausible M&A, secondary, or public market paths? In categories like AI, is the company being priced like a global leader when the more realistic outcome is narrower? [1]

Conviction and valuation are tightly linked. A strong thesis does not justify any price. This shows up in three ways. First, investors still have to underwrite a realistic outcome within the fund’s time horizon, often using a five-year scenario to test whether the company can plausibly deliver the return implied by the entry price. Second, multiples depend on the business model, growth, and the quality of the benchmark. SaaS businesses are often assessed on ARR, more mature companies move toward audited revenue and eventually EBITDA or net profit, and AI-native companies can look expensive on little revenue because the market is still debating how to price future potential. Third, private round momentum is not enough. Exit assumptions are stronger when they are anchored to relevant public benchmarks rather than optimistic private comps. [1]

This matters because conviction should sharpen pricing discipline, not weaken it. A thesis can be directionally right and still be a poor investment if the valuation assumes a global winner too early, uses the wrong multiple, or leaves too little room for the fund to earn its target return. That is also why ownership targets, check size, and realistic exit paths matter so much in venture underwriting. [1]

Think like a VC

So where does VC conviction come from?

It comes from understanding what is changing, why now, what has to be true for the company to win, and what evidence supports that view. It comes from choosing the right lens, testing the thesis against hard questions, and making sure the opportunity is large enough to matter but concrete enough to evaluate. [1]

The portfolio examples make this practical. The point is not that each company maps neatly to a single lens. It is that the strongest cases usually combine several sources of conviction at once: founder fit, market timing, licenses, product quality, ecosystem building, and visible proof from the market. [2] [3] [4] [5]

For founders and builders, understanding conviction changes how you explain the company. The goal is not to sound visionary in the abstract. It is to show why this market is opening now, why your team is equipped to win, what proof already exists, and what milestones will make belief stronger over time.

That framing also matters beyond venture firms. Angels, family offices, and CVCs may invest with different return expectations, time horizons, or strategic goals, but they still need a clear reason to believe. Understanding VC conviction helps them separate compelling stories from investable ones, ask better questions about timing and evidence, and see whether an opportunity is backed by more than enthusiasm.

In that sense, conviction is useful not just for VCs. It is a practical language for anyone building, backing, or evaluating startups. It helps founders communicate more clearly, and it helps investors of all kinds decide what they actually believe and why.

References

[1]: Insignia Ventures Academy Certificate in Venture Capital Cohort 10 Session 1 Thesis-Driven Investing.

[2]: Paulo Joquino. The Trillion Dollar Opportunity of Building a World-Class Global Treasury Operating System: Why We Back Finmo. Insignia Business Review. 02/18/2025.

[3]: Paulo Joquino. The License-Distribution Moat: Why Southeast Asian Fintechs Are Building the Right Foundations. Insignia Business Review. 07/11/2025.

[4]: Paulo Joquino. What Makes Surfin a Wave Maker at the Intersection of AI and Fintech (Part 1/2). Insignia Business Review. 05/06/2025.

[5]: Clare Leighton. The $4.4 Trillion Opportunity: How fileAI powers the Future of Work. Insignia Business Review. 07/08/2025.

[6]: Todd Sherman. Bringing YouTube Shorts to the U.S.. YouTube Blog. 03/18/2021.