Best fintech stocks: how to pick them with data

The first thing is to identify the type of business in front of you, because it defines everything else. Ask yourself: does this company take on credit risk (lend money it might not get back) or does it only charge a fee for moving other people's money? Pure networks and processors belong to the second group, the most profitable and predictable. Lending or "buy now, pay later" fintechs belong to the first and, in reality, should be analyzed with a banker's eye (defaults, provisions, capital). Classifying the company correctly stops you from applying the wrong metrics.

The second thing is to assess the strength of the moat. In payments, the competitive moat comes from the network effect and from switching costs: a network with billions of cards and tens of millions of merchants is practically impossible to displace, because no competitor can offer that universal acceptance from scratch. The third is the growth of processed volume and revenue, but always accompanied by real profitability: a fintech that grows a lot while burning cash isn't the same as a network that grows while generating profits. With these three readings —type of business, moat and profitable growth— you can already start filtering the sector with the stock screener.

The queen metric in networks and processors is the operating margin: how much profit is left from each dollar of revenue after the business's costs. Visa and Mastercard show operating margins above 50%, a figure that reveals a toll business with near-zero marginal costs. Such a high, stable margin is the fingerprint of a powerful moat. Alongside it, look at ROIC (return on invested capital): the big networks have it sky-high because they generate enormous profits with very little physical capital. A high, sustained ROIC is the objective proof that a competitive advantage exists.

For fintechs that aren't profitable yet, the analysis changes. There, what matters is revenue growth, the margin trend (is it approaching profit or still burning?) and, above all, the cash on hand versus the pace at which it consumes it. A fintech with no profit but cash for years and improving margins is different from one that needs to raise capital every twelve months. And here comes a central piece of the method: the price. The big networks usually trade expensive precisely because everyone knows their quality, so the question isn't just "is it a good business?" but "what growth expectations is the price already discounting?". To answer that, read on.

The great risk when investing in quality businesses like payment networks is overpaying for something good. An excellent company bought at an absurd price can deliver a mediocre return for years. This is where DeepTicker applies discounted-cash-flow valuation (Reverse DCF): instead of telling you "this stock is worth $X", it calculates what growth and what margin the current price is discounting and lets you judge whether you believe it. It's the right question for an expensive payments business.

An example from the system itself illustrates it: a company trades at $372 and today grows around 12% a year; the price is only justified if it grows close to 18% a year for ten years and lifts its cash margin from 20% to 32%. DeepTicker shows you those two requirements and you decide whether they are credible for a mature payment network. Also, growth isn't projected flat: it tapers year by year until it stabilizes around 2.5% (a multi-phase model), because no company grows at 18% forever. The system uses the real cost of capital (WACC) by industry from public data, not a generic one, which sharpens the valuation. The final verdict is summed up in a clear label: Bargain · Reasonable · Demanding · Expensive · Priced-in bubble, so you know at a glance what the market is asking for.

The first risk is regulatory. Networks and processors charge fees that regulators around the world watch closely; a legal cut to interchange fees can reduce income at a stroke. Banking and payments are among the most heavily regulated sectors, and that caps part of the upside. The second risk is technological disruption: instant account-to-account payments, central-bank digital currencies or new schemes that bypass the traditional networks could, over the long run, erode the toll. The moat is enormous today, but it isn't eternal by decree.

The third risk, specific to young fintech, is profitability and valuation. Many listed startups grow at triple digits but lose money and depend on raising capital; if the market turns off the tap or rates rise, their model wobbles. On top of that comes valuation risk: even the best networks can be so in fashion that their price discounts growth that's hard to deliver, and buying them there dooms future returns. Finally, lending fintechs carry credit risk just like a bank: in a recession, their defaults spike. Diversify, tell the toll from the promise and watch the price. This is educational information, not a buy recommendation.

Reviewing every listed payment and fintech company by hand is unfeasible, and mixing profitable networks with loss-making startups leads to costly mistakes. That's why a screener is worth it. With the DeepTicker stock screener and its 140+ filters you can, for example, ask for sector companies with an operating margin above 30%, high ROIC and positive profits, and separate in seconds the established tolls from the promises still burning cash. That turns a scattered search into an orderly, repeatable process.

Every result comes paired with the DeepTicker Score (a quality grade from 0 to 100 with sector benchmarks) and the Reverse DCF valuation verdict, so you see at a glance whether the company is Elite or Fragile quality and whether its price is Reasonable or Expensive. That's the essence of the method: separating the two questions, is it a good business? (quality, with emphasis on the franchise and the moat) and is it priced right? (the discounted-cash-flow valuation, Reverse DCF). DeepTicker applies recognized fundamental-analysis methods, but made simple, and explains every number so that the more you use the tool, the better an investor you become. It isn't financial advice: it's data so you decide for yourself.