How startups are reshaping the ‘moats’ of traditional companies

Abstract

The concept of a competitive moat, popularized by Warren Buffett, describes the sustainable advantages that protect a company from competition and secure its long‑term profitability. Traditionally, these moats have relied on scale, brand, regulation, and ownership of physical assets. However, the rise of digital startups is redefining what counts today as a real competitive advantage: rather than competing only on products or prices, they are changing the rules of the game by turning data, user experience, and communities into defenses that are hard to copy [1][2].

This white paper analyzes how classical moats are being eroded or transformed in different industries—finance, retail, mobility, and health/education—with the emergence of new digital moats. Drawing on real examples and recent evidence on corporate investment in startups, open innovation, and sectoral regulation, it shows that the frontier between traditional companies and startups is increasingly porous [1][2]. It argues that technology and user experience act as “enabling” moats that amplify or replace classical defenses, and it derives concrete strategic implications for incumbent executives and founders seeking to build sustainable advantages over the next 3–5 years.

Background

The notion of a competitive moat comes from a simple metaphor: just like a castle’s moat, a sustainable advantage protects a company’s “fortress” from attackers. Warren Buffett insisted that it is not enough to have good products or a solid balance sheet; what is decisive is how difficult it is for a competitor to replicate or surpass your position. For decades, this idea worked in environments where competition progressed relatively gradually, technology cycles were long, and physical assets or regulatory concessions moved slowly.

In that context, large corporations built moats around tangible assets: factories, distribution networks, patents, bank branches, hospitals, universities. The asymmetry in capital, information, and regulation worked in their favor. It was costly to build a physical banking network, replicate a global brand, or gain access to established distribution channels. Financial regulation—such as the 2010 Dodd‑Frank Act in the U.S., designed to reinforce stability and consumer protection after the 2008 crisis—further raised compliance and capital requirements, strengthening the moats of established banks by increasing entry costs for new players [1].

Similarly, in the U.S. healthcare industry, certificate of need (CON) laws required healthcare providers to obtain state approval before opening new services. Although they were justified as mechanisms to avoid oversupply in urban areas and improve access in rural areas, in practice they often functioned as entry barriers that consolidated the position of incumbent hospitals [12]. In other sectors—such as telecommunications, energy, or infrastructure—licenses, concessions, and rigid regulatory frameworks also acted as protective walls.

On top of these elements were moats based on brand, scale, and intellectual property. Large corporations invested massively in advertising to build recognized brands, benefited from economies of scale in production and distribution, and protected their key innovations through patents. In the automotive industry, for example, economies of scale in engine manufacturing and accumulated know‑how in design and safety made it very difficult for a new entrant to compete on equal terms [1][2].

However, digitalization has drastically lowered several of these barriers. Setting up a global e‑commerce operation or a branchless neobank is now much cheaper than building a physical network of stores or offices. Frameworks such as open banking in Europe (PSD2, since 2018) force banks to open transactional data to authorized third parties, eroding the informational exclusivity that once constituted a key moat. The speed at which digital products spread and the falling cost of cloud infrastructure change the nature of sustainable advantage: what used to be defensive (scale, assets, regulation) no longer guarantees protection unless it is combined with digital capabilities and a radical focus on the user [1].

In parallel, large companies are trying to adapt through open innovation and collaboration with startups. In Spain, for example, Wayra—Telefónica’s vehicle—invested €9.3 million in 37 startups in 2024, many of them focused on digitizing traditional sectors such as banking, insurance, and health with AI and SaaS solutions [2]. CaixaBank launched a €150‑million venture debt fund for tech startups and scale‑ups in Spain and Portugal, competing with similar proposals from Santander, BBVA, and Bankinter [2]. Grupo Lets, for its part, created the Letsinnovate unit and hired the former head of open innovation at Acciona to lead it, with the aim of structuring formal vehicles for collaboration with startups and exploring new business models [2].

Despite these initiatives, there remains a gap between rhetoric and practice: according to a Back Fund report, of the 100 most relevant startup acquisitions, only 18 were carried out by large Spanish companies, reflecting a culture that still prioritizes organic and international growth over the acquisition of digital capabilities [2]. This context suggests that understanding how moats are being reconfigured is not a theoretical exercise but a matter of strategic survival: incumbents and startups are competing and cooperating on new bases of advantage.

Methods

This analysis is based on a qualitative synthesis of recent secondary sources focused on the intersection between traditional corporations and startups, with a particular focus on the European and Spanish context. The methodology combines three blocks of evidence:

First, data and examples of corporate investment in startups and open‑innovation programs are used. Cases such as the creation of the Letsinnovate unit at Grupo Lets illustrate how incumbents structure formal vehicles to collaborate with startups [2][5]. Wayra’s activity (€9.3 million invested in 37 startups in 2024) and CaixaBank’s €150‑million fund provide concrete magnitudes for the financial effort aimed at capturing digital capabilities [2][3]. These data are treated as approximate indicators of the strategic priority given to new digital moats.

Second, examples of startups that have built sustainable moats by combining technology, sustainability, and user‑experience design are included. Cases such as Too Good To Go, Ecoalf, OnTruck, Holaluz, or Lounn provide evidence of models where the integration of sustainability, data, and UX generates competitive defenses that are hard to replicate [6][7][8][9][10][2]. These cases are used not as isolated success stories, but as archetypes of moat strategies based on data, network, community, and purpose.

Third, the role of regulation in the creation and erosion of moats is reviewed, in both finance and health. The 2010 Dodd‑Frank Act and the repeal of Glass‑Steagall in 1999 in the U.S. are used as examples of how regulation and deregulation can reinforce or weaken entry barriers [1][11]. In health, CON laws illustrate how certain rules can become regulatory moats for established providers, while their repeal in some states has shown that increased competition is possible [12].

Using these inputs, a sector‑by‑sector comparative framework (finance, retail, mobility, and health/education) is constructed to contrast traditional moats with new digital moats. The analysis is complemented with logical inferences about the dynamics of data, network effects, and user experience, avoiding extrapolation beyond what the sources support. All quantitative facts cited are linked to specific references, and limitations are made explicit where the evidence is partial or contextual.

Key Findings

1. From asset‑based moats to data‑ and UX‑based moats

In most of the sectors analyzed, there is a shift from moats anchored in physical resources and regulation toward advantages grounded in proprietary data, algorithms, and digital experiences. This shift, however, is not binary: rather, traditional moats lose prominence if they are not combined with digital capabilities.

In banking, physical branches and privileged access to capital were among the main moats. Post‑2008 regulation—such as Dodd‑Frank—reinforced the role of large banks by raising capital and compliance requirements, making it harder for new players to enter [1]. However, the emergence of fintechs and super‑apps operating with light infrastructures, together with the push from open banking (PSD2), has shifted part of the defensive value from branches to the ability to orchestrate data from multiple banks in superior mobile interfaces [1][2]. Today, neobanks such as N26 or Revolut capture young users not by having more branches, but by offering better UX, transparency, and data‑driven features.

In retail, store density and supplier agreements provided significant barriers. The rise of e‑commerce and DTC brands has drastically reduced the cost of launching new players: platforms such as Shopify, along with external logistics networks, allow building a global channel without massive investment in bricks and mortar. DTC brands exploit online behavioral data, continuous A/B testing, and intense communities to refine products and messages at a speed unattainable for rigid physical networks [1][2]. Here, the moat shifts toward customer knowledge and responsiveness, more than mere physical presence.

A similar pattern is seen in mobility (from owned fleets to ride‑hailing platforms and logistics optimization) and in health and education (from hospital or university campuses to digital platforms supported by longitudinal user data). The table below summarizes this shift in simplified form:

This change does not eliminate classical moats but forces them to be reinterpreted. Brand still matters, but it is now built day by day through coherent digital experiences. Scale is still useful, but only if it translates into more data and better algorithms. Regulation remains relevant but can become ambivalent: frameworks like PSD2 reduce the defensive value of data exclusivity while creating opportunities for new specialized intermediaries [1][2].

2. New startup‑ecosystem moats: data, network, community, and speed

Proprietary data and advanced analytics

Robust digital startups tend to place data at the core of their moat. It is not only about collecting large volumes, but about turning transactional and behavioral data into personalization, prediction, and automation that are useful to the user. Neobanks such as N26 or Revolut extract value from spending patterns, location, and usage behavior to offer automatic categorizations, relevant alerts, and personalized products—something traditional banks took years to roll out at scale [1][2].

Cases such as Lounn in Mexico show how the use of artificial intelligence to automate credit processes can redefine access to capital for SMEs, transforming an area where traditional banks had a moat based on manual processes and in‑person relationships [10][2]. Similarly, OnTruck uses optimization algorithms to fill trucks and optimize routes, cutting costs and emissions in freight logistics, making it difficult for traditional carriers with analog processes to compete on efficiency [8].

Network effects and multi‑sided platforms

Network effects—the value of a service increasing with the number of users—become especially powerful when combined with two‑sided marketplaces. Uber and Lyft connect riders and drivers; Airbnb connects hosts and travelers; Too Good To Go connects stores with surplus food to price‑sensitive and sustainability‑minded consumers [6]. Each new user on one side reinforces the attractiveness for the other, creating a virtuous circle.

In Too Good To Go, for instance, each new store increases the variety and proximity of “surprise packs” available; each new consumer increases the likelihood of efficiently clearing surplus, reducing waste. The system improves its matching as the network becomes denser, consolidating a moat that does not depend on owning physical assets but on coordinating them better than anyone else [6].

Community and engagement

The most defensible startups do not just have customers; they have communities. Brands like Ecoalf, with a presence in more than 60 countries thanks to its sustainable fashion proposition based on recycled materials, rely on a community that shares environmental values and acts as an evangelist [7]. Too Good To Go has turned the fight against food waste into a “movement,” where each purchase is perceived as an act of positive impact [6].

In purely digital realms, product communities and user‑generated content (UGC)—for example in edtech, with forums and user contributions—generate a constant flow of improvement and organic virality. These community‑based moats are especially powerful when intertwined with network effects: more users generate more content and more data, which in turn improve the product and reinforce belonging.

Speed of iteration and experimentation culture

The ability to launch, measure, and adjust products in short cycles is, in itself, a cultural moat. Many startups integrate continuous A/B testing and experimentation as a daily routine. This speed is not only due to the absence of technological legacy: it reflects governance and a mindset that favor rapid testing over exhaustive planning [1][2].

By contrast, large companies whose technology is focused mainly on internal efficiencies—rather than experimentation at the customer interface—often take months to roll out changes that a digital player adjusts in days. This time asymmetry translates into a learning asymmetry: those who learn faster deepen their moat sooner.

API ecosystems and integrations

Becoming “infrastructure” for other businesses is another emerging pattern. B2B fintechs offer APIs for payments, identity verification, or credit scoring that allow third‑party companies to embed financial capabilities without being banks themselves. Open banking and PSD2 regulation have accelerated the creation of such infrastructure, enabling third parties to access banking data with user consent [2].

Companies that become the infrastructure layer benefit from high switching costs and indirect network effects: the more businesses integrate their API, the more attractive it becomes for new partners. At the same time, banks that open their own APIs and build ecosystems around them are trying to transform their former regulatory and scale advantage into a platform moat.

Outstanding UX/UI as a moat in itself

Finally, user experience has become a standalone moat when sustained by data, community, and a solid product. Holaluz, with more than 600,000 customers and a proposition centered on 100% renewable energy and solar self‑consumption, has used a clear, transparent, and simple UX to differentiate itself from the traditionally opaque perception of energy utilities [9]. Similarly, many fintechs have shown that a simple app—with account opening in minutes and transparent fees—can dislodge decades of inertia favoring traditional banks [1][2].

In all these cases, UX is not just an aesthetic layer but the visible manifestation of processes, technology, and culture that are deeply user‑centric.

3. Collaboration dynamics: open innovation and corporate investment

Large companies are not only competing with startups; increasingly, they are incorporating them as part of their moat strategy. Grupo Lets, for example, created the Letsinnovate unit with the explicit objective of fostering corporate innovation and engagement with startups [5][2]. This structure acknowledges that some moats—such as community, agility, and specialized digital capabilities—are more efficient to acquire or co‑develop than to build entirely in‑house.

On the financial side, Wayra allocated €9.3 million in 2024 to support 37 tech startups, many focused on digitizing sectors such as banking, insurance, and health through AI and SaaS [2]. CaixaBank launched its €150‑million venture debt fund for tech startups and scale‑ups, aligning with similar strategies from Santander, BBVA, and Bankinter [3][2]. These figures reveal a strategic move: banks are using their access to capital—a classical moat—to gain exposure to new digital moats.

Even so, corporate investment in startups in Spain remains limited in relative terms: of the 100 most relevant startup acquisitions, only 18 were undertaken by domestic companies [2][4]. This suggests that although new moats are recognized, there is still a culture that prioritizes organic growth and international expansion over the purchase of digital capabilities. For many incumbents, the strategic dilemma is not understanding the new moats, but changing culture and decision‑making processes to integrate them effectively [2].

Comparative Analysis

Financial sector: traditional banking vs. fintech

Historically, banking relied on moats of brand, institutional trust, branch networks, and regulation. The 2008 crisis reinforced this dependence on regulation as a defensive moat: Dodd‑Frank in 2010 increased capital and oversight requirements, raising operating costs and consolidating the position of large banks [1]. In Europe, similar requirements reinforced the perception that “being big” was almost synonymous with “being safe.” Customer information remained largely locked inside banking systems, making data a passive but effective moat.

Fintechs have challenged this model by building alternative moats. First, they redesign UX: accounts opened in minutes, instant virtual cards, clear spending visualizations, and automatic savings features. Second, they exploit transactional data to offer value‑added services (spending analysis, personalized cashback, modular products). Third, they leverage APIs and open banking to aggregate data from multiple banks in a single app, diluting each institution’s informational exclusivity [1][2].

Regulation plays an ambivalent role here. On the one hand, frameworks such as PSD2 erode data‑exclusivity moats by forcing banks to open data to authorized third parties [1]. On the other, fintechs that manage to navigate this complex environment acquire their own regulatory moat in the form of compliance know‑how and relationships with supervisors. Additionally, initiatives such as CaixaBank’s venture‑debt fund or Wayra’s investments show how incumbents are trying to reuse their privileged access to capital—a classical moat—to anchor strategic relationships with fintechs that possess UX, data, and community moats [2][3].

Retail and consumer: physical stores vs. e‑commerce / DTC

In retail, incumbents defended themselves through premium locations, exclusive supplier contracts, and dense store networks. These barriers made it very costly for a new player to achieve volume and visibility. Mass advertising consolidated brands built over decades, reinforcing a cycle where physical presence fed consumer attention, and vice versa [1][2].

The rise of e‑commerce and DTC brands has changed the rules. Consumer startups can launch products without their own stores, relying on digital platforms, social networks, and third‑party logistics. Warby Parker and Glossier (in the international context) have used behavioral data, continuous product testing, and digital communities to build strong brands without the historical infrastructure of physical retail. Spain‑born Ecoalf has projected its sustainability vision to more than 60 countries through both online channels and selective physical partnerships, showing that a powerful, coherent narrative can partially substitute for former physical ubiquity [7][2].

The moat shifts from “owning the best corner on Main Street” to “having the best customer knowledge, the best digital experience, and the most engaged community.” Logistics adds another source of advantage: startups such as Too Good To Go, which connect surplus food inventories with real‑time demand, demonstrate how technology enables monetization of assets that traditional retail saw only as waste [6].

Mobility and transport: traditional operators vs. digital platforms

Airlines, logistics operators, and taxi companies built their moats on licenses, concessions, fleets, and access to physical hubs. The barrier to entry was predominantly capital and infrastructure: buying planes, trucks, or taxi licenses required sizable investments and time. Reservation and allocation systems were opaque to end users, who adapted to the available supply.

Digital mobility platforms such as Uber and Lyft introduced a different kind of moat: matching and dynamic‑pricing algorithms, real‑time data, and a unified app‑based user experience [1]. In B2B logistics, OnTruck uses AI to optimize routes and consolidate loads, reducing empty kilometers and emissions, giving it an operational edge that is hard to replicate for operators relying on manual planning [8]. Physical ownership of the fleet becomes less relevant than the ability to orchestrate a flexible network of distributed assets.

These new moats depend on data scale and algorithm quality, reinforced by network effects: more drivers and customers mean better wait times and prices; more shippers and carriers in a network such as OnTruck mean better asset utilization and service. Regulation again cuts both ways: licenses remain a moat for some operators, but also a double‑edged sword, since rigid frameworks can slow the adoption of more efficient models that attract users based purely on convenience [11][12].

Education and health: traditional institutions vs. edtech / healthtech

In education, universities and schools consolidated their moats around academic brand, official accreditation, and physical campuses. The promise was not just content but reputation, networks, and life experience. In health, hospitals and insurers concentrated infrastructure, professionals, contracts with payers, and strong regulatory frameworks, including mechanisms such as CON laws that protected established providers [12].

Edtech platforms such as Coursera or Duolingo have begun to unbundle this package. Content becomes ubiquitous, but the real moat arises from progress data, personalization, and global learning communities [1][2]. Similarly, healthtech startups that manage longitudinal patient records, facilitate teleconsultations, and offer simple UX reconfigure trust: users begin to trust not only the institution but also the tool that provides transparency, reminders, accessible history, and ease of use.

Studies on the repeal of CON laws in some U.S. states show that, once these barriers are removed, the number of hospitals increases in both rural and urban areas, suggesting that part of the moat was purely regulatory and not necessarily tied to quality [12]. These findings point to a future in which a greater share of the moat in health and education will come from data quality, service coordination, and UX, rather than mere ownership of regulated physical assets.

Case Studies

Case 1: Too Good To Go – sustainability and network effects as a moat

Too Good To Go started with a simple proposition: connect consumers with surplus food from restaurants and stores at reduced prices. Behind this simplicity lies a complex moat combining sustainability, network effects, and data. Each new store joining the platform expands the geographic and product offering; each new user increases the likelihood of efficiently clearing surplus, reducing waste [6].

The sustainability component is not cosmetic; it is built into the business model. Stores reduce losses and improve their environmental reputation; consumers gain both economic and symbolic value from “saving food.” The brand is associated with positive impact, which feeds the community and generates organic recommendation. The app captures data on pick‑up patterns, schedules, and preferences, enabling optimization of offers and communications. Thus, the combination of purpose, data, and participant network builds a moat that is hard to replicate for retail incumbents addressing waste purely as a logistical problem [6][2].

Case 2: Ecoalf – materials innovation and a global community

Ecoalf has disrupted the fashion industry by basing its portfolio on recycled materials such as fishing nets and plastic bottles. It does not simply “use recycled materials”: it invests in materials R&D, collaborates with international organizations, and has expanded its presence to more than 60 countries [7]. The moat is built in three layers: materials technology, a credible sustainability narrative, and a global community aligned with those values.

Large fast‑fashion groups could copy the design superficially, but replicating the coherence between product, supply chain, and message is far more costly. Consumers perceive Ecoalf’s authenticity compared to more superficial initiatives. Each new collaboration and market strengthens brand recognition and the customer base seeking lower‑impact fashion. The company thus turns sustainability—backed by tangible innovation—into a moat that competes against the traditional advantages of scale and distribution enjoyed by multinational textile companies [7][2].

Case 3: OnTruck – AI and transparency in freight logistics

OnTruck operates as a digital platform that connects shippers with carriers, using artificial intelligence to optimize routes and loads. Its moat does not lie in owning trucks but in orchestrating them better than anyone else. It has managed to expand across several European countries, handling thousands of shipments with notable reductions in costs and emissions [8].

Transparency in prices, timings, and load factors builds trust between customers and carriers, differentiating it from more opaque traditional practices. The system learns from each shipment, improving demand forecasts and routing. As the user base grows, the algorithm gains more data and the network becomes denser, increasing route‑optimization capacity and service reliability. This learning‑ and network‑based moat makes it difficult for analog competitors to catch up, even if they have comparable physical assets [8][2].