The Ghost Dossier: How Incumbents and Startups Are Losing (Almost) the Same Trillion Dollars

The crime scene: the day the Excel wouldn’t close

Friday, 8:37 p.m. Investment committee meeting. Flawless PowerPoint, impeccable narrative: “fintech that will break banking,” “healthtech that will democratize healthcare,” “edtech that will kill off traditional universities.” Classic pitch-deck bingo.

Everything sounds good… until we open the consolidated financial model by sector: banking, retail, healthcare, mobility, education, manufacturing. The sum of future market shares, expected margins, and projected TAM doesn’t match macro reality. Value is missing. A lot of value.

This isn’t a formula error. This is a crime scene: in six critical sectors, value is not being captured either by the traditional giants or by the startups that call themselves “disruptors.” A trillion dollars of structural advantage is up in the air, with no clear owner.

My job as a VC is not to applaud the narrative. It’s to identify the real suspect: who truly has the conditions to capture that value in the next 5–10 years—incumbents or startups? And above all, under what terms of collaboration or conflict?

This report is the strategic autopsy of that gap: banking/fintech, retail/ecommerce, healthcare/healthtech, mobility/logistics, education/edtech and manufacturing/industry 4.0, seen not as isolated case studies but as a recurring pattern of missing value.

The origin of the case: how we ended up with a half‑dressed body

The official story is well known: digitalization rewrote the rules. Startups, light and digitally native, attacked slow incumbents burdened by legacy systems, physical branches and bureaucracy. Each sector repeats, with variations, the same narrative:

• Banking/Fintech: branch‑based banks, interest margins and fees vs. purely digital fintech in the cloud, obsessed with UX and payments. As recent analyses note, this tension led to a wave of cooperation: payment agreements, banking as a service, integration of fintech solutions into traditional banks.
• Retail/Ecommerce: physical stores and traditional inventory models vs. B2C, B2B, C2C ecommerce platforms that exploit digital marketing and user data, with omnichannel as a mandatory trend.
• Healthcare/Healthtech: hospitals and clinics focused on in‑person care, paper records or closed systems, versus healthtech built on telemedicine, electronic health records and connected devices.
• Mobility/Logistics: conventional transport operators versus mobility‑as‑a‑service (MaaS) platforms that orchestrate multiple transport modes and optimized routes in a single interface using data.
• Education/Edtech: physical schools and universities, fixed enrollment and programs vs. online learning platforms, modular courses and digital management tools.
• Manufacturing/Industry 4.0: factories with conventional, low‑sensorization processes vs. plants with advanced automation, robots, data analytics and services tied to smart products.

At the same time, AI and generative AI are beginning to reconfigure robotics, supply chains and the energy mix, pushing traditional companies to move, as reflected in reports like those from Capgemini. The sharing economy—Uber, Airbnb and the like—showed that startups can rewrite entire value chains, forcing whole sectors to rearm.

Incumbents react: digitalization, transformation programs, corporate venture capital, acquisitions like Cisco–Meraki, co‑innovation agreements. The big trend of the “winning alliance” between startups and large companies begins.

Up to here, it’s the story anyone can tell at a conference. The problem is what isn’t being said.

The invisible conflict: everyone talks disruption, almost nobody looks at the “missing value”

The systemic mistake is this: in both traditional corporate committees and VC investment committees, people analyze who wins today’s market share, not who captures the value that doesn’t exist yet, but that digitalization and regulation are enabling.

Incumbents think: “How do I defend my installed base?” Startups think: “How do I steal X% of that market from incumbents?” Almost no one asks:

“What part of the customer’s problem remains unsolved by both sides, precisely because of how the relationship between them is configured?”

Regulatory friction, corporate culture, legacy systems, unit‑economics pressure and mutual tech dependence have created something counterintuitive:

• Startups hyper‑focused on features, with fragile business models, unable to capture all the value their own technology enables.
• Incumbents with massively underexploited assets (data, trust, channels) but tied down by structures, regulations and the need to protect the core.

That intermediate space—integrated services, new risk models, dynamic pricing, product‑as‑a‑service, ecosystem orchestration—is where the trillion dollars of missing value accumulates.

Regulation steps in as a key character in the crime: startups use it as a challenge to innovate (“compliance as a feature”), incumbents as a shield and lobbying tool. The result is sectors where:

• Technology could move faster.
• Business models could be much more ambitious.
• User experience could be far more integrated.

But it doesn’t happen, because neither side is structurally designed to capture the whole.

What follows is the systematic examination of the body, sector by sector.

Test bench 1: Banking vs. Fintech

a) Business models: the margin nobody wants to touch

Traditional banking

• Revenues: interest margins, service fees, asset management. Broad, integrated, regulated business.
• Costs: branch network, staff, legacy systems, heavy compliance. High operating leverage, but massive fixed costs.
• Channels: branches + web + app, moving toward omnichannel.
• Intermediation: the classic intermediary. Regulation protects them, but also ties them down.
• Innovation: long cycles; products launched after extended pilots and internal approvals.
• Regulation: high entry barriers. Ability to influence public policy.

Fintech

• Revenues: transaction fees, freemium models, premium subscriptions, revenue share with partners.
• Costs: lean structure, cloud‑native tech, heavy investment in product and digital acquisition.
• Channels: mobile‑first; APIs to plug into third‑party ecosystems (BaaS, embedded finance).
• Intermediation: create new layers (payment gateways, wallets, financial aggregators).
• Innovation: high speed, continuous iteration.
• Regulation: adapt quickly, turn compliance into added value, but with less lobbying power.

The missing value: the integrated regulatory platform model. Banks have licenses and data; fintech have the front‑end and experimentation capacity. What barely exists yet is an architecture where the bank monetizes its “compliance stack” as a structural service and fintech focus on designing radically new products on top of it—not just pretty accounts and metal cards.

b) Technology: the autopsy of legacy

• Banks: monoliths, legacy systems, many patch layers. AI mostly used for descriptive analytics, scoring and some fraud prevention.
• Fintech: cloud‑native, microservices, public APIs, advanced analytics and granular personalization.
• Both are being pushed to integrate AI and automation (RPA, low‑code), but banks do it with the handbrake on, due to cybersecurity and strict regulations.

c) UX: trust vs. friction

• Banks: onboarding still with friction in many markets, heavy KYC processes, mixed support (call center + branch + chat). They win on perceived trust.
• Fintech: fast onboarding, freemium, instant trial, polished app design, mainly digital support. They lose on perception of long‑term stability.

Value gap: financial products bundled around life events, integrated into verticals (health, education, housing) that neither side offers holistically.

Test bench 2: Retail vs. Ecommerce

a) Business models: squeezed margins

Traditional retail

• Revenues: direct sales in physical stores.
• Costs: rent, staff, inventory, traditional logistics.
• Channels: physical core with growing digital extensions.
• Innovation: slow, driven by seasons and collections.

Ecommerce

• Revenues: online sales in B2C, B2B, C2C; marketplace fees; embedded advertising.
• Costs: technology, heavy digital marketing, optimized logistics.
• Channels: web and mobile, increasingly integrated with physical stores (click & collect, etc.).
• Innovation: constant A/B testing, continuous releases.

Missing value: full value chain orchestration: from factory to end customer, with shared demand, stock, price and logistics data. Neither physical retailers nor most ecommerce platforms share data in a way that protects margins for all actors involved.

b) Technology

• Retail: traditional ERPs, POS, poorly integrated inventory systems.
• Ecommerce: digital platforms, behavioral analytics, programmatic marketing.

c) UX

• Retail: rich physical experience, but disconnected from digital.
• Ecommerce: convenient and scalable, but often cold and undifferentiated.

The gap: true omnichannel experiences where user context travels with them between online and offline, with coordinated—not conflicting—pricing and recommendations.

Test bench 3: Healthcare vs. Healthtech

a) Business models: the patient as a fragmented file

Traditional healthcare

• Revenues: in‑person consultations and treatments, procedures, hospitalization.
• Costs: clinical staff, infrastructure, equipment, insurance, heavy regulation.
• Channels: physical centers; little or fragmented digital care.
• Regulation: extreme, with strong influence from big pharma and hospital groups.

Healthtech

• Revenues: telemedicine subscriptions, clinical management software licenses, connected device sales.
• Costs: software development, healthcare certifications, B2B2C acquisition.
• Channels: apps, web platforms, deals with hospitals, insurers and employers.
• Innovation: high, driven by the need to coordinate patient data.

Missing value: the model of continuous data‑driven healthcare. Today, the patient is still treated as an isolated case, not as a longitudinal flow of clinical, lifestyle and behavioral data.

b) Technology

• Traditional healthcare: paper or closed systems, low interoperability.
• Healthtech: electronic health records, telemedicine, wearables, analytics for decision support.

Cybersecurity and compliance are critical on both sides and slow the adoption of more aggressive AI models, though startups generally move faster to adapt to emerging regulatory frameworks.

c) UX

• Incumbents: intense in‑person experience, but with friction around appointments, waiting times, paperwork, payments.
• Startups: more agile access, but perceived as less clinically robust and riskier on data privacy.

The empty space is an “operator of health continuity” that combines traditional clinical infrastructure, integrated data and a seamless digital experience.

Test bench 4: Mobility/Logistics vs. MaaS

a) Business models: the trip as a dead product

Traditional mobility

• Revenues: transport fares, logistics contracts.
• Costs: owned fleet, fuel, maintenance, staff.
• Channels: physical points, call centers, B2B contracts.

Mobility/MaaS startups

• Revenues: platform usage fees, user subscriptions, dynamic pricing.
• Costs: technology, marketing, incentives to drivers or providers.
• Channels: apps integrating different transport modes in one experience.

Missing value: a model where the trip stops being a standalone product and becomes part of a lifestyle or economic activity bundle: mobility integrated with work, leisure, personal logistics, energy (e.g., EV + energy tariff + parking + insurance + maintenance in a single stack).

b) Technology

• Traditional: conventional fleet management systems, little real predictive analytics.
• Startups: real‑time platforms, route optimization, multi‑provider integration.

c) UX

• Incumbents: less flexible booking, less real‑time visibility.
• Startups: everything on mobile, flexible payment options, more transparent experience.

Here regulation (licenses, local rules) sets the pace, and large companies usually have the advantage in shaping it. Startups win on innovation but run into regulatory barriers that can slam shut overnight.

Test bench 5: Education vs. Edtech

a) Business models: captive credentials, underused learning

Traditional education

• Revenues: tuition, recurring fees, public subsidies.
• Costs: physical campuses, teaching and admin staff, regulation and accreditations.
• Channels: physical presence as the core, with digital extensions.

Edtech

• Revenues: subscriptions, individual course sales, SaaS licenses to institutions.
• Costs: technology, content production, user acquisition.
• Channels: 100% online platforms, B2C and B2B models.

Missing value: the model that integrates official credentials with effective, continuous learning. Universities still control certification; edtech controls experience and flexibility. Both leave a huge area unexplored: learning paths aligned in real time with the labor market, validated by performance data.

b) Technology

• Traditional: basic LMS, video tools, legacy admin systems.
• Edtech: cloud platforms, learning analytics, content personalization.

c) UX

• Incumbents: intense in‑person experience, but bureaucratic and rigid schedules.
• Startups: flexible access, more modular experiences, but often less reputational weight.

Here regulation of official degrees and cultural inertia still protect incumbents, even as startups advance as a parallel layer.

Test bench 6: Manufacturing vs. Industry 4.0

a) Business models: products that could be services… but aren’t

Traditional manufacturing

• Revenues: physical product sales (machinery, components, consumer goods).
• Costs: raw materials, labor, energy, equipment maintenance.
• Channels: distributors, direct sales, trade fairs.

Industry 4.0

• Revenues: smart products, associated services (monitoring, predictive maintenance), industrial data analytics.
• Costs: sensors, connectivity, data platforms, specialized talent.
• Channels: B2B deals, industrial platforms, system integrators.

Missing value: the “factory as a service” model at scale—not just a connected machine, but a full outcomes‑based contract where the provider captures part of the efficiency upside and the client reduces CAPEX.

b) Technology

• Traditional: spot automation, low sensorization, minimal OT–IT integration.
• Industry 4.0: IoT, advanced robotics, analytics on production lines, AI in maintenance and planning.

c) UX (for the industrial customer)

• Incumbents: relationship based on one‑off sales and reactive support.
• Startups: value propositions around dashboards, alerts, pay‑per‑use models.

Again, the gap lies in integrating risk, financing, technology and operations in a single package.

The full picture: who’s winning today and who is leaving money on the table?

Winners vs. Losers Scorecard (Forensic Version)

This table is the X‑ray: in almost every sector, incumbents dominate cash flow and regulation; startups dominate technology and point‑level experience. The missing value sits where neither dominates yet: integrated, data‑driven, risk‑sharing models.

Evidence and patterns: what real cases show

Incumbent–startup collaboration is not theoretical:

• In banking, recent analyses show that fintech’s impact on payments pushed long‑term agreements. Banks lean on startups to digitalize products; fintech leverage bank channels and reputation to scale.
• In corporate tech, cases like Cisco–Meraki illustrate a clear route: identify startups with strategic solutions (Meraki in wireless networking), invest, integrate and scale to a major acquisition.
• In manufacturing and traditional sectors like crafts, projects integrating AI (such as recent initiatives covered in the press around design and sustainability) show that tech can reconfigure highly physical sectors if combined with existing assets.
• AI is penetrating robotics, supply chains and energy, forcing legacy firms to move or be displaced.
• Sharing‑economy models (Uber, Airbnb) showed you can build value on assets you don’t own, forcing entire industries to rewrite their regulations and competitive logic.

At the same time, serious cultural tensions are documented in collaboration programs: founders dealing with middle managers with no decision power, corporate timelines incompatible with startup burn, risk of tech dependence when IP isn’t well protected.

And above that, regulation:

• Startups adapting quickly to new regulatory frameworks, even in demanding areas like AI.
• Corporates using size and resources to influence rules, as seen in pharma and other heavily regulated sectors.

This evidence supports the forensic thesis: the crime is not startups killing incumbents or vice versa; the crime is value destruction due to both sides’ structural inability to systematically exploit, together, the new space opened by technology and regulation.

The plot twist: the “Master Plan” both sides lack

As a VC, I don’t care who has the better storytelling today; I care who has an unassailable 10‑year position. That requires a symmetric strategic shift in both incumbents and startups.

1. Rewrite the incumbent–startup contract

The standard model—corporate accelerator, PoC, press release, maybe an acquisition—is broken. It creates:

• Startups leveraged on a single corporate client, with no defenses.
• Corporates buying features, not structural capabilities.

What needs to change:

• Design outcome‑sharing contracts: especially in banking, healthcare and manufacturing. Don’t pay for licenses; pay for improvement in specific KPIs (NPLs, length of hospital stays, OEE on the shop floor).
• Structure agreements from the C‑suite, not isolated departments, so pilots can actually scale.
• Protect IP so that the startup doesn’t get vampirized and the incumbent doesn’t become a hostage.

2. Turn regulation into product, not just a checklist

In sectors like banking, healthcare or AI, regulation is seen as a burden (startups) or a shield (incumbents). That mindset destroys value.

The winning move is to build “compliance‑as‑a‑service platforms”:

• Banks exposing their regulatory stack as a consumable service for fintech.
• Healthcare providers structuring interoperability and privacy frameworks that healthtech can use without reinventing the wheel.
• Large industrials packaging safety, certifications and quality standards as APIs that industry 4.0 startups can leverage.

Whoever controls this layer will set standards and capture structural rents.

3. Move from product to system: design for missing‑value capture

In every sector, the key is the same: stop thinking in product/feature, start thinking in system. A few concrete examples:

• Banking/Fintech: design financial service stacks tied to health, housing, education, mobility. Credit, insurance, payments and savings as invisible parts of a flow, not as standalone apps.
• Retail/Ecommerce: link production, distribution, sales and usage data, sharing value in exchange for transparency. A retailer that just “launches an ecommerce site” is playing to lose.
• Healthcare/Healthtech: go beyond video visits; build continuous clinical traceability where insurer, hospital, physician and patient share incentives.
• Mobility/MaaS: integrate mobility with energy, remote work, leisure and personal logistics. MaaS as part of life bundles, not just a transport app.
• Education/Edtech: integrate learning platforms with on‑the‑job assessment systems so credentials are driven not only by degrees but by measurable performance.
• Manufacturing/Industry 4.0: structure outcomes‑based contracts that include financing, maintenance, upgrades and analytics.

Tactical report: opportunities and risks by sector

5–10 year scenario table

These scenarios are not abstract bets; they align with observed trends in AI adoption, digitalization and incumbent–startup collaboration documented in recent reports and real cases.

Wider scene: cross‑sector patterns the market underestimates

1. Typical startup advantages (when they work):

   • Fast iteration, short product cycles.
   • Focus on UX and frictionless journeys.
   • Heavy use of data and advanced analytics.
   • Low organizational inertia to adapt to new regulations.

2. Typical incumbent advantages:

   • Brand and trust, especially in banking and healthcare.
   • Operational scale and omnichannel distribution.
   • Ability to shape and influence regulation.
   • Access to cheaper, more stable capital.

3. How the gaps are closing:

   • Intense incumbent digitalization to reduce legacy dependence.
   • Corporate venture capital and targeted M&A to bring in external capabilities (Cisco–Meraki is a pattern, not an exception).
   • Structured partnerships, still too tactical and weakly tied to real business KPIs.

4. Where startups tend to be more disruptive:

   • In layers close to the end user (payments, ecommerce, mobility apps, edtech platforms) where digital experience outweighs physical infrastructure.
   • In creating new intermediation layers (marketplaces, comparators, aggregators) that change who owns the customer relationship.

5. Where startups tend to be more complementary:

   • In heavily regulated, capital‑intensive sectors (full‑stack banking, hospital care, heavy manufacturing) where the incumbent still owns structural risk and licenses.

The key pattern: the heavier the regulation and fixed capital, the more true disruption will come from “structured cooperation” or “role reconfiguration,” not direct substitution.

Wide‑angle view: the “Trillion Dollar Bet” memo

Framed as a high‑risk bet, it would be:

Over the next 10 years, at least a trillion dollars in market value will be created in companies whose core model is not “be the next bank/retailer/hospital,” but be the mandatory collaboration infrastructure between incumbents and startups in regulated or capital‑intensive sectors.

It won’t be fintech or banks alone taking the prize, but those who turn:

• Regulation into an API.
• Trust into a protocol.
• Data into a currency of exchange between actors, with aligned incentives and real protection.

If you’re in a large‑corporate C‑suite, your question is not “Do we launch a new app?” but:

• “Which parts of my regulatory, operational and data stack could be a service to third parties, not a sunk cost?”
• “How do I redesign contracts with startups to share risk and outcomes, instead of buying one‑off projects?”

If you’re a founder, your question is not “How do I grab 5% of the banks’/retailers’/etc. market?” but:

• “What structural piece is missing so that incumbents and startups have to use my platform if they want to operate at the speed and compliance the market demands?”

The crime scene is clear: the missing value is not in a better onboarding flow, a prettier UI or marginal automation. It’s in designing systems of forced collaboration, where the cost of staying out is so high that no one can ignore them.

That’s the type of play that justifies serious risk capital. Everything else—isolated features, decorative PoCs, glossy “innovation” press releases—is background noise in the autopsy.

References

1. Spanish Wikipedia, "Tecnología financiera." Context on traditional banking and fintech, and their use of digital technologies and cloud‑native architectures.
2. Spanish Wikipedia, "Modelos de comercio electrónico." Description of B2C, B2B, C2C models and their relationship with retail/ecommerce.
3. Academic article on mobility as a service (MaaS), RIICO. Definition of platforms integrating various transport options.
4. Analysis of differences between business models in fintech, Hispamer. Comparison of traditional banking revenues vs. subscription, transaction and freemium models in fintech.
5. Analysis of digitalization and disruptive business models, Infoautonomo. Impact of ecommerce and omnichannel in multiple industries.
6. Opinion on the relationship between fintech and the banking sector, Cinco Días (El País), 2023. Growing cooperation in payments and other services.
7. Report on the impact of AI and generative AI on companies and sectors such as robotics, supply chains and the energy mix, Capgemini, cited in Cinco Días (El País), 2024.
8. Project on contemporary crafts and AI (Rrrmaker), El País, 2024. Example of revitalizing traditional sectors with digital technologies.
9. Article on disruptive business models (Uber, Airbnb), Realidad Económica. Impact of the sharing economy on transport and hospitality.
10. Analysis of digitalization and challenges for traditional companies, Hispamer. Need to adapt strategy and operations to compete with startups.
11. Fundación Bankinter, "Startups y grandes empresas, una alianza ganadora." Mutual benefits and cultural challenges in incumbent–startup collaborations.
12. Cisco–Meraki case, Squads Ventures. Example of strategic investment and later acquisition to integrate innovative technology.
13. EGADE Ideas, analysis of startup–corporate collaboration. Cultural tensions and alignment challenges.
14. Algoeducation Library, guide to IP protection in tech innovation collaborations.
15. Infoautonomo, analysis of regulatory impact in the AI sector, 2023. Differences in adaptation between startups and established firms.
16. Cinco Días (El País), interview with an AstraZeneca executive on investment in Europe and the regulatory environment in pharma.