FinTech is Dead,Long Live Finance

Abstract

In this essay I argue that Financial Technology (FinTech) should no longer be taught as a standalone subject in graduate finance programs. A decade ago, dedicated courses made sense when emerging technology use in finance was experimental. Today, it mediates virtually every financial services process, yet curricula maintain an artificial separation that leaves students unprepared for careers where finance and technology are tightly connected. I leverage my experience as a practitioner and educator, designing and teaching FinTech programs since 2016, reviewing program structures at selected business schools, and examining senior finance scholars who already integrate technology into their work. Current university responses typically create separate FinTech degrees rather than integrating technology into core finance courses. I propose a four-step framework for integration: establish financial theory, examine empirical evidence, demonstrate how technology reshapes processes, and explore business model innovations. Team-teaching and professors of practice can address faculty skill gaps. Faculty should adapt courses and institutions need to rethink program structures, moving beyond standalone FinTech offerings toward integration that prepares graduates for finance as it now operates.

Introduction

Imagine a finance professor teaching a derivatives class. A young and curious student spontaneously asks why they study the Black-Scholes formula without discussing the concentrated liquidity mechanisms of decentralized exchanges like Uniswap v3 that also offer option-like payoffs. These blockchain-based trading venues now process billions in volume monthly, so the question is not unreasonable. ¹ Now imagine a computer science professor explaining random forest algorithms in his intro to machine learning course as part of a Master of Finance. Another sharp student asks why they never learn to apply these methods in the context of algorithmic trading. The question is equally valid given that algorithmic trading accounts for over 70% of total trading volume. ² Most curricula fragment knowledge precisely where integration matters most.

I write this opinion piece as someone who helped build FinTech education. Like many colleagues, I championed dedicated FinTech modules when financial technology and novel startup businesses seemed a genuine alternative to established financial services, when robo-advisors were novelties, when blockchain was experimental, when Large Language Models did not exist. We were right to do so, and the data confirmed it: between 2014 and 2016, UK online searches for FinTech-related jobs and education grew by 817% while searches for finance and accounting declined (Sung et al., 2019). My first dedicated FinTech course launched at Singapore Management University in 2016, and similar courses served as essential bridges, helping students and faculty grapple with the promising combination of emerging technologies and business models that seemed to sit outside traditional finance. A decade later, I have reached an uncomfortable conclusion: the category of education we created needs to dissolve into the core finance curriculum.

The evidence surrounds us. American company Circle (NYSE: CRCL) processed USD 1 trillion in monthly stablecoin transactions in late 2024. ³ Aave, a decentralized lending protocol, manages over USD 35 billion in loans without loan officers, relying instead on smart contracts. ⁴ Investment management giants BlackRock and Franklin Templeton tokenize money market funds on public blockchains. ⁵ Machine learning models now drive investment decisions at quant funds managing hundreds of billions of dollars in aggregate. ⁶ What was once experimental is now operational. Yet many Master of Finance curricula maintain a curricular divide offering FinTech courses as if the topic still were a curious addition to finance rather than its operating system. The examples and institutional evidence I draw on reflect primarily well-resourced, globally oriented finance programs in North America, Europe, and Asia. The pace and feasibility of integration will vary across institutional contexts.

Conceptually following Edmans’ (2023) treatment of ESG, this essay argues that FinTech is ”both extremely important and nothing special”. It is extremely important because technology now mediates virtually every financial process, from price discovery to settlement to compliance. Any finance professional must understand it deeply. But it is nothing special in the sense that technology deserves no separate pedagogical treatment; no dedicated courses, no siloed faculty, no distinct career tracks. Treating FinTech as a standalone subject made sense a decade ago. Today the separation obscures connections between finance and technology that students need to see. A derivatives course that ignores concentrated liquidity provision is incomplete. A market microstructure course that omits machine learning is outdated. The problem is not that we teach FinTech, it is that we teach it separately. Research from the field of Education supports this direction. Brown et al. (1989) already argued a long time ago that conceptual knowledge taught in isolation from the activity and context in which it is applied limits learning effectiveness.

The Current Divide

This argument will disappoint two camps. The enthusiasts among us who have built degree programs and hence part of their careers around FinTech as a distinct field will resist its dissolution. They have invested heavily in the narrative that novel business models and technologies represent a fundamental break from how traditional finance operates, requiring entirely new frameworks and dedicated expertise. Traditional finance faculty, meanwhile, will resist integrating related concepts and technologies into their courses. They view FinTech as someone else’s problem, a passing trend best left to computer scientists or a specialized elective lecturer for students with particular interests. In my view, both positions have become untenable. The enthusiasts overstate discontinuity; the core economic principles that govern traditional markets, for example price discovery, liquidity provision, risk and return, to a large extent also govern technology-enabled ones, even if the implementation differs. The traditionalists understate relevance; a graduate who cannot evaluate the risks associated with blockchain-based settlement alongside conventional clearing is not equipped for today’s financial markets. The separation we maintain exists in our curricula but not in the industry, and our students recognize this disconnect even when we do not.

I want to be clear, standalone FinTech programs have delivered real value over the past decade. They created institutional space for experimentation when no other home existed for the topic, attracted students who might otherwise have chosen computer science degrees, and continue to serve a signaling function in the labor market. Employers scanning resumes for technology fluency may quickly pinpoint FinTech graduates. It is also possible that integration and specialization coexist during a transition period, with standalone offerings persisting where faculty capacity for integrated teaching has not yet developed fully. I do not dismiss these arguments. In conversations with colleagues at other Universities, I have encountered candid explanations for why standalone programs persist: deans who have invested reputational capital in marketing them, program teams for whom a new degree is more promising than incremental reform of an existing one, and the practical reality that adjusting established curricula can require as much effort as building something new. These are legitimate institutional constraints. But the signaling benefit of a dedicated FinTech credential is likely transitional: as technology becomes even more embedded across finance roles, it will carry diminishing marginal value relative to a finance degree whose core courses already demonstrate that integration. Moreover, the marketing argument cuts both ways. A business school that comprehensively redesigns its Master of Finance to reflect how deeply modern finance depends on technology and innovation has a distinctive story to tell. Their narrative may resonate more strongly with prospective students than another standalone FinTech degree entering an increasingly crowded market, particularly where such degrees prioritize technology over finance theory. What remains to be settled is whether the separation should persist as the default organizing principle for how we teach finance that is heavily reliant on emerging technologies and continuously evolving business models.

Yet some senior finance scholars already point the way forward. They reject the separation through their integrated approach to research work, and most likely also in their classroom. For example, Bryan Kelly investigates artificial intelligence to asset pricing, demonstrating that machine learning belongs within core investment theory. His work shows how regression trees and neural networks can identify non-linear return predictability patterns that traditional factor models miss (Gu et al., 2020), and that more complex machine learning models consistently outperform simpler approaches in portfolio construction across asset classes (Kelly et al., 2023). Similarly, Katya Malinova and Andreas Park explore how automated market makers, a concept from the world of DeFi, could transform equity markets, a topic that belongs in market microstructure courses alongside traditional order book mechanics (Malinova & Park, 2024).

The Costs of Separation

The costs of this separation are real. Students graduate with fragmented knowledge, learning about collateralised lending in one course and Decentralized Finance (DeFi) protocols in another without necessarily recognising that automated liquidations in blockchain-based lending address the same risk as margin calls in traditional finance. They study corporate governance separately from decentralised autonomous organisations (DAOs), blockchain-based entities governed by token holders, without exploring how token voting rights compare to equity securities (Bongaerts et al., 2025). Resources bridging this gap for finance professionals now exist (Liebau & Oh, 2025), yet curricula have been slow to incorporate them. Students may learn content, but we force course participants to assemble it after graduation rather than assisting them with seeing the holistic picture during their education. A recent survey found that 77% of graduates learned more in their first six months on the job than during their entire undergraduate education, and 96% of HR leaders believe universities need to take more responsibility for workforce preparation. ⁷ While these findings apply to education broadly, the direction is consistent with what financial services recruiters report. Indeed, global financial services recruitment firm Selby Jennings reports that banks now prioritise candidates with data analysis, AI, and digital infrastructure expertise alongside traditional financial modelling skills, yet most finance programmes continue to treat these as separate domains. ⁸

Costs also accrue at institutional level. Business schools face growing competition from computer science departments that offer, for example, blockchain, machine learning, and quantum computing courses attracting students interested in financial applications of these technologies. Such courses often lack discussions on the economics, regulatory depth, and a thorough assessment of opportunities and risks in the finance context, yet students enroll in CS degrees because they perceive technology skills as more marketable than traditional finance theory. The result is on one hand finance students who lack technology skills and, on the other hand, technology students who lack a depth of finance.

Universities have noticed this gap. They have responded to the rise of financial technology by launching dedicated programs, a welcome development that signals recognition of the topic’s importance. Yet the response typically takes the form of separate degrees rather than integration into core finance curricula. Siddiqui and Rivera (2023) propose structuring dedicated FinTech programs around four disciplinary pillars, taking the standalone format as a given rather than questioning it. Imperial College Business School, for example, offers an MSc Finance and a separate MSc Financial Technology as distinct degrees with different curricula and admissions processes. ⁹ At HEC Paris, AI appears as a set of electives within the International Finance specialization rather than integrated within finance courses. ¹⁰ Universities increasingly launch standalone MSc FinTech or MSc Blockchain programs. HKUST offers a dedicated MSc FinTech jointly run by its Business, Engineering, and Science schools, a solid step toward integration. ¹¹ A similar pattern is evident in a related field. Desplebin et al. (2025) find that universities teaching blockchain to accounting students converge on remarkably similar standalone course formats, imitating each other’s offerings to signal legitimacy rather than independently evaluating the best pedagogical approach. I believe more can be done.

Some may argue that universities should concern themselves with advancing knowledge rather than graduate employability. Yet even from this perspective, confronting financial theory with technology and novel methods allows both fields to evolve intellectually, not just practically.

What Integration Looks Like

What would real integration look like in practice? Integration means absorbing FinTech into existing finance courses rather than eliminating it from curricula. To stick to the examples above: a derivatives course would cover Black-Scholes using Uniswap’s concentrated liquidity mechanisms as an example. A market microstructure course would teach how hedge funds and other sophisticated actors use regression trees and other machine learning algorithms to spot opportunities, manage risk, and execute orders. The goal is not to train every finance student as a blockchain developer or machine learning expert, but to ensure they understand how FinTech reshapes the opportunities, risks, and problems they will encounter professionally, and in the right theoretical context. Evidence from a FinTech sub-domain supports this direction. For DeFi, experts expect a convergence scenario, with traditional finance embracing DeFi (Liebau, 2025). If practitioners expect finance and technology to merge, our curricula should prepare students accordingly.

The obvious objection is expertise. Finance professors who brilliantly teach option pricing theory may lack the blockchain background. Computer science faculty who could teach machine learning may lack the finance theory depth to contextualise. This is a legitimate concern, but not an insurmountable one. Where individual faculty up-skilling proves infeasible, collaboration offers a path forward. Team-teaching arrangements between finance and computer science faculty can deliver integrated courses where theoretical depth meets technical implementation. Such collaborations have precedent in other interdisciplinary fields, and are beginning to emerge in FinTech itself. Jackson et al. (2023) describe one such model at Worcester Polytechnic Institute, where a program brings together business, computer science, and data science faculty to co-develop respective curricula. These arrangements allow faculty to learn from each other over successive course iterations. Coordination costs and institutional structures that reward individual teaching make this harder than it sounds, but these are obstacles to manage rather than reasons to avoid integration.

Where team-teaching proves impractical, professors of practice may offer a solution. These faculty members typically combine rigorous doctoral training in finance with often long years of industry experience in executive and sometimes even senior non-executive board-level roles. Their PhD provides grounding in financial theory and empirical research methods; their careers provide firsthand experience driving innovation, managing associated risks, and adopting financial technology. I may be biased here, but this dual expertise makes them well suited to teach courses where finance meets technology.

Both team-teaching and involving professors of practice align with ambitions of some innovative universities that push for cross-departmental collaboration and staying close to industry.

A Four-Step Framework

One approach to structuring integrated courses follows four steps: first, establish the financial theory; second, examine empirical evidence from markets; third, demonstrate how emerging technology reshapes these processes; and fourth, explore business model innovations that challenge existing frameworks.

Consider this example of a market microstructure course. It would begin with foundational theory on price discovery, liquidity provision, and market maker incentives through limit order books. Students would then examine empirical evidence from equity exchanges showing bid-ask spreads, price impact, and trading volume patterns. The technology component introduces algorithmic trading that reduces latency from milliseconds to microseconds, allowing firms like Citadel Securities and Virtu Financial to improve execution quality while maintaining traditional market maker structures. Finally, the business model innovation segment explores automated market makers like Uniswap, where constant product formulas and liquidity pools replace human market makers. Students recognise that both approaches solve the same economic problem, providing liquidity and enabling price discovery, but through different structures. This progression ensures students understand when traditional market making remains optimal and when decentralised alternatives offer advantages.

The pattern is already emerging in practice. At least one Master in Finance program is redesigning its market microstructure course to incorporate digital platforms and FinTech-related topics, doubling the number of sessions to reflect how deeply technology now shapes financial markets. Separately, one colleague teaching financial risk management and banking regulation has begun exploring how to incorporate current technological developments, in particular quantum computing applications to Monte Carlo simulation. These cases reflect a growing recognition among finance faculty that integration is both necessary and achievable.

Similar integration opportunities extend across the curriculum. Appendix A outlines additional opportunities for integration for corporate finance, financial modeling, risk management, international finance, and regulation courses.

Assessment and Implementation

Assessment methods must evolve accordingly. Traditional exams testing memorisation of formulas fail to capture whether students can connect financial theory to its modern implementations. Projects requiring students to evaluate both the economic logic of a financial problem and alternative technological solutions better reflect workplace demands. An international finance assignment might ask students to calculate settlement costs for a cross-border transaction via SWIFT versus stablecoin rails, applying transaction cost theory to both systems. A corporate finance case study could require students to assess whether a security token offering makes sense for a particular firm, drawing on capital structure theory alongside blockchain considerations. These assessments signal to students that mastery means understanding financial principles deeply enough to evaluate any implementation, traditional or technology-enabled.

Implementation need not require wholesale curriculum revolution. Course coordinators can identify where technology naturally fits within current topics and provide resources for integration, including texts that translate FinTech research for finance practitioners (Liebau & Trimborn, 2026). Joint assignments between finance and computer science courses can help students see connections without restructuring entire programs. Generative AI tools can assist both students and faculty in bridging disciplinary gaps more efficiently, though their use requires careful consideration of ethical and other risks. Guest lectures by experienced practitioners who work at the intersection of finance and technology can supplement faculty expertise. The goal is gradual integration that builds faculty confidence and student understanding simultaneously.

None of this is costless. Accreditation cycles impose constraints on how quickly programs can restructure course offerings. Faculty incentive systems that reward individual research output over collaborative teaching make team-taught courses harder to staff. Budget pressures may favor launching a new program with dedicated fee income over redesigning an existing one. These barriers are real and will slow the pace of integration in many Universities. They do not, however, constitute an argument for the status quo. They are implementation challenges that need to be tackled head-on.

Conclusion

To conclude, let’s return to where we started. The students who asked about concentrated liquidity in derivatives class and their counterpart in CS asking about trading in the machine learning course pointed out an obvious gap: the finance they learn in classrooms no longer matches the finance they will most likely practice in their careers. The distinction between traditional finance and financial technology is increasingly a fiction we maintain for administrative convenience rather than intellectual coherence and alignment to the reality that graduates face in the industry. FinTech is now simply a part of how finance operates today. The title of this essay is a challenge. FinTech as a standalone category served its purpose: it created space for experimentation. That era has ended. The task now is integration. Faculty must adapt courses and institutions must rethink programme structures. If we act, we can produce a generation of finance professionals who move fluently between finance theory and the technology, between traditional markets and their digital counterparts. Our responsibility as educators demands that we prepare students for finance as it is, not as it was when our textbooks were written. FinTech is dead. Long live finance.