Finance as social technology

The idea that finance functions as a social technology is not new, even if the exact phrase appears unevenly in the literature. Its foundations lie in several streams of scholarship that converge on a single claim: that financial markets are not self-equilibrating mechanisms governed by the impersonal logic of price, but socially organized systems for managing the radical uncertainty of the future.

The most direct articulation belongs to Beckert (Reference Beckert2016), whose account of ‘imagined futures’ places fictional expectations at the heart of capitalist dynamics. Economic actors cannot know the future, in the Knightian sense, yet must act as though they can. Financial markets solve this problem through the production and circulation of credible narratives, shared stories about growth, innovation, risk, and return that stabilize expectations and enable coordination. Money flows toward projects whose futures have been made investable through socially persuasive representation, rather than toward those an optimizing calculus would select. Finance, in this rendering, is a technology of collective imagination, furnishing the symbolic and institutional infrastructures through which uncertain futures become investable.

Esposito (Reference Esposito2011) develops a complementary argument from the standpoint of systems theory. Financial markets do not predict the future so much as produce a present that incorporates the future as a dimension of current decision-making (see also Doganova, Reference Doganova2024). Derivatives, in particular, function as instruments for binding the present to specific conditional futures. The conception is again that finance constructs a relationship to the future that permits commitment under conditions of uncertainty.

A third strand emphasizes the institutional and professional dimensions of coordination. Analysts, ratings agencies, auditors, and central bankers translate uncertain prospects into standardized or otherwise persuasive assessments (Rona-Tas and Hiss, Reference Rona-Tas, Hiss, Beckert and Aspers2011; Holmes, Reference Holmes2013; Abolafia, Reference Abolafia2020; Carruthers, Reference Carruthers2022). Their authority rests on recognized social position and accreditation rather than superior prediction (which the empirical record rarely supports). Valuation, in this view, is never purely technical. It is an institutionally embedded practice shaped by convention, jurisdictional struggle, and professional culture (Wansleben, Reference Wansleben2013; Ortiz, Reference Ortiz2014; Beunza, Reference Beunza2019). The ‘technology’ of finance thus includes the organizational routines and epistemic communities that stabilize judgement in the absence of determinate knowledge.

These perspectives are united by a conviction that seemingly automatic processes in the economy are nothing of the sort. What economists treat as market efficiency, price discovery, and the discounting of future cash flows are, in fact, achievements of an elaborate social apparatus that renders the future imaginable and manageable. Finance, on this view, is a social technology in the robust sense, a structured arrangement for producing and binding the temporal orientations on which economic activity depends.

One dimension of this view deserves emphasis, because the technofinance thesis confronts it most directly. Finance as a social technology is episodic in its temporality. Coordination occurs through discrete moments of judgement, such as the analyst’s report, the quarterly earnings call, the annual valuation review, and periodic portfolio rebalancing. Between these episodes, commitments hold. Investors wait. Trust, once established, persists until reasons arise to revise it. The temporal grain of finance is therefore coarse, measured in months, quarters, and years. This episodic quality has not been a deficiency of modern finance but a constitutive feature (Poliks and Trillo, Reference Poliks and Trillo2025). It allows for deliberation, for the weighing of competing narratives, and for the slow accretion of institutional confidence that long-term investment requires. Social technologies of coordination presuppose intervals in which social processes can operate.

This characterization remains foundational, and recent scholarship has begun to track what happens to its elements under data-intensive conditions. Studies of machine-driven finance find expertise being rebuilt around data work, model development, and the supervision of learning systems (Hansen and Souleles, Reference Hansen and Souleles2023), while research on expectation formation asks what becomes of narrative when forecasting passes to algorithms trained on past prices (Svetlova, Reference Svetlova2022). We build on such work. Narrative, trust, expertise, and institutional mediation persist, and their reconfiguration is increasingly well documented domain by domain. Our claim concerns the aggregate. Taken together, these reconfigurations amount to a change of regime, in which social mediation is often no longer the primary medium of financial coordination. Something else has moved into the foreground, and naming it requires an analytical register that no single domain study has needed to supply.

The fintech thesis and its limits

The most visible candidate for naming the change is ‘fintech’. This term gained currency in the 2010s and now designates a broad domain of innovation in which digital technologies are applied to the delivery, accessibility, and efficiency of financial services. Mobile payments, peer-to-peer lending, robo-advisory services, algorithmic trading, buy-now-pay-later apps, blockchain-based settlement, and digital currencies all fall within its scope (Maurer, Reference Maurer2015; Bernards and Campbell-Verduyn, Reference Bernards and Campbell-Verduyn2019; Rella, Reference Rella2020; Hayes, Reference Hayes2021; Langley and Leyshon, Reference Langley and Leyshon2021; Tan, Reference Tan2021). Fintech scholarship has produced important insights into how digital platforms reconfigure financial inclusion and exclusion (Aitken, Reference Aitken2017; Gabor and Brooks, Reference Gabor and Brooks2017; Bernards, Reference Bernards2019; Rodima-Taylor and Grimes, Reference Rodima-Taylor and Grimes2019; Brandl and Dieterich, Reference Brandl and Dieterich2023), how algorithmic systems reshape credit assessment and risk pricing (MacKenzie and Pardo-Guerra, Reference MacKenzie and Pardo-Guerra2014; O’Neil, Reference O’Neil2016; Fourcade and Healy, Reference Fourcade and Healy2017; Gruin, Reference Gruin2019), and how the platform economy intersects with surveillance and the financialization of behavioural data (Srnicek, Reference Srnicek2017; O’Dwyer, Reference O’Dwyer2019; Zuboff, Reference Zuboff2019; Sadowski, Reference Sadowski2020; Westermeier, Reference Westermeier2020).

As an analytical category, though, fintech encounters a structural limitation. It frames the relationship between technology and finance as additive. Technology is applied to finance – disrupting incumbents, lowering costs, and widening access – while finance itself remains conceptually stable. The question fintech scholarship typically asks, therefore, is how technology changes the delivery of financial services. Our question is whether the mode of financial coordination has itself become technological. The distinction is not pedantic. By preserving a boundary between the social and the technical, the fintech framing treats finance as a social domain into which technical artifacts are introduced, and so obscures the possibility that a more fundamental change has occurred. If finance has become technological in its mode of operation, the relevant transformation lies not at the level of products and services, but at the level of the coordinative infrastructure through which investment, valuation, and risk distribution are organized.

An analogy clarifies the stakes. To say that newspapers adopted digital distribution, through websites, apps, and social feeds, describes a transformation at the level of information delivery. To say that the public sphere has become technologically constituted – that the formation of public opinion now runs on algorithmic curation and ranking, platform architecture, and automated recommendation – describes a change in the mode by which information itself is coordinated (Pasquale, Reference Pasquale2015; Cheney-Lippold, Reference Cheney-Lippold2017; Fourcade and Healy, Reference Fourcade and Healy2024). For our purposes, the first claim is about fintech; the second is about technofinance.

The recent discourse on embedded finance clarifies the limitation from another angle. ‘Embedded finance’ names the integration of financial capabilities like payments, lending, insurance, and investment, into the digital environments of non-financial platforms, enabled by application programming interfaces (APIs) and Banking-as-a-Service (BaaS) models. It is, in industry terms, the ‘next frontier’ beyond fintech, a stage in which financial services are woven into the fabric of everyday digital interaction, from ride-hailing apps to e-commerce marketplaces to healthcare portals. This centripetal movement toward platform embedding sits in tension with the decentralizing thrust of much recent commentary on alternative finance. Where blockchain-based ‘decentralized finance’, or DeFi, promised to democratize finance by disintermediating traditional gatekeepers through technological assemblage (Campbell-Verduyn, Reference Campbell-Verduyn2018; Hayes, Reference Hayes2019), embedded finance uses the power of centralized platforms to deliver financial services in a seamless and context-specific manner (Langley and Leyshon, Reference Langley and Leyshon2025). The opposition between decentralization and embedding bears on questions of trust, control, and the institutional mediation of financial interaction.

But embedded finance and DeFi, for all their differences, share the limitation of the framing that contains them. They describe new configurations of delivery (who provides the service, through what channel, under what protocol) while assuming that the coordinative function of finance remains unchanged. The embedding of payments into an e-commerce checkout or the disintermediation of lending through a smart contract simply reconfigures access and efficiency. They become more than that only if the infrastructure through which they operate has altered the basic mode by which finance coordinates. The notion of embedded finance unwittingly points toward exactly this. If finance can be lodged into technical environments so seamlessly that it disappears from view, then the conditions of coordination are no longer primarily social, in the sense that they entail narrative, trust, or professional judgement, but architectural, in the ways indicated by interface, protocol, and API. Embedding is a symptom of technofinance (see Table 1).

The fintech framing also tends to treat individual technologies – a particular algorithm, a specific platform, a given protocol – as discrete interventions, which makes the systemic character of the change hard to see. The systemic tendency is not uniform and therefore requires careful articulation. Borch and Min (Reference Borch and Min2023), for example, trace how the spread of machine learning converts automated trading from a collection of hand-coded strategies into an ecology of interacting, self-revising models, a systemic transformation within a single market domain. Vogl (Reference Vogl2022: 24) captures a systemic quality of another kind, describing an ‘alliance of media technology and finance’ in which finance becomes informational and information becomes financial, a convergence and symbiosis that renders information at once the medium and the object of valorization. Technofinance builds on such accounts and pushes them further. It directs attention away from specific technologies within finance, and away from the informational merger that Vogl diagnoses, toward the displacement of social coordination by infrastructural constitution, a process that runs across trading, credit, payments, and investment. We likewise extend Langley and Leyshon’s (Reference Langley and Leyshon2025: 7) notion of ‘fintech disappearance’, or the embedding of finance into ‘the mundane rhythms of technologically enabled socio-economic life’. What disappears, on our account, is not ‘fintech’ as an identifiable market domain, but the primacy of finance in its social mode of operation. Finance is reconstituted through its becoming-technological.

Three dimensions of technofinance

The claim that finance has become technological gains its force through three interconnected dimensions: the infrastructural, the performative, and the communicative. Each marks a domain in which the operative logic of coordination shifts from social mediation toward technical constitution. Together they describe a transformation that is qualitative rather than incremental.

From representation to operation: The temporal logic of technofinance

These three dimensions converge on a shift that can be stated precisely: Finance has moved from a representational to an operational mode of coordination. This shift is most consequential in its temporal register, for it is in the reorganization of time that technofinance has its deepest effects.

Traditional finance, which is to say modern finance, was in the business of stretching time. Its fundamental operation was to connect present resources to possible futures through projections and institutional commitments that held orientation steady across long horizons (Beckert, Reference Beckert2016). A pension fund bought equities because a story about long-run growth made the commitment reasonable. A corporation issued bonds because revenue projections made repayment plausible. A central bank set interest rates because a macroeconomic model made the path of inflation interpretable. In each case, coordination depended on a temporal bridge between present action and future outcome, and the technology that built the bridge, narrative, model, or convention was representational. It produced images of the future persuasive enough to underwrite commitment now.

Technofinance compresses time. Its characteristic operation is the continuous generation of real-time signals that prompt immediate response. Technical infrastructures emit relentless streams of data, prices, volumes, sentiment indices, trending assets, liquidity measures, and risk alerts, all of which are consumed as cues for action rather than inputs to deliberation. What matters in this paradigm is not whether a story about the future persuades, but whether a signal presents an opportunity now.

This temporal compression has significant consequences. First, it changes the cognitive demands on financial actors. In modern-representational finance, the central task was interpretation and imagination. In technofinance, it is pattern recognition and response, the detection of signals within engineered environments and the execution of appropriately-timed action. Interpretation still exists, but it is subordinated to a system built for continuous throughput rather than periodic reflection.

Second, it changes the meaning of valuation. In the finance-as-social-technology view, valuation was an interpretive act, a socially contested assessment of long-run prospects anchored in subjectivity, convention, and professional judgement (Zuckerman, Reference Zuckerman2012; Doganova et al., Reference Doganova, Giraudeau, Helgesson, Kjellberg, Lee, Mallard, Mennicken, Muniesa, Sjögren and Zuiderent-Jerak2014; Muniesa, Reference Muniesa2014; Ortiz, Reference Ortiz2014). In technofinance, valuation becomes an emergent property of recursive technical systems. An asset’s ‘value’ is less a judgement about its long-term trajectory than a function of its current visibility, its liquidity, and its position in platform rankings and algorithmic feeds. Valuation is produced by systems rather than performed by subjects (Hansen, Reference Hansen2021).

Third, it reconfigures risk. Classical risk management built probabilistic models of future contingencies and designed institutions to pool and manage them: actuarial science, hedging instruments, diversification. Techno-financial risk management instead works through real-time monitoring and automated response to individual (un-pooled) claims: collateral triggers, margin calls, circuit breakers, and algorithmic liquidation protocols that fire on threshold violations with minimal human intervention. Risk is processed continuously in the present at fine-grain rather than estimated for the future and classified (Gamerdinger, Reference Gamerdinger2025).

These dynamics are most consequential where the money is – in the institutional core of securities trading. Machine learning systems now scan order flow, news, and alternative data for exploitable structure, revise their own strategies in light of what they find, and execute at speeds that place the entire loop beyond real-time human intervention (MacKenzie, Reference MacKenzie2021; Borch and Min, Reference Borch and Min2023; Borch, Reference Borch2026). Risk controls operate inside the same compressed loop, via pre-trade checks, kill switches, and automated deleveraging that fire on threshold violations in microseconds. Coordination here is not narrated at any point; it is computed, continuously, by systems whose orientation toward the future is a trained disposition rather than an articulated expectation. Nothing about this is marginal. It describes the ordinary functioning of the markets in which most of the world’s tradable wealth is priced.

If machine-driven trading shows the new regime at the system’s core, meme-coin platforms show it at the limit, where the representational mode is displaced altogether. On platforms such as Pump.fun, the entire asset lifecycle, from token creation through price discovery and speculative trading to collapse, is squeezed into minutes. What is striking is not the speed alone, but the operational architecture through which it occurs. The narrative apparatus of traditional finance – the founding team, the business plan, the prospectus, the analyst’s assessment, the earnings projection – are dispensed with and replaced by a stimulus ecology of bonding curves, trending feeds, visceral memes, and live leaderboards that bypasses interpretive deliberation. The asset is triggered rather than narrated. Coordination proceeds through the immediate responsiveness of participants (human and machine alike) to signals that the platform engineers – and not through shared stories about what the asset might become, which in most cases is nothing. The social technology of fictional expectations gives way to a technical impetus of stimulus and response. Such platforms sit at the periphery of financial coordination, and that is their diagnostic value: they show what the coordinative logic looks like when nothing else constrains it.

The old and new regimes often collide, and the collisions expose the seams. In March 2022, a short squeeze in nickel futures drove prices on the London Metal Exchange past $100,000 a tonne, more than doubling in a few hours of overnight electronic trading, as automated margining cascaded through clearing systems faster than the positions behind it could be unwound. Allowing the morning’s trades to stand would have triggered a margin call of nearly $20 billion and pushed a string of member firms toward default. The exchange reached for the bluntest of social technologies. Its officials suspended the market and cancelled roughly $12 billion of already-executed trades, substituting institutional judgement, retroactively, for what the machines had settled (Farchy et al., Reference Farchy, Cang and Burton2022). The episode displays both faces of the present conjuncture at once. Coordination migrates into an infrastructure of automated margining that no narrative could outrun, while the residual authority to override that infrastructure remains lodged in an institution, exercised episodically, defended in the courts on the ground that the market had become ‘disorderly’. Technofinance names the first face. The second is what persistence looks like.

In short, finance becomes technological when the coordination of investment no longer depends primarily on socially persuasive representations of the future but on infrastructural systems that generate, rank, circulate, and operationalize future-oriented signals automatically and at scale. The shift is not from ‘analog’ to ‘digital’ finance, a framing that keeps the old function and merely updates its medium. It is from representation to operation, from interpreting uncertain futures to technologically producing a never-ending series of moments that coordinate, activate, and dissipate.

The architectural power of technofinance

If finance becomes technological in the sense described, then the distribution of power within financial systems is also transformed. This is perhaps the most consequential implication of the technofinance thesis, and it connects the argument to current debates about platform capitalism, digital governance, and the political economy of infrastructures.

In the social-technology regime, power ran along familiar lines. Those with capital could direct labour and investment. Those with expert knowledge (e.g., financial analysts, macroeconomists, rating agencies) could shape legitimacy and expectations. Those in institutional positions (e.g., central bankers, regulators, and exchange officials) could set the parameters of market activity. Power resided with identifiable actors who controlled the narratives, the capital, or the rules of the game. Its distribution was never equitable, and scholars of financial regimes have documented its asymmetries (Piketty, Reference Piketty2014; Godechot, Reference Godechot2017; Tooze, Reference Tooze2018; Alami et al., Reference Alami, Alves, Bonizzi, Kaltenbrunner, Koddenbrock, Kvangraven and Powell2023). But the kind of power was legible, taking the form of discursive authority, capital control, or institutional jurisdiction.

Technofinance introduces a different axis of power, one that corresponds more with the legal and technical design of financial systems. When visibility, liquidity, eligibility, and responsiveness are set by technical infrastructures, those who design, maintain, and govern such infrastructures hold a distinctive form of power (De Filippi and Wright, Reference De Filippi and Wright2018; Yeung, Reference Yeung2018). Platform designers shape who can participate and on what terms. Feed algorithms determine which assets are seen and which stay obscure. Scoring models define who qualifies for credit. Protocol rules govern how transactions settle, how disputes resolve, how value distributes. Interface designs structure attention, frame choice, and set the tempo of action. This is architectural power, a power that works by shaping the technical infrastructures through which coordination takes place. We define it as the capacity to set the terms of coordination in advance, through the specification of protocols, parameters, defaults, and thresholds that determine what a system will see, rank, permit, and execute.

The concept has near neighbours from which it needs distinguishing. Infrastructural power, in the lineage running from Mann’s (Reference Mann1984) state theory into the sociology of finance, is power exercised through infrastructures already in place: central banks that govern by transacting through the plumbing of repo and collateral markets (Braun, Reference Braun2020; Wansleben, Reference Wansleben2023), or narrative authority that travels along the channels built to carry it (Coombs, Reference Coombs2022). It provides scholars with a tool to link the study of financial infrastructure with macro-political debates, but the concept has little to say about the technical constitution of such infrastructure (Coombs, Reference Coombs, Westermeier, Campbell-Verduyn and Brandl2025). Meanwhile, platform power is the positional power of a centrally designed and controlled technical system, typically expressed in economic terms as the rents and dependencies that accrue to whoever controls the bottleneck (Langley and Leyshon, Reference Langley and Leyshon2017; Srnicek, Reference Srnicek2017). Architectural power is prior to both. It is a form of power inscribed into specifications and design choices before any transactions occur, and it persists in artefacts that can bind even those who formally own or operate a system, long after the designers themselves have moved on. Architectural choices made at a specific point in time sediment into the materialities of a financial technology, and facilitate or limit the subsequent agency of both users and owners. Architectural power thus manifests in the design and propensities of a technology or infrastructure. It becomes viable as the agency encoded into the material and technological substrate of technofinance (Westermeier and de Goede, Reference Westermeier, de Goede, Westermeier, Campbell-Verduyn and Brandl2025).

Infrastructural power, platform power, and architectural power overlap in practice, since owners commission designs and standing infrastructures embody past design decisions, but they isolate different moments of the power relation: operation, position, and disposition. What technofinance changes is the weight of the third moment. When coordination is constituted by technical systems, disposition stops being a preliminary and becomes the main event. The decisive moment becomes the one in which designers, engineers, and manufacturers inscribe anticipated behaviours and usage patterns into a technical object or system, giving it a disposition of its own that may resist attempts to use it otherwise (see Akrich, Reference Akrich, Bijker and Law1992).

Two cases make dispositions visible at different scales. When the Investors Exchange (IEX) introduced its ‘speed bump’, a 38-mile coil of optical fibre adding 350 microseconds of latency to incoming orders, it issued no rule, published no judgement, and moved no price. It altered the physics of access, and in doing so eliminated a class of latency-arbitrage strategies that depended on outrunning the exchange’s own price updates (MacKenzie, Reference MacKenzie2021). A design parameter redistributed profitability across the field. Index construction exercises the same form of power at vastly greater scale. The methodological rules by which exchange groups and index providers classify markets and weight constituents steer trillions of dollars of benchmarked investment, so that a reclassification decision functions as capital allocation performed through specification (Petry, Reference Petry2021). Hansen’s (Reference Hansen2025) account of ‘stack inversion’ in automated trading names the condition to which such power answers: as trading systems become layered assemblages of models, data feeds, and third-party dependencies, operational and analytical primacy shifts to the architecture itself. Architectural power belongs to those who write its script.

Nor is the form unique to finance. Across the digital economy, from the rising weight of artificial intelligence and its data centres to new regimes of online advertising and algorithmic curation, influence increasingly operates through design and circumscription rather than authority and coercion (Pasquale, Reference Pasquale2015; Luitse and Denkena, Reference Luitse and Denkena2021; McGowan et al., Reference McGowan, MacKenzie and Caliskan2024; van der Vlist et al., Reference van der Vlist, Helmond and Ferrari2024). Architectural power is frequently invisible to participants, lodged in systems whose workings are opaque. And it concentrates among actors who may sit far from traditional financial institutions – the software engineers, protocol developers, platform architects, and data intermediaries – who rarely face the accountability regimes that govern banks, regulators, or exchanges.

Financial regulation, organized historically around the oversight of institutions like banks, exchanges, and clearing houses, and the policing of conduct like fraud, manipulation, and insider trading, struggles to reach power exercised through infrastructure (Yeung, Reference Yeung2018; Bernards and Campbell-Verduyn, Reference Bernards and Campbell-Verduyn2019). Relevant regulatory objects today include protocols, the design of matching engines, the parameters of scoring models, the rules of platform access, and the logic of feed curation. The frontier of financial governance in this way now lies in technical adjudication, where regulators often lack both the expertise and the jurisdiction to intervene effectively.

The tension between decentralization and recentralization described above sharpens the problem. DeFi protocols claim to replace institutional gatekeepers with algorithmic rules encoded in smart contracts, distributing governance across token-holding communities. Meanwhile, embedded finance consolidates intermediation within a handful of powerful platforms and makes access depend on proprietary API ecosystems. Both redistribute architectural power, albeit in opposite directions, and neither fits regulatory frameworks built for institutional oversight. Central bank digital currencies (CBDCs) are a third configuration, in which monetary authorities take up technologies originally designed to circumvent centralized control. Central banks across the world are now exploring digital currencies for wholesale and retail use, with motivations ranging from financial inclusion to monetary sovereignty to cross-border efficiency (Chey, Reference Chey2026; Chu et al., Reference Chu, Fang and Lai2025). CBDCs in this way show that the co-evolution of financial technology and institutional authority follows no single logic of centralization or decentralization, proceeding instead through contingent negotiations between technical possibility and institutional interest. More fundamentally, they indicate that architecture has itself become a primary site of monetary governance. New forms of money are new financial infrastructures, and their effects depend not only on who issues them but on how they are designed. Unlike traditional currencies, which are simply issued, CBDCs are engineered to enable new relations among public, private, and international actors (Westermeier, Reference Westermeier2024).

Autonomous AI agents in financial environments mark the leading edge of architectural power today. AI agents that manage their own non-custodial crypto wallets have already commissioned work from humans and other AI agents alike with crypto transactions confirmed on-chain, a configuration in which the principals of financial action are software rather than human beings (Hayes, Reference Hayes2026). When AI systems execute trades, allocate capital, and enter smart contracts without human instruction or oversight, the locus of agency migrates from the human actor to the technical system more literally than the performativity literature ever envisaged. The question here is no longer only who designs the infrastructure, but how far the infrastructure has begun to operate on its own behalf. AI-to-AI transactions point to a wider process by which the financial field is increasingly populated with non-human actors that coordinate among themselves, for purposes that need not align with, or be legible to, the humans who originally built them.

This displacement of humans by machines raises problems of democratic accountability that exceed the usual concerns of financial regulation. If the future of finance is no longer merely imagined and interpreted but technologically formatted and enacted, if the range of futures that appear financially thinkable is set by the design of dashboards, the logic of ranking algorithms, and the parameters of scoring models, then the design of financial infrastructure becomes a way of governing futurity in general. Which projects get funded, which groups gain credit, which assets draw attention, and which risks are rendered visible or invisible, are settled by architectural decisions that are rarely open to public deliberation. Technofinance thus poses a problem of accountability that neither the social-technology nor the fintech view anticipated.

A research agenda for technofinance

If technofinance names a real transformation, it also opens a programme of inquiry. Treating finance as technological coordination reframes a familiar question in the political economy of finance. The old question was who controls capital. Technofinance adds a second – who designs the architectures through which capital is coordinated – and the two questions need not have the same answer. Parts of the second question have been answered for particular sites, from exchange groups turned infrastructure providers (Petry, Reference Petry2021) to the layered architecture of automated trading (Hansen, Reference Hansen2025); the task now is to pursue it as a general property of the regime. It is already plausible that the designers of financial infrastructures shape investment patterns more decisively than many of the investors who operate within them. Five lines of inquiry follow.

The first concerns formatting. How do technical infrastructures format financial visibility, eligibility, liquidity, and attention, and with what distributive effects? APIs, scoring models, and ranking systems are some of the natural sites. A second concerns authority. How do platforms and protocols redistribute financial authority away from banks, exchanges, and rating agencies, and toward the engineers, protocol developers, and platform owners whose power is exercised through design? A third concerns temporality. How does the compression of decision cycles reshape valuation, risk, speculation, and the subjectivity of an investor who must now act within environments built for continuous response? Trading apps, dashboards, and at the limit platforms like Pump.fun, are where this is most legible. A fourth concerns persistence. How do narrative, trust, and expertise survive inside technofinancial systems? Reconfigured expertise in machine-driven finance (Hansen and Souleles, Reference Hansen and Souleles2023) and the fate of narrative under algorithmic forecasting (Svetlova, Reference Svetlova2022) mark the path, and the discretionary ‘overlay’ that quantitative managers retain over model outputs offers a concrete, observable site. This question guards the thesis against its own overstatement, and it is where the social studies of finance retain their full purchase. A fifth concerns accountability. What forms of regulation and political oversight are possible when power is exercised architecturally, before any transaction occurs and largely out of public view?

A final issue belongs to the agenda at its outer limit rather than its centre. Technofinance does not abolish human actors, but it may relocate them, from zones of judgement toward those of design, oversight, maintenance, compliance, and residual intervention. Relocation is a tractable claim, and the fourth line of inquiry above exists to test it. Its extrapolation is something else. If coordination can run through infrastructures that generate signals, execute trades, and allocate capital without interpretive deliberation, and if those infrastructures increasingly incorporate autonomous agents transacting with one another through smart contracts (Hayes, Reference Hayes2026; Langley and Leyshon, Reference Langley and Leyshon2026), then human beings may become progressively residual to the process of financial coordination. In this way, a question that philosophers have long asked about technology acquires a new register. Might technofinance contribute to what Anders (Reference Anders2025/Reference Anders1956) called ‘the obsolescence of the human’?

Announcements of human obsolescence have a poor track record in economic commentary, and current evidence – the labour-intensive data work behind every ‘autonomous’ system, the human overlays retained across quantitative finance – counsels scepticism. But the prospect nevertheless informs contemporary discourse, shaping optimistic visions of post-work abundance and autonomous corporations as well as darker ruminations (Amodei, Reference Amodei2024; Bostrom, Reference Bostrom2024; Poliks and Trillo, Reference Poliks and Trillo2025; Milei, Reference Milei2026). How one receives these depends, in the end, on how one reads the history of nihilism (Samman, Reference Samman2026). We do not resolve the question. We instead register it as the empirical horizon of the thesis: the point at which the technologization of finance gives way to a world in which technofinance operates without us. The consequences of crossing such a threshold would not be not only social and political, but anthropological and metaphysical (Baudrillard, Reference Baudrillard2010: 79–82).