FinTech Is an IS Problem Disguised as Finance

I was scrolling through an upcoming fintech conference agenda last week when one panel stopped me. The description promised to explore how open banking APIs act as catalysts for financial innovation. I read it twice. They were describing boundary resources. Ghazawneh and Henfridsson (2013) defined boundary resources as the tools, interfaces, and rules through which a platform owner coordinates complementors while keeping control. Mayer et al. (2025) recently showed how generative AI is stretching that concept; outputs become harder to standardize, validation gets harder, and complementor skills have to evolve. An open banking API does exactly the same thing in a narrower domain. It lets a fintech startup plug into a bank's core infrastructure, access customer data with consent, and build a complementary product. The bank sets the rules, controls the rate limits, and decides which endpoints stay open. That is not a finance breakthrough. It is platform governance with a suit and tie.

Finance journals keep publishing papers on open banking ecosystems without citing platform governance research. They discuss API adoption rates, data-sharing consent frameworks, and competitive dynamics as if these were uniquely financial phenomena. They are not. The theoretical work was done in IS. Wessel et al. (2025) frame GenAI's impact on digital platforms through intelligent automation and boundary-resource transformation. The logic applies just as cleanly to a payment rail releasing new developer endpoints as it does to a content platform releasing a generative writing tool. The resource mediates between the platform owner and the complementor, and governance evolves as the resource changes. When a regulator forces a bank to open its APIs, the bank becomes a platform owner overnight. Its competitive problem shifts from raising deposits to managing complementor quality. That is an IS identity problem, and it is sitting in the finance section of the library.

RegTech offers an even clearer case. Startups in that space sell software that automates compliance reporting, anti-money-laundering checks, and regulatory filing. Finance scholars describe this as efficiency gains from regulatory technology. I look at it and see DiMaggio and Powell (1983). Institutional theory explains why organizations converge in form and practice through coercive, mimetic, and normative pressure. Coercive isomorphism arises from external regulatory pressure; the bank does not choose to report suspicious transactions in a certain format because it is optimal, but because the regulator demands it. Mimetic isomorphism explains why one bank buys the same transaction-monitoring stack that its peer just bought; uncertainty about regulatory expectations drives imitation. Normative isomorphism explains why compliance officers with shared professional certifications push for the same audit trails across competing institutions. RegTech is institutional isomorphism encoded in Python and sold as a service. The finance literature discusses it as cost reduction. The IS literature already has the explanatory framework, and it explains the why, not just the how much.

I have written before about why governance theater performs rather than protects; RegTech is different. It is not theatrical in the fake sense. It is institutional isomorphism with a sales deck. The real value of the software is not the code. It is the signal that the organization is doing what regulators and peers expect. That signal is exactly what DiMaggio and Powell theorized.

Decentralized finance, or DeFi, looks like disintermediation, and disintermediation is a transaction cost story. Williamson (1975) argued that organizations choose between markets and hierarchies to minimize transaction costs, with asset specificity, uncertainty, and frequency determining the efficient boundary. Banks exist in part because they reduce the transaction costs of trust, settlement, and enforcement in financial exchange. Smart contracts on a blockchain reduce those costs algorithmically, which shifts the efficient boundary away from hierarchical intermediaries toward automated markets. Gurbaxani and Whang (1991) sharpened the IT version of this argument by separating the effect of information technology on internal coordination costs from its effect on external transaction costs. The direction of the boundary shift depends on which cost falls more. DeFi lowers external transaction costs, search costs for counterparties, bargaining costs over terms, and monitoring costs for execution, by replacing human intermediaries with code. The result is not a new economic miracle. It is a shift in governance choice predicted by transaction cost economics. Finance papers celebrate this as a novel market structure. Williamson and Gurbaxani and Whang laid the groundwork decades ago, and the same boundary-shift logic runs through the IT business value debate.

Payment systems are perhaps the most obvious example. Visa, Mastercard, Alipay, Stripe, and every modern central bank digital currency pilot operate as two-sided platforms. They bring together distinct user groups, generate network effects, and rely on complementors (merchants, developers, wallet providers) who extend the core functionality through standardized interfaces. The platform owner sets governance rules. Complementors invest in platform-specific assets. End users generate network effects. The terminology in a payment systems paper will talk about interchange fees, liquidity, and settlement risk. Strip away the finance vocabulary and you are reading a platform governance study. I wrote about why platform theory belongs in IS, and payment systems are the proof.

The pattern bothers me because it is not just cross-disciplinary borrowing. It is asymmetric borrowing. When IS researchers study a financial platform, we cite Williamson, DiMaggio and Powell, and Ghazawneh and Henfridsson because our field rests on explicit theoretical foundations. When finance researchers study the same platform, they often treat the organizational and technological infrastructure as a black box wrapped in finance jargon. They measure outcomes with familiar variables, returns on assets, spreads, default rates, without theorizing the IT artifact that produces those outcomes. Benbasat and Zmud (2003) warned that the IS discipline drifts when it stops centering the IT artifact. I think the reverse is also true: when other disciplines use the IT artifact without theorizing it, they produce flattened explanations that miss the mechanisms. Finance is currently running a large natural experiment in flattened explanation.

I am not saying that finance has nothing to add. Pricing risk, portfolio optimization, and macro-prudential regulation are genuinely financial questions. But when a paper is about how banks adopt APIs under regulatory pressure, how compliance software drives organizational similarity, or how smart contracts replace intermediaries, it is not doing finance. It is doing IS while wearing a finance name tag. The theories we have, platform governance, institutional isomorphism, boundary resources, and transaction cost economics, were built for exactly these problems. The only missing ingredient is the willingness to call the work by its proper name.

Next time someone pitches me a disruptive fintech idea, I will ask which IS theory they are wearing as a costume.