Anticipatory FinTech Regulation through Big Data Analytics
Financial Technology (FinTech) blends finance with information technologies. FinTech lies at the heart of disruptive financial services innovation, which comprises the critical infrastructure for modern business and national economic security. All sectors of modern FinTech innovation are data driven – startup finance, commodities and investment instrumentation, payment systems, exchange markets and trading platforms, corporate governance and disclosure, market failure regulation, underwriting and syndication, risk assessment and management, advisory services, commercial banking, transaction settlement through financial intermediaries, and currencies.
Recent FinTech attention focuses on commercial banking, investment risk analysis, and advisory services. However, FinTech innovation historically assumed many forms impacting all sectors of financial services. Our recent paper, "Anticipatory FinTech Regulation: On Deploying Big Data Analytics to Predict the Direction, Impact and Control of Financial Technology," examines FinTech innovation that disrupted, created or destroyed value by redirecting and transforming stocks and flows. Four major technological watersheds comprise the defining technical moments of history’s five FinTech phases: (1) pre-industrial origination phase, truncated by widespread telecommunications, (2) industrial capitalism phase, truncated by machine enhanced calculation and automated record-keeping, (3) computerization phase, ending with the fusion of telecommunications and computerization, (4) information and computer technology phase, possibly evolving into, (5) artificial intelligence, the next phase. The AI phase will require available, well-protected large scale data.
Typically, FinTech is touted as yielding efficiency and opportunity, particularly in transaction processing and analysis, delivered through disruptive disintermediation. Our paper frames the ongoing debate over how laissez-faire approaches are socially beneficial, given enforcement history illustrating which FinTech mechanisms externalize their design flaws causing market failure. Most of the historical watersheds in 20th and 21st century securities and banking regulation demonstrate that FinTech usually deserves a wary eye. Many FinTechs initiate stealth operations then trigger abuse causing side effects through uncertain and incalculable risks. FinTech successfully skirting regulation creates regulatory lag, delay following the initial appearance of novel FinTechs and uncertain later development, assessment, and deployment of reliable regulatory mechanisms.
An anticipatory FinTech regulatory approach is introduced, essentially a predictive, readiness paradigm enabling financial regulators to intercede quickly when FinTechs fail. For example, central banks have long anticipated the impact that competing currencies have on government regulation of the economy. Further, the SECs FinHUB oversight efforts have foreseen blockchain-enabled cryptocurrency violations, another emerging anticipatory development. Unsurprisingly, some FinTechs are government creations, such as Check21 and XBRL. The anticipatory approach also enables ancillary control mechanisms, like private rights of action. Champions of FinTech innovation and FinTech’s skeptics can each benefit from this generalized anticipatory model of FinTech regulation.
FinTech is analyzed here using supply chain scrutiny that permits regulatory, pinch-point deployment of measured control by incentivizing socially useful actions and deterring market failure. Traditional supply chain elements of communications, documentary instruments, trading platforms and exchange markets, transmission, and intermediaries directly apply to most FinTechs. Various regulatory modes are examined enabling the stacking of controls - from ex-ante ethical norms, market discipline, private-sector self-regulation, and voluntary standards to the effectiveness and political acceptance of ex-post liability remedies.
FinTech is often developed as inventions, touted as socially-useful innovation and defended as essential social progress. For example, FinTechs have been represented as patentable trading platforms, exploited exclusively in stealth payment networks, dominated by owners of trademarked financial instruments, manifest as trade secrets (algorithms) or otherwise embodied in intellectual properties under business method patents, proprietary databases, and trademarked financial products and services. FinTech cannot be analyzed, understood or effectively regulated without acknowledging an increasing reliance of FinTech innovators on layers of IP in the deployment of payment systems, trading market innovations, trading strategies, risk management and insurance, underwriting, and P2P schemes.
Our paper demonstrates the above, then signals future research opportunities, illustrating how most FinTech innovations, scholarship and public policy development are significantly informed by big data analysis. Big data is essential in balancing three essential societal functions: (1) an innovator focus - innovation incentives to design, develop and deploy FinTechs, (2) a research focus – develop and refine diagnostic and forensic analysis of FinTech impacts, primarily to enhance understanding through market failure forensics, and (3) public policy response focus – the development and deployment of minimally intrusive but effective regulation of FinTech’s negative externalities while encouraging FinTech’s positive societal externalities.
John W. Bagby - The Pennsylvania State University
David Reitter - Google AI