Recently, the rapid development of FinTech, or financial technology, has attracted considerable attention within the finance industry. Many observers have welcomed the rise of FinTech, claiming that it has the potential to radically transform financial services by making them less expensive, more convenient, and more secure. However, despite widespread interest in FinTech, little is known about how exactly these new technologies will impact existing financial firms and business models. Do FinTech innovations create value for their inventors? Will new FinTech discoveries help established financial companies reduce costs, increase profits, and better serve their customers? Or, will FinTech innovations enable industry outsiders to compete with incumbents, leading to lower value throughout the industry? Such questions have been difficult to answer until now due to a lack of systematic evidence on FinTech innovation.
In our paper “How Valuable is FinTech Innovation?,” forthcoming in the Review of Financial Studies, we construct a unique dataset of patent filings during 2003-2017 to provide the first large-scale evidence on the occurrence and value of FinTech innovation. Using text-based machine learning methods to identify and classify FinTech patent filings, we estimate their value impacts on publicly-traded firms and industries. Our results reveal that, in general, FinTech innovation creates positive value for innovators, with Blockchain being the most valuable technology type. For the entire financial sector, Internet of Things (IoT), Robo-Advising, and Blockchain are the most valuable. However, some FinTech innovation types can impact particular financial industries negatively, especially when the innovations involve disruptive technologies and come from nonfinancial startups. Market leaders that have invested heavily in their own R&D are able to avoid much of the negative value impact from nonfinancial startups’ disruptive FinTech innovations.
What is FinTech?
Our study requires a clear notion of what exactly “FinTech” is and what real-world technologies the term encompasses. Since no standard definition of the term currently exists, we develop our own broad typology of FinTech. Based on a reading of various articles and reports, we start with the premise that FinTech consists of recently-developed digital computing technologies that have been applied—or will likely be applied in the future—to financial services. Our typology classifies these technologies into seven categories: Cybersecurity, Mobile Transactions, Data Analytics, Blockchain, Peer-to-Peer (P2P), Robo-Advising, and Internet of Things (IoT). The following table lists definitions of these categories along with associated key technologies and real-world examples.
Categories of FinTech
|Category Definition||Key Technologies||Real-World Examples|
Hardware or software used to protect financial privacy or safeguard against electronic theft or fraud
|Encryption, tokenization, authentication, biometrics||Diebold iris-scanning ATM, Mastercard Biometric Card, USAA face recognition login, Experian CreditLock|
Technologies that facilitate payments via mobile wireless devices such as smartphones, tablets, and wearables
|Smartphone wallets, digital wallets, near-field communication||Apple Pay, Android Pay, PayPal Mobile Express Checkout, Venmo, Square|
Technologies and algorithms that facilitate the analysis of transactions data or consumer financial data
|Big data, cloud computing, artificial intelligence, machine learning||Equifax NeuroDecision credit scoring, JPMorgan Contract Intelligence (COiN), Bloomberg Social Sentiment Analytics|
Distributed ledger technologies with a primary application to financial services
|Cryptocurrency, proof-of-work, smart contracts, directed acyclic graphs||Bitcoin, Ripple Payment Network, Visa B2B Connect, Nasdaq Linq asset trading platform|
Software, systems, or platforms that facilitate consumer-to-consumer financial transactions
|Crowdfunding, P2P lending, customer-to-customer payments||GoFundMe, Kickstarter, Lending Club, Prosper Marketplace, Zelle|
Computer systems or programs that provide automated investment advice to customers or portfolio managers
|Artificial intelligence, big data, machine learning||Betterment, E-Trade Core Portfolios, Schwab Intelligent Portfolios, Vanguard Personal Advisor Services|
|Internet of Things (IoT):
Technologies relating to smart devices that gather data in real time and communicate via the internet
|Smart devices, near-field communication, wireless sensor networks, actuators||UnitedHealthcare Motion F.I.T. tracker, Nationwide SmartRide telematics, Travelers Insurance smart home sensors|
Identifying and Classifying FinTech Innovations from Patent Filings
The empirical analysis uses full-text patent filings from the U.S. Patent and Trademark Office (USPTO). We first extract information from the USPTO’s Bulk Data Storage System (BDSS) on 4,680,587 patent applications published between January 1, 2003 and September 7, 2017 and restrict the sample to those applications made by U.S. companies or individuals. In the case of company filers, we use multiple public databases to retrieve additional information on firms’ ages and industry classifications. Next, we use two main steps to identify and classify FinTech innovations. In the first step, we construct a new lexicon of financial terms and use it as a text filter to narrow down the large set of patent filings to 67,948 filings that are potentially related to financial services. In the second step, we employ various supervised machine-learning algorithms to automatically classify patent filings. This process identifies 22,937 finance-related patents, among which 6,511 are FinTech filings classified into the seven technology categories in our typology.
Basic Facts About FinTech Innovation
The constructed dataset of patent filings enables us to document several key facts about FinTech innovation. For instance, we find that public firms, private firms, and non-firm individuals all contribute heavily to FinTech innovation, accounting for 37.3%, 23.0%, and 39.7%, respectively, of all FinTech applications in the sample. We also find that certain types of innovators tend to focus more within particular FinTech categories. Non-firm inventors are important drivers of FinTech innovation in Cybersecurity and Robo-Advising. Public firms are active within most of the seven categories, whereas private firms innovate heavily in Robo-Advising, Mobile Transactions, Data Analytics, and Cybersecurity. Financial firms dominate innovation in Blockchain and IoT, but nonfinancial firms contribute significantly in Cybersecurity, Mobile Transactions, and Peer-to-Peer. Regarding industry-level differences, we find that banking and payments firms dominate nearly all categories of FinTech innovation. Some categories do, however, exhibit narrowly-focused activity by firms operating in other industries. For instance, the asset management industry is the most active in terms of Robo-Advising, and the insurance industry is the second most active with regards to IoT.
The Market Value of FinTech Innovation
To explore the implications of FinTech innovation, we develop a novel approach for estimating the market values of patent filings to one or more publicly-traded firms. The first step in our approach is to predict innovation arrival intensities via regression models that control for the characteristics of patent filers and their filings. We then combine the predicted arrival intensities with observed stock-market responses to patent filing announcements to infer underlying innovation values. Based on this approach, we find that public financial companies obtain economically sizeable benefits from their own FinTech innovation. The median market value to an innovator is $19.7 million (in 2003 dollars). By comparison, non-FinTech financial innovations generate a much lower median value of $2.3 million. Median market values are positive for almost all categories of innovation, with the largest values being associated with Blockchain ($98.1 million), Cybersecurity ($52.9 million), and Robo-Advising ($49.1 million).
We also extend our valuation approach to examine the value impact of FinTech innovation on the overall financial services sector and its key industries: banking, payment processing, brokerage, asset management, and insurance. The value estimates show that, for the entire financial sector, Blockchain, Robo-Advising, and IoT are the most valuable FinTech categories, with median values of $6,053 million, $11,625 million, and $18,348 million, respectively (all in 2003 dollars).
Some FinTech categories negatively impact the market value of the financial sector (e.g., Data Analytics has a median value impact of −$5,862 million), suggesting that certain types of FinTech innovation may open the door to new business models, entrants, and competition that will substantially erode the profits of incumbent firms. We also find that there is wide variation in market value impacts across different technology-industry pairs. For example, the median value impact from Blockchain innovations is significantly positive for Banking and Insurance but significantly negative for Payment Processing. This finding is consistent with the argument that blockchain technology can help banks and insurers improve consumer experience and lower costs, while it may also disrupt traditional payment systems.
Disruption, Competition, and the Value of FinTech Innovation
Why do the value effects of FinTech innovation vary so widely across technologies and industries? To address this question, we focus on FinTech innovations that (1) involve a disruptive technology; and (2) originate with a FinTech startup, which we define to be a young (no more than eight years old), nonfinancial company in our sample. We focus on these types of innovations because they likely present the largest competitive threat to an established industry. In regression analysis, we find that a FinTech innovation is indeed significantly more harmful to industry value when the innovation comes from a FinTech startup and is based on disruptive technology.
Next, we investigate the value impact of nonfinancial startups’ disruptive innovation on different groups of established financial firms: market-share leaders and their rivals. Our results suggest that innovations by FinTech startups are less harmful to market leaders when the underlying technology is disruptive rather than non-disruptive. This finding is consistent with the idea that a disruptive innovation from a FinTech startup can widen a market leader’s advantage over rivals because the leader has greater financial resources and technical economies of scale with which it can pursue its own innovation.
To further explore this possibility, we examine the link between a market leaders’ prior R&D spending and the adverse value impact that the leader experiences from disruptive innovations made by FinTech startups. In our regression analysis, we find that the adverse value impact for a leader is smaller when leaders’ prior R&D investments are larger. For instance, a one percentage-point increase in a leader’s prior R&D intensity is associated with roughly a 16.2 percent reduction in the magnitude of the negative value effect. Overall, the results support our explanation that market leaders’ ability to invest heavily in their own innovation is what helps them to better cope with FinTech startups’ disruptive innovation.
Our study provides the first large-scale evidence on the occurrence of FinTech innovation and the value that it brings to innovators, industries, and incumbent firms. Using a unique dataset of U.S. patent filings by public firms, private firms, and non-firm inventors, we apply text-based machine learning to identify and classify FinTech innovations. To measure the market value such innovations, we develop and apply a new empirical method that combines stock market reactions with estimated innovation intensities. We find that FinTech innovations are generally valuable to innovators and to the financial sector as a whole. However, certain types of FinTech innovation can impact some financial industries negatively, particularly when the innovation comes from a nonfinancial startup and is based on disruptive technology. Market-share leaders that have invested heavily in their own innovation can avoid much of the harm from disruptive FinTech innovation by nonfinancial startups.
The findings of our study have implications for how managers of financial firms can best direct scarce R&D resources to pursue certain types of FinTech innovation or protect against disruptive innovation by nonfinancial startups. Also, our findings show that certain types of FinTech innovation can have positive value effects for some financial industries but negative value effects for others. This suggests that regulators should take into account the varied nature of interactions between industry type and technology type when considering how to regulate FinTech startups. Finally, our findings can provide guidance to venture capitalists and other early-stage investors about how to value different types of FinTech-related intellectual property.