Fintech: Emerging Trends, Future Directions — An Introduction

Posted January 30, 2019 | | Amplify

Though not always in plain view, fintech is everywhere. It is broadly — and quickly — transforming personal and professional transaction processing of all kinds, at all levels. The list of fintech methods, tools, and techniques includes artificial intelligence (AI), machine learning (ML), cryptography, cryptocur­rency, blockchain, insurtech, smart contracts, regtech, robo-advisors, cybersecurity, open banking, and underbanked services. AI/ML, blockchain, and cryptography are fundamentally changing how money is exchanged and even the form of money itself. There’s a race to adopt fintech for competitive advantage. We ignore it at our own risk.

Fintech is not just another technological revolution. It’s different because it’s technologically so broad and because its application potential is so great. It’s a combinatorial technology where the whole is much bigger than the sum of its parts. It’s also focused on every kind of transaction processing. Consumers, corporations, and governments all benefit from fintech, and they benefit from the unpreventable fintech explosion. It’s one of those technological cases where inevitability meets benefit, where technology adoption will happen regardless of how consumers, corporations, and governments react (even as their lives improve due to the convenience and seamlessness of fintech-enabled transactions).

This issue of Cutter Business Technology Journal (CBTJ) describes the range of methods, tools, techniques, and applications of the fintech revolution. The articles demonstrate fintech’s importance and explore the different levels of fintech technologies, experimentation, and applications. While many questions remain, fintech is unstoppable. Institutions, companies, and whole countries are adopting it for financial, political, and even military purposes. Make no mistake: fintech is a game-changer.

The range of potential fintech applications includes all the vertical industries and nearly every business model and process that enables them. No industry or process is safe from the disruptive impact that fintech will have in the next five years. Keep in mind that fintech will integrate across business and technology architectures, platforms, databases, and applications.

The application range of blockchain technology, for example, is much broader than originally forecast. There are already compelling indicators of extensibility. Prototype platforms and applications have already deployed, venture capitalists are investing in blockchain’s applied potential, applications platforms are in development, and consortia have been formed. Blockchain as a ser­vice (BaaS) is no longer aspirational. The major cloud providers are offering suites of blockchain products and services, as well as other fintech offerings. In fact, there’s competition among BaaS providers to grab as much market share as possible as adoption skyrockets.

All this interest is the result of conceptual and actual applications and the possibilities around transaction seamlessness enabled by blockchain (and other fintech technologies). The ready blockchain domains include at least the following (there are more in queue): financial services (asset management, insurance, payments), smart property (unconventional money lenders/hard money lending, car/smartphone, blockchain Internet of Things), and smart contracts (blockchain healthcare, blockchain music, blockchain government, public value/community, vested responsibility, blockchain identity). In addition, we can expect an evolving blockchain architecture that includes other fintech technologies, especially AI/ML. Intelligent transaction validation — necessary for blockchain scalability — is well underway. In an excellent overview, Karin Flieswasser helps us think about the natural and growing relationship between AI/ML and blockchain: “the combination of AI and blockchain is fueling the onset of the ‘Fourth Industrial Revolution’ by reinventing economics and information exchange. From healthcare to government, the potent combination of both AI and blockchain is slowly but surely transforming industries.”

AI/ML provides intelligent search and analytics, and blockchain provides the secure transaction platform. While fintech is most often associated with financial services, many fintech technologies — like blockchain and AI/ML — are already disrupting other industries.

This extensibility is important to understand. Fintech is a basket of technologies targeted primarily at financial transaction processing. Many of the technologies have their origins elsewhere and have been working in the trenches for years. Fintech has commandeered the technologies, added a few purely from the financial domain, and adapted the technologies for their own (broadly defined) transaction processing purposes. But there are important questions: Where does transaction processing begin and end? Which vertical industries do not depend upon fast, flexible, and secure transaction processing? The application range of “fintech” will continue to grow dramatically, well beyond its initial focus on financial transaction processing.

In This Issue

This installment of CBTJ presents a broad look at fintech technologies, the issues surrounding their development and application, and the applications clearly within their range. It’s an objective look at fintech’s reality and potential. Upon reading the articles in this issue, researchers and practitioners will have a solid understanding of fintech technologies and where consumer and professional transaction behavior will be impacted.

The first article, by Salvatore Moccia, Katia Passerini, and Igor Tomic, focuses primarily on the financial services industry, noting the importance of connectivity, digital assets, and regulation. The authors recognize the opportunities and disruptions that fintech creates. They look at how incumbents must respond opportunistically and defensively to fintech adoption. A key observation is the tension between “stability and innovation,” where change — regardless of how important or impactful — threatens existing proc­esses, platforms, and regulations. The regulatory challenges are especially important since many of the new technologies — particularly blockchain and cryptocurrency — are uncharted and unregulated. Regulations will emerge that will challenge and enable fintech, and technology providers and those who adopt fintech should prepare for alternative regulatory scenarios.

The next article, by Keng Siau, Michael Hilgers, Langtao Chen, Steve Liu, Fiona Nah, Richard Hall, and Barry Flachsbart, looks at data science and AI/ML. These are two of the foundational technologies that empower fintech. They’re foundational because they’re universally applicable and therefore ever-growing. The authors look at data’s role in all fintech transactions. They describe AI and ML as enablers and amplifiers. The financial institutions that adopt emerging fintech technologies (like AI and ML) have a competitive advantage, though there are adoption challenges for even the most adventurous companies. The authors take a detailed look at fintech and marketing and how big data, analytics, marketing, and financial services can be leveraged.

Based on findings from a Cutter Consortium survey examining the adoption and application of AI technology, Cutter Consortium Senior Consultant Curt Hall next looks at AI adoption drivers in banking and financial services. He identifies six: (1) competition; (2) the availability of massive data sets; (3) the growing number of commercial AI-based applications; (4) innovation among the players; (5) a growing understanding and appreciation of the potential of AI, ML, and natural language processing (NLP); and (6) increasingly sophisticated user interfaces and customer experience/engagement. His data reveals the primary foci of applications — banking and financial services — and the range of those applications, which extends from “credit approval, compliance, risk management, research and discovery, and document capture and processing to intelligent virtual agents and chatbots employing NLP and ML for automated customer engagement and self-service applications.” Predictably, fraud detection, wealth management, and the increased use of bots and virtual assistants of all kinds are major targets. The data also reveals the wide deployment of platforms like blockchain into new markets.

Next, Magesh Kasthuri looks at blockchain’s impact on fintech. The article delves into the analysis of a specific technology; perhaps one of the most foundational technologies in the fintech basket. Kasthuri discusses the inevitability of BaaS and its security concerns. Most major cloud providers already provide some level of BaaS, but Kasthuri calls for a full blockchain “utility.” He anticipates the widespread use of blockchain to enable all kinds of transactions, not just ones tied to the financial services industry.

Diarmuid Lane next looks at text- versus voice-based question answering (QA) systems in financial services. He explores a larger question: how efficient are chatbots, really? While the age of NLP-based QA systems is well underway, there are still hurdles in usability, security, and privacy to address. Lane offers a reality check on some of the supporting technologies that enable transaction processing of all kinds. While we’re sometimes a little too eager to adopt new technologies, he reminds us that testing — in this case, usability testing — is a necessary step.

Next, Shivani Raghav, Jari Koivisto, and Frank Michaud raise the digital privacy stakes as they explore how banks could become “identity trust anchors” — and increase revenue as part of the process. Technologies like self-sovereign identity can help with the identity and privacy problem that is ubiquitous on the Web. In fact, KYCaaS (“know your customer” as a service) is a proposed new business model enabled as a new revenue-generating service. This is an interesting look at how fintech technologies, products, and services provide opportunities for companies to profitably commercialize transaction processing.

Markus Warg, Markus Frosch, Peter Weiß, and Andreas Zolnowski next take us into the insurtech platform world and describe how incumbents must adapt their business models and processes to exploit technological opportunities to remain competitive. They suggest that the definition of “platform” can extend from a purely technological definition to a more integrated one, and they explore ways incumbents can benefit from the capabilities insurtech offers.

In the final article, I look at the fintech “arms race,” reporting country rankings in several foundational areas. I explore the areas of AI, blockchain, and cryptocurrency, and how countries are faring in the fintech arms race as measured by their investments in, and adoption of, these three fintech baskets. I also look at their national digital infrastructures. For countries to compete, they must invest in these baskets. If they fail to invest and adopt, they cannot compete in the global fintech arms race, and if they fail to compete in the fintech arms race, they will suffer economically, politically, and militarily.


Fintech is here to stay. The message here is that fintech is broad and will continue to disrupt not only the financial services industry but all industries that rely upon transaction processing — which is all industries! As the fintech community perfects its methods, tools, and techniques, its applicability will expand. Rather than define itself around specialty technologies or limited domains, fintech will become a platform across industries. BaaS (and other service models) will yield to fintech as a service (FaaS), simply because no industry, product, or service exists without transaction process­ing. As fintech technologies evolve and the range of applications expands, FaaS will become an enabling platform for all industries.

About The Author
Steve Andriole
Stephen J. Andriole is a Fellow with Cutter Consortium, a member of Arthur D. Little's AMP open consulting network, and the Thomas G. Labrecque Professor of Business Technology at Villanova University. His specialty areas include digital transformation, emerging technology trends, cloud computing, social media, technology due diligence, software IP valuation, business technology strategy, business technology management, technology governance,… Read More