The Rise of Fintech. A Regressive Progression?

Contents

Abstract

Introduction

Literature Review
The Nature of Fintech and its Rise
Historical Roles of Fintech and its Evolution

The Present Role of Fintech
Algorithmic Technology in the Financial Markets
Artificial Intelligence in Corporate/Commercial Banking
Technology in Corporate/Commercial Banking
The Effects of Fintech on the Layman
Theories Indicating the Future of Fintech

Catching Up and the Production Models

Bibliography

Discussion
To what extent is Fintech a ‘Regressive Progression’?
Historical Patterns Indicating Progressive and Regressive Traits
Present Patterns Indicating Progressive and Regressive Traits
Progressive and Regressive Tendencies Within Algorithmic Intervention
Progressive and Regressive Tendencies Within Artificial Intelligence in Finance
Technologically Innovative Endeavours and their Progressive and Regressive Natures
Is Central Governance The Answer To Mitigating Regression?
The Essence of this Discussion; What Does The Answer Involve?

Conclusion
The Final Verdict
Suggestive Considerations for The Future

Evaluation

Abstract

Following on from an enquiry and explanation into the essence of the question at hand, this project delves into exploring the nature of Fintech and its rise. This project opens, from the offset, a deep and riveting consideration of this question of Fintech not only being a scrutinization of its tangible impacts – but rather, a question with much more metaphysical bearing.

The cultural, societal and technological impacts of Fintech are deemed pivotal components of this project, and as this paper ventures into the heart of the literature review – decades of scholarly and non-scholarly items of research are synthesised, critiqued and questioned - drawn to reason the impact that Fintech has historically manifest over the course of the previous 150 years – and the literature review begins to open the argument that previous and proven trends in Fintech can be indicatively utilised to project possibilities for future movements in this industry. Transitioning the focus of the project from the historical to the present; the current and most novel developments in Fintech are correspondingly explored. The literature review explores the impacts of three pivotal counterparts of today’s Fintech movements; including Algorithmic Technologies, Artificial Intelligence (AI) and Technological Products, and fashions these explorations in, both, commercial and corporate banking contexts. Strengthening arguments discovered over the course of the review in literature, these present developments within the industry are explored continuously in context of the question at hand, eventually leading us to discover the sheer extent to which each aspect of Fintech had its progressive peaks and regressive troughs. This approach to the review of literature is sustained, as an enquiry and synthesis of informative sources is continued into the context of analysing the impacts of Fintech on the layman, as well as a breakdown of theories indicating the future of Fintech.

The discussion goes on to associate a realm of qualitative reason to each facet of Fintech explored in the literature review. After outlining the rationale behind the question of Fintech’s categorisation as a ‘regressive progression’, the discussion becomes critical of the historical legacy of Fintech, and begins to question what extent the occurrences of former times can be used to predict the forthcoming movements of such a dynamic industry. Present regressive and progressive traits are explored, as the discussion begins to corroborate and refute a wide range of ideological standpoints that were brought alight by proponents of either side of the progressive/regressive divide. Furthering this, a new argument is discovered in the midst of this interrogation – a question of Central Governance. Upon the discovery that the developments of Fintech are inexorable, the nuance of the discussion became focussed not on the prospects of certain developments in Fintech taking place – but rather, a question of condition, environment and attitudes towards them.

It is with this very metaphysical rationale that the conclusion of this project’s findings takes place. This project defines that Fintech is most definitely a progression, if not, a quintessential progression. However, its most novel developments have been castigated by a hindrance of regression that lies innate to all revolutions in history: the eventuality of cultural and industrial opposition. With this in mind, it becomes a question of our own attitudes and response to these regressions: as the industry follows a constant process of adapting to our changing needs, it is important that we, too, adapt to the ever-dynamic outcomes of Fintech.

Introduction

The world of finance is in the midst of captivation; forces of democratisation, liberation and decentralisation have seized facets of the banking world that were once held true for millennia. Empowered by technology, an innate and increasing strive for efficiency has ruptured financial infrastructure in all civilised parts of the world – characterised by a social, cultural and technological revolution: Fintech.

Fintech, in many ways, has sparked something of a Hadean upheaval. Truisms to the world of finance, such as the governance of an industry by industrial-age firms, have been provoked by the very liberal ‘spirit’ of technology; revolving around innovation and reformation. However, with forces of Fintech taking unprecedented rises in global influence and power; this increase in Fintech’s intrinsic binding to the tapestry of the world’s financial system, comes at a cost.

As argued by many sceptics of this global movement, with the seeming ‘progression’ that, in many ways, epitomises the Fintech movement – there are a pervasive plethora of regressive instincts that plague, an otherwise, quintessentially perfect cultural shift. With this pessimistic response to rapid reformations taking place at the whim of Fintech, a dichotomy of two ideologies is manifest. A void now haunts the revolutionaries of Silicon Valley, as they fight to convince conservative ideologues that Fintech is not the ‘regressive progression’ that many deem it to be.

At the heart of questioning the extent to which this liberal rationale is true, one must dissect the collusion of these two independent industries in a macrocosmic fashion. As part of answering this question in such broad context, the history of Fintech is a necessary component of exploration. With the history of Fintech, much contrary to conventional wisdom, spanning over 150 years; it is clear to see that, as we explore this tender void, that the two industries of Finance and Technology may not be as independent as one may initially observe, but rather – these two pivotal industries are crucially inter-reliant.

The intention of this project is to bridge this ‘ideological chasm’; bringing together the differences of, both, conservative and liberal approach towards Fintech – exploring the differences – questioning the impacts – and inexorably, producing a verdict. Although, in anticipation, it may seem that proponents of both rationales may hold a sense of righteousness – the heart of this paper will lie in scrutinising both beliefs with objective and subjective conviction, and inevitably, finding a sense of reason in both points of view.

Bridging the 150 years of Fintech’s history, with the most novel developments of the industry today – the essence of this paper will also be driven by a passion to determine the future of the industry. Observing the lessons of the past, the occurrences of today – the prospects of tomorrow can duly be modelled.

As with all questions of ideology, the heart of reason is powered by the provision and limits of objective and subjective truths. Delving further within this, is the prospect of qualitative and quantitative method employed in order to extract this reason. Economic theory and modelling, accompanied by a very quantitative econometric methodology – we are able to corroborate normative perspectives with positive techniques. The impact of this project will partly be transgressed through this approach, in turn, mitigating the prospects of inauthentic and subjective conclusions.

As we venture on this journey, acknowledge the importance of viewing this paper as an ‘exploration’ more than mere commentary and research on already existent findings. This paper will not only delve into synthesising decades of scholarly research and journals, but will gander across the façade that embodies a very contemporary issue of ours, that is now more applicable to our civilised state of existence than ever before. With this ‘exploration’ comes an associated realm of development; this paper, most namely in the discussion, will present forth an ‘evolution of opinion’ – an ‘evolution’ that will henceforth reach its zenith at the point of conclusion – where the regressive and progressive instincts of Fintech are brought to a close, and the intentions and impacts of this behemoth of a movement, are brought into question.

Literature Review

The Nature of Fintech and its Rise

The fundamental essence of Financial Technology (Fintech) is one that has its root and passion driven by one intrinsic notion: the desire for technological change. However, in a world where technology and its dynamic, metamorphosing and nuanced nature composes the very fabric of our socio-economic existence – the true impact of Fintech and its exacerbating influence is beyond our comprehension, leading to unforeseen changes occurring in fields that were traditionally covered by banks.¹

Like all historical revolutions known to man, very little has come of ‘reinventing the wheel’, rather, Fintech is eponymously crafted out of the rationale that may be characterised as ‘standing on the shoulders of giants’ – with each revolution after the next being a seeming product of a relentless strive to improve the efficiency of the financial world, as soon as technology permits it.²

Fintech has come to represent a new wave of innovation – a titular phase to define the novel technologies that are taking the financial world by storm.³ However, when coming to define Fintech under an objective, umbrella term there is often observed to be a vast and unequivocal subjectivity. The nature of this lies within the idea that Fintech is much more sporadic than one can initially consider. Technological advancements in the financial world are long deemed to be multi-stream and non-linear - as will be discussed as this project progresses. Some of the many fields that Fintech has since come to define are namely: Algorithmic (Algo) Advancements In the Markets, Artificial Intelligence (AI) Powered Finance, Commercial Banking Services and Crypto (Block Chain Assets).

Within all industries that Fintech has come to represent, in very recent times, the hold of these particular industries is becoming ever-more ubiquitous. This is what has come to be known as: ‘The Rise of Fintech’ – a revolution of sorts, expected to democratise financial services.⁴

This so-called ‘rise’ is observed to be a product of a financial system, which as according to Mark Carney (current Governor of the Bank of England), is becoming exponentially ‘resilient with greater diversity, redundancy and depth’.4 This is very much in line with Carney’s subsequent statements that celebrated a world of ‘global trade and portfolio management’, said to be only ‘made possible by new technologies’.⁵ Carney’s statements, despite carrying an unyielding degree of subjective fallibility and speculation, give us a key insight into his rationale towards the matter. His lamentations, in particular those published and recorded in recent years, present the Governor of the Bank of England to be a proponent of the rise of these technologies – but the question lies in what has led to this advocation, and furthermore, how does the support of such pivotal figures in Fintech reflect the nature of this movement’s rise?

This very notion is something that Kellee James, founder and CEO of a market information service and online trading platform, Mercaris (specialising in online agricultural commodities), has described as an inexorable eventuality with the world’s destination towards efficiency, giving her the conjectural hope that ‘the entrepreneurs and technologists in the Fintech sector, will continue to focus on the problems that matter most in people’s lives’, henceforth implying that a movement towards a much more efficient future, will lead to the mitigation of many problems facing the general consensus today.⁶

Synthesising this notion with Carney’s previous points made regarding the ‘Rise of Fintech’ being driven by fundamental technological change, it has become clear that the rationale behind this change is not just the human desire to trivially ponder through in linear progression, but instead, Fintech’s rise seems to be a much more dedicated journey towards a much more efficient future. In a financial sector where the risk of inefficiency can cost millions, and losses can cause destruction to the livelihood of entire populations – the sheer value of efficiency may be far greater than one may initially consider.

Historical Roles of Fintech and its Evolution

Now that the ‘Nature and Rise of Fintech’ has been explored, the basis upon which this rise has occurred is an equally pivotal direction of review. The development of Fintech is a lot more historic than one may initially observe. With the relationship between the financial sector and ‘Information Technology’ stemming back up to 150 years ago – Fintech today, has truly been many years in the making.⁷

The infographic below, created by the Zigurat Innovation & Technology business school highlights, in a very objective fashion, the evolution that has taken place in the world of Fintech. Each key stage of Fintech’s development has been numbered accordingly:⁸

Abbildung in dieser Leseprobe nicht enthalten

Figure 1 – An Infographic on the Evolution of Fintech

Fintech 1.0 (1886-1967) is about the development of the infrastructure of Fintech:

The years between 1886 and 1968 represent the time in history when financial globalisation was first manifest – when the world of finance diverted from being a microcosmic view of mere local economic happenings but, rather, adoptive of much more macrocosmic natures. This phase introduced to the world the whole essence of communicative and global finance, now defining the large and rapidly growing industry of Fintech, worth an approximated US$12 billion in value.⁹ Fintech 1.0 started with technologies such as the steam-powered ships, rail roads and telegraphs that allowed, for the first time in history, cross-border communication of financial information. The most influential advances in this period include the original transatlantic communication wire and Fedwire in the USA (methods of transferring information at optimal speed, being released in 1886 and 1918 correspondingly), and the world’s first electronic fund transfer system, which was utilised through technologies such as the telegraph and Morse code signalling – which are now mostly deemed archaic. At the dawn of the 50s, credit cards were introduced to the world – offering the world’s first alternative to cash payment. Diner’s Club International (an American charge card company) were the first to introduce a credit card in 1950, American Express Company followed suit when releasing their own card in 1958.

This first phase in the evolution of Fintech brought such unprecedented development to the foundation of what Fintech is today. This period of infrastructure made developments such as those mentioned above, truly pioneering in their time. Much of today’s financial world, and therefore, much of our modern existence would not be possible without these fundamental technologies that were implemented at this key stage. The sheer marvel present in this stage of Fintech’s history now dubs this period the ‘phase of financial globalisation’.¹⁰

Abbildung in dieser Leseprobe nicht enthalten

Fintech 2.0 (1967-2008) is about the adoption of Fintech by financial institutions:

Fintech 2.0 represents the shift from manual technologies to more intuitive, digital technologies and is led by traditional financial institutions, such as the many banks that still have their precedence in society today. In 1967, Texas Instruments released the world’s first ever hand held calculator and in the same year, Barclays installed the first ATM in the UK – leading to the commencement of this modern era of Fintech.¹¹ There were various significant technological happenings that were manifest in the early 1970s, such as the establishment of NASDAQ, a stock exchange that was fully digitally automated – paving the way for the solely digital stock exchanges of today and some of the latest manifestations of information technology in the industry.¹² The Society for Worldwide Interbank Financial Telecommunications (SWIFT) was founded in 1973, and it became the first communication information protocol between banks in the world – and still remains the most commonly utilised one to this day. Protocols such as this, facilitate large volume cross-border payments – allowing banks to optimise the costs of making payments, achieving the required level of functionality and reliability that they so intrinsically rely on in the present day.¹³

Online banking was introduced to the world in the 80s, which only exponentially grew in the 1990s when the likes of ecommerce-models (online shopping) came around following the dawn of the internet. During this era, the way that money was perceived (traditionally as something tangible), was altered forever – and peoples’ relationships with large financial institutions became something new entirely. By the beginning of the 21st century, the unseen internal processes of banks and their interactions with proprietary and non-proprietary information, had become fully digitised – the analogue and much more tangible techniques used in finance for 1000s of years, had quickly become displaced by this complete and definitive adoption of more metaphysical, technological techniques.

This phase of complete institutional digitisation ends in 2008, with the Global Financial Crisis causing a spiral of economic turmoil. It is often considered that such an event was only doable on such a large scale with the help of these newly adopted hyper-efficient technological methods - with many believing that Fintech could cause the next financial crisis, due to the sheer extent of its assault on how age-old financial systems have long been able to sufficiently stabilise markets.¹⁴

Abbildung in dieser Leseprobe nicht enthalten

Fintech 3.0 (2008- ) is about new business start-ups:

Following the chaos and havoc caused by the Global Financial Crisis of 2008, in the period shortly after, the nature and causes of the crisis transpired and became apparent. The public became aware that financial institutions, with their non-democratised and conservative nature gave rise to predatory Moral Hazard (a notion that will be explored throughout this paper) – subsequently encouraging wider society to look for alternative financial methods to centralised means. Many professionals out of work following the crash, adopting a new and almost bohemian attitude towards large financial institutions, began to look for ways to make their own retributive mark on the system. Using the power of technology, they have crafted the current era of Fintech, Fintech 3.0, characterised by the accession of new business start-ups within financial technology.

This stage of Fintech is seen to be a product of the emergence of new, alternative means of financial service, in lieu of those in Fintech 2.0, which were long seen to monopolise the financial industry prior to this phase of liberalisation. Bitcoin v0.1, the first version of the infamous cryptocurrency, was released in 2009. This led to surge in the growth of a plethora of cryptocurrencies that now dominate the blockchain market. Although the extent of the future impacts of blockchain technologies (digital ledgering systems) are unknown, the impacts of them will only lead to an increasingly democratised financial industry.

Also following 2008, the smartphone became hugely mainstream across the world, enabling access to the internet for many who had no access to it before. Since 2008, the smartphone has become the primary mode of internet utilisation and interaction with financial services. In 2011, Google Wallet was added to the plethora of financial services accessible via the mobile phone – followed by Venmo’s mobile payment app in 2012 and Apple Pay in 2014. This surge of Fintech as newly founded source of entrepreneurship, has likened it to the Gold Rush of the Wild West, only this time – it may be the future of the financial world that many are trying to get their hands on – and the ‘intrinsically innovative attitudes’ of these newly-manifested Fintech initiatives.¹⁵

Bringing these different sources together, it is clear to see that the evolution of Fintech has truly been, as mentioned earlier, a case of ‘standing on the shoulders of giants’ – catalysed by an ever ‘greater incentive’ to innovate.¹⁶ Each advancement in the industry, has been an encouragement and by-product of each advancement that has come before it. However, there appears to be no time of greater change in the Fintech industry than now. With such mass-penetration in the sector, this almost Darwinian process of technological evolution will only speed up. To review the advancements that are due to take place in the industry, it is key that we get an idea of the nature of Fintech today, and what its present role could indicate about what we could expect ahead.

The Present Role of Fintech

The role of Fintech today is largely observed to be divided into three main attributes: Algorithmic Technologies in the Markets, Artificial Intelligence in Corporate / Commercial Banking and Technology in Corporate / Commercial Banking. These three sectors have come to define what the field stands for today – and these three industries can be thought to have led Fintech to ‘become a much more omnipresent notion’ in our present, and most current stage of Fintech: Fintech 3.0.

Algorithmic Technology in the Financial Markets

Algorithmic technology in the financial markets, is commonly brought under the titular description of ‘Algorithmic Trading’. Algorithmic trading is described most concisely as a ‘process for executing orders utilising automated and pre-programmed trading instructions to account for variables such as price, timing and volume’.¹⁷

To understand this seemingly jargon-filled description of Fintech, one must be able to understand what an algorithm is. An algorithm is most fundamentally a ‘set of instructions to solve a problem.’ Within the context of the financial markets, these sets of instructions are written in the form of code (most commonly in the syntaxes of C++, Java, C#, Python and R)¹⁸ and the problem that these sets of instructions are trying to solve are maximising profit in a relentlessly volatile market, where these factors of price, timing and volume are constantly variable.

However, with this in mind, one could question how computer code, with set and objective parameters could ever control and execute decisions in correspondence to a constantly variable and metamorphosing market situation. The answer to this lies in the root of what one can define as ‘quantitative analysis’, where highly advanced mathematical models and formulae are used in conjunction with previous market patterns and trends, to help predict market movements and execute decisions subsequently.¹⁹

There are many significant advantages to algorithmic trading, as well as many significant drawbacks. The advantages of algorithmic trading are multitudinous, and are described to occur in many fields of practice that are commonly associated with trading.

Firstly, computers are deemed to be faster than humans when it comes to processing and acting on information – a relationship which has been objectively proven.²⁰ Where humans may take hours to retrieve, process and identify decades of previous market trends, the most capable computers can conduct these within a matter of milliseconds. In advanced economies, such as the US, where algorithmic trading makes up 70% of trading volume, there is seen to be significant financial advantage over emerging economies such as India, where algorithmic trading only makes up 40% of trading volume.²¹

Secondly, another advantage of algorithmic trading lies in the fact that there is potential for higher correlation in computers’ trading actions than in those of humans, due to the fact that computers need to be preprogramed and react similarly to a given signal.²² The benefit of this is that, patterns within financial markets that have been proven to work before, are able to be reacted in a profitable way again – without the scope for human fallibility and computational weakness.

However, equally, there is evidently also an equivalent opportunity for algorithmic trading to become a source of disadvantage upon its use too.

In normal conditions, the speed of order execution can be seen as an unequivocal advantage to the user – however, it is clear to see that, without human intervention, high-frequency trading as product of algorithmic execution can be seen to be a disadvantage as well. The flash-crash of 2010 is observed to be a product of the execution of several orders simultaneously without human intervention.²³

Additionally, the idea of liquidity can be seen as a grave disadvantage to algorithmic trading. Financial liquidity is defined as ‘how easily assets can be converted into cash’.²⁴ In the financial markets, financial liquidity is termed as the ability of an investor to purchase a security (tradeable asset) from a seller, and correspondingly the ability of the holder of the bond to sell the asset to a buyer. Much of the liquidity in the financial markets is created through rapid buy and sell orders. These can disappear in a moment, eliminating the opportunity for prior-programmed algorithms to profit off price changes. Equally, the same idea can be applied to the notion that algorithmic trading can also lead to a loss of liquidity too.

Research has revealed that algorithmic trading was a major factor in causing a diminishing of liquidity in currency markets after the Swiss franc discontinued its Euro peg in 2015. Following the crisis, the Bank of England published a paper into how algorithmic trading led to this occurring, decreeing: ‘A key issue raised by the rapid growth of computerised algorithmic trading is how it responds in extreme situations’ and stating that Bank of England analysts determined, ‘this type of trading contributed to the deterioration of market quality following the removal of the cap on the Swiss franc on 15 January 2015’.²⁵ Although the Bank of England has been renowned in the past for its lack of advocation towards non-neutral sentiments, the notion that the UK’s Central Bank is so clearly veering from their neutral culture, could highlight the sheer extent to how objective this particular endorsement of blame could be.

So as all these sources describe, it is ubiquitous and clear to see that as well as having a progressive element to its nature, there perhaps may be a fundamental regression and harm as product of such rapid and unexpected growth in the financial technology industry. The bearing of these two natures of Fintech will serve the basis for the discussion, debate and conclusion further in the paper.

Artificial Intelligence in Corporate/Commercial Banking

The second counterpart of Fintech’s present role is the subsector of Artificial Intelligence (AI) in, both, corporate and commercial areas of banking. Before one looks at the nature of how AI has its impact on both fields of banking, it is critical that one observes what distinguishes the two fields of banking from each other.

The first and most significant difference between Corporate and Commercial banking is the clientele that each field deals with.²⁶ Corporate Banking concerns the services that cater for businesses that are small, medium and large in size – these financial agents are considered institutions rather than individuals. Corporate Banking consists of a world of specialist services that are designed to develop these large-scale businesses and serve their functional needs. Commercial banking, on the other hand, serves the needs and monetary functions of individuals – with small businesses circumstantially falling under the umbrella of Commercial banking.

Another difference is the volume of capital involved with each field of banking. Corporate Banking involves much larger amounts of money, simply due to the scale of revenue brought in by large businesses, accompanied by the sheer scale of loans offered to some of the largest scale businesses. On the other hand, Commercial banking dealing with much smaller individual incomes and mortgages, leads to much smaller sums of money being loaned, deposited and invested by these average consumers.

A final difference between the two fields, is the extent of the variation in financial incentive between employees of both sectors. According to Glassdoor salary statistics (composed of statistics collated by rather speculative samples of workers within particular industries), Corporate Banking salaries can reach up to £130,000 within 5 years of employment²⁷, whilst Commercial banking offers a much more modest average of £30,000 a year.²⁸ As trivial as salary may sound, with the financial world being dominated by monetary incentive and reward, even salary could be a factor that may influence certain decisions that are made in each field of banking.

The ways in which AI impacts each field of banking is very much unique and distinctive in its own way. With the needs and services of each sector being incredibly diverse in their essence, it is only necessary the way that AI impacts both will duly vary in its application.

In its most simple and beautiful quintessence, AI has been described as ‘the study of computations that make it possible to perceive, reason and act’ or ‘the automation of intelligent behaviour’.²⁹ Within the context of each field of banking, the idea of ‘perceiving, reasoning and acting’ become very different processes, given the very different desired outcomes of each field.

In the field of Commercial banking, where clientele is often individual and small-scale, artificial intelligence is most commonly found in the form of Chatbots, ‘Robo-Advice’ and ‘Digital Twins’. More specifically, these forms of AI are applied in the customer-service sector, where individuals are now able to obtain financial advice through programmes that computationally act like human beings.

Much of AI’s impact within the commercial banking’s customer service sector is met largely with positive response by the general consensus. In fact, a recent Accenture survey of 33,000 consumers found that more than 70 per cent were willing to receive computer-generated banking advice. The report made it clear that, “comfort with computer-generated support is growing, bolstered by lower costs, increased consistency and high reliability”, potentially indicating that AI’s hold on the commercial customer service sector will only proliferate.

However, the impact of AI in commercial banking extends far beyond the support that customer service offers in the field. There is a surge in the usage of AI in the commercial payments management field. More particularly, the purpose of AI in the commercial payments sector is to analyse data in search of anomalies. With the sheer extent of payment data in lists, combined with the tedious nature of analysing small batches of information – it is deemed that anomalies within these large data sets would not be able to be identified by even the most experienced human administrators. AI is seen as the best way to tackle this sort of commercial payment data for anomalies. By coding an artificially intelligent programme to check for anomalies, large data streams are able to be fully analysed in a matter of milliseconds, without the nature of the work having any bearing on the thoroughness of the analysis – which is a common problem associated with human interaction in managing such a wide array of tedious and repetitive items.³⁰

In the field of Corporate banking, where everything from the clientele to stores of capital are of much greater scale, the impacts of AI are correspondingly amplified. There is evidently much greater scope for AI to have its impact where there are exponentially greater amounts of decisions to be made, where the vast amounts of decisions are conducted in a state beyond the realm of human computational fallibility.

Some of the many areas where AI is currently dominating Corporate Banking includes:

- Document Digitization: AI is used in the transferring of huge stores of data in paper format to digital format. This assists banks when it comes to the searching and analysing of this data, whilst still remaining within the parameters of regulatory compliance.
- Fraud Detection: In many ways similar to Commercial management systems, whereby AI is used to detect fraud through the analysis of anomalies and use of predictive perception within large streams of data.
- Automated Accounts Receivable With Predictive Analytics: AI is used in predictive analytics within bank administrative systems to check whether accounts are able to charge corporate customer credit cards, or have already been declined and are attempting to carry out the transaction again.³¹

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¹ Romānova, I. and Kudinska, M. (2016), "Banking and Fintech: A Challenge or Opportunity?" Both Inna Romānova and Marina Kudinska are professors within the Faculty of Business, Management and Economics of the University of Latvia – Latvia’s flagship university, with it ranking – as according to most recent university statistics – 7th out of the Balkan states. However, the attitudes of these two professors, in regards to the liberal nature of Latvia and academia as a whole, must be taken into account when considering the neutrality of the source.

² Mr.Dong He, Mr.Ross B Leckow, et al. (2017), “Fintech and Financial Services: Initial Considerations” All the authors within this source are self-titled staff of the ‘IMF Team’. The IMF, or International Monetary Fund, describes itself as an ‘organization of 189 countries, working to foster global monetary cooperation, secure financial stability, facilitate international trade, promote high employment and sustainable economic growth, and reduce poverty around the world’. The fund’s strong emphasis on universal and quite liberal policy, may therefore be a cause of concern when assessing for potential bias that may be present within this academic journal – and others also published by the IMF.

³ Nicoletti B. (2017) Introduction On: The Future of FinTech Bernardo Nicoletti is an Italian academic, and is currently Professor of IT Procurement at the Master in Procurement of the University of TorVergata, Rome, Italy and provides consultancy in Europe and Asia on IT Strategy, Organization and Procurement. He calls his approach to technological innovation as 'Lean & Digitize' and over time has developed a specific methodology as a way to reduce costs and improve quality, bringing value to the world of Fintech. Nicoletti is an example of an academic who has practically endeavoured within the world of Fintech, and henceforth can be deemed as a highly credible source. I will certainly be trusting any of Nicoletti’s sources in the future.

⁴ Carney, M. (2018) Speech on: Promise of Fintech – Something New Under the Sun? Mark Joseph Carney is the current Governor of the Bank of England – the UK’s central bank. When it comes to the nature of economics and the idea of economic future and prosperity – Carney’s knowledge on the matter is deemed nonpareil. However, following Brexit, Carney has been quick to adopt a much more pessimistic view on the future – this could be seen to effect the neutrality of his speeches, given that both which have been quoted have been from after the Brexit referendum.

⁵ Carney, M. (2019) Speech on: A Platform for Innovation See Source 4 for evaluative details on Mark J. Carney.

⁶ Dove, T. (2018) Women of Color Magazine, Vol. 17, No. 1 (SPRING 2018) Very little to nothing can be found on Terrence Dove, the editor of this edition of the ‘Women of Color Magazine’. However it can be taken that the ‘Women of Colour’ Magazine is hugely liberal in its nature – with focus on women and individuals of colour being its primary rationale. It can therefore be assumed that the magazine and its associated interviewees will bear a much more ethical and humanitarian stance to Fintech, therefore disregarding the much more capitalistic and greed-governed aspects that may influence it.

⁷ Arner, D., Barberis, J., Buckley, R. (2015) University of New South Wales Law Research Series, THE EVOLUTION OF FINTECH: A NEW POST-CRISIS PARADIGM? Although cited as a publication and journal released by the University of Hong Kong Faculty of Law, the three authors tasked with the publication of this article are from the University of New South Wales’ Law Faculty. Largely this Australian University is deemed to be a highly prestigious institution, ranking 43rd in the world, according to 2020 QS World University Rankings. The university’s prestigious stance, accompanied by its dedicated and funded research teams, may make it a credible source.

⁸ Unnamed, Evolution of Fintech, Zigurat Innovation and Technology Business School The Zigurat Innovation and Technology Business School describes itself as a, ‘Global Business School focused on Innovation and Technology. Which offers a range of programs, including masters, corporate training and events, tailored to professionals and business’s needs’. The nature of the school, as an independent, free and liberal institution could definitely put the credibility of its statements and information up for question. Only objective information that it has released, has therefore been considered.

⁹ Wang, C. Financial Technology Booms (2015) Little can be found on the journalist Chloe Wang, however the source of the information, Channel News Asia is seen as a left-leaning news channel based in Singapore, broadcasting to 29 territories across Asia and Australia. Singapore is seen as a leader of Fintech, however the questionable political leanings of CNA, could put its statements up for ideological refutation.

¹⁰ Arner, D., Barberis, J., Buckley, R. (2015) University of New South Wales Law Research Series, THE EVOLUTION OF FINTECH: A NEW POST-CRISIS PARADIGM? See Source 7 for evaluative details on these three authors.

¹¹ Lerner, T. (2015), Mobile Payment 3 According to Springer.com, a leading online publication service for academic journals: “Thomas Lerner has been an adviser to banks, telecommunications and industrial companies since the 1990s and works in mobile business/payment in different projects with banks and telecommunications companies.” Given Lerner’s dedicated, prolonged and practical experience in the field – it can be deemed that any of his sources could be seen as highly informed and credible.

¹² Boot, A. W. A. (2016), Understanding the future of banking: Scale & scope economies, and Fintech, in The future of large internationally active banks, Arnoud Boot is professor of Corporate Finance and Financial Markets at the University of Amsterdam, co-director of the Amsterdam Center for Law & Economics (WRR) and Chairman of the bank council of the Dutch Central Bank (DNB). He additionally is the chairman of the European Finance Association (EFA) and directs the Amsterdam Center for Corporate Finance (ACCF), a think tank that seeks to stimulate the dialogue between academics and practitioners. Boot can be seen as quintessentially academic in his nature, and has been commended for his diplomatic nature. The question in terms of credibility lies in: what could encourage his diplomacy to hinder his advocation of truth in his sources?

¹³ Modrzejewski, T. (2014), What are the famous communication protocols used in industrial field? Modrzejewski is a freelance author and poster on Bayt.com, which describes itself as ‘The Middle East’s Leading Job Site’. Although the website itself is clearly credible and trustworthy in its nature – the nature of Modrzejewski’s freelance writing, which is unauthenticated, could possibly jeopardise Bayt.com’s seemingly credible profile.

¹⁴ Dove, T. (2018) Women of Color Magazine See Source 7 for evaluative details on Terrence Dove.

¹⁵ B. Nicoletti (2017), The Future of FinTech See Source 3 for evaluative details on Bernardo Nicoletti.

¹⁶ Mr.Dong He, Mr.Ross B Leckow, et al. (2017), “Fintech and Financial Services: Initial Considerations” See Source 2 for evaluative details on these authors.

¹⁷ J. Chen (2019), Algorithmic Trading, Investopedia James Chen is the director of Trading & Investing content at Investopedia and former head of research at Gain Capital (NYSE: GCAP). For over 20 years, he has been integrally associated with the financial markets as a trader, investor, investment adviser, and global market strategist. His practical experience in the field is nonpareil, and his information may be seen as highly credible in relation to his links with Investopedia – a trustable, online investment advice provision service.

¹⁸ R. Sim (2016), 5 Programming Languages You Should Know If You Are An Aspiring Trader Similar to Investopedia, Dollar and Sense is an online investment advice provision service. However, the difference lies in the nature and background of the authors. Investopedia features certified and authenticated authors, whilst Dollar and Sense features writings mainly from freelance journalists and writers – with Sim being one of these. This pertains a sense of dubiety, when considering the concrete evidence of credibility for this source.

¹⁹ Motley Fool Staff (2017), What is Algorithmic Trading? This source was written by staff of Motley Fool – an organisation which describe themselves as a ‘provider of solutions for investors of every kind’. The website, founded in 1993 by brothers Tom and David Gardner, aims to provide authentic and liberal investment guidance to individual investors. However, since the staff at Motley Fool all supposedly follow this culture of liberal information provision, the nature of the information provided could be debated.

²⁰ ALAIN P. CHABOUD, BENJAMIN CHIQUOINE, et al. (2014), Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market Very little can be found on the four authors tasked with the publication of this academic journal, however by assessing and evaluating the extent of the credibility of the journal that they write for: The Journal of Finance – enough can be gauged regarding the validity of their advocations. The Journal of Finance is an established source for years, I have settled that any future citations to this source are to be deemed credible, although any particular political leanings of the authors should be taken into account.

²¹ Experfy Editor (2017), The Future of Algorithmic Trading, Experfy Experfy describe themselves as ‘data missionaries based in Harvard Innovation Lab, providing human talent to help organizations optimize their hiring of data experts and solutions providers’. The Harvard Innovation Lab has long been known for its credibility and lack of bias, therefore, even though the cited research has been published by an anonymous editor, I still hold a sense of trust in what it advocates.

²² ALAIN P. CHABOUD, BENJAMIN CHIQUOINE, et al. (2014), Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market See Source 21 for evaluative details on these four authors.

²³ J. Chen (2019), Algorithmic Trading, Investopedia See Source 18 for evaluative details on James Chen.

²⁴ J. Mueller (2019), Financial Liquidity, Investopedia See Source 18 for evaluative details on Investopedia. Jim Mueller, much like James Chen is an Investopedia certified author. However, Investopedia is yet to publish a profile on him – this may put his credentials up for question.

²⁵ Francis Breedon, Louisa Chen, et al. (2018), Judgement Day: algorithmic trading around the Swiss franc cap removal Very little can be specifically found about the four authors listed above, however, it is clear to see that as researchers at the Bank of England, the UK’s central bank – any information that is advocated is bound to possess limited bias and/or political influence. The BoE is known for its politically neutral stance.

²⁶ S. Quain (2018), Difference Between Commercial & Corporate Banking Sampson Quain has been described by the Chron, a politically neutral financial advice outlet, as ‘an experienced content writer with a wide range of expertise in small business, digital marketing, SEO marketing, SEM marketing, and social media outreach. He has written primarily for the EHow brand of Demand Studios as well as business strategy sites such as Digital Authority’. The clear extent to his experience is an indication of his credibility, however his endeavours particularly in the world of social media could give rise to his potential political leanings.

²⁷ Glassdoor Salary Statistics (2019), Corporate Banking Salaries Glassdoor is an online information outlet that allows current and former employees of companies to post reviews on their employing firms. One of their additional functions is providing salary insights based on anonymous entries. This is highly refutable and up for debate when it comes to the credibility of these statistics.

²⁸ Glassdoor Salary Statistics (2019), Commercial Banking Salaries See Source 28 for evaluative details on Glassdoor.

²⁹ Stephan De Spiegeleire, Matthijs Maas, et al. (2017), ARTIFICIAL INTELLIGENCE AND THE FUTURE OF DEFENSE: STRATEGIC IMPLICATIONS FOR SMALL AND MEDIUM-SIZED FORCE PROVIDERS The Hague Centre for Strategic Studies describes itself as a thinktank that ‘conducts its activities independently and in collaboration with its large network of affiliated experts’. Its products are described to be ‘diverse: full-fledged reports, issue briefs, quick topic reports, and commentaries in the media. These products often consist of strategic surveys, innovative policy recommendations, trend and scenario analyses, risk assessments, geopolitical and regional security analyses, conflict analyses, operational evaluations and identifications of lessons learned’. Furthermore, it has also been described as a ‘platform for the exchange of ideas and development of new concepts and strategic insights’. All of this, in my mind, deems it as a source that is highly credible, this is strengthened by it seemingly politically neutral stance too.

³⁰ R. Barnett (2017), DOES ARTIFICIAL INTELLIGENCE HAVE A ROLE IN COMMERCIAL BANKING? Russell Barnett is the Chief Technology Officer at Fraedom, a high-tech commercial card provider for banks. The Global Banking & Finance Review is a service that provides a plethora of finance related articles. This outlet is always committed at bringing the most informed authors in – corroborating its credibility.

³¹ N. Mejia (2019), Artificial Intelligence in Corporate Banking – Current Applications Niccolo Mejia covers AI applications across industries at Emerj – an information outlet that is committed at providing online users with free, AI related articles. He holds a bachelor's degree in Writing, Literature, and Publishing from Emerson College. His writings seem very neutral, and there is constant reference to sources in his writings throughout. This makes his writings a highly trustable source.