Author Archives: TBR Team

What Anna Delvey’s Ankle Monitor Can Teach Us About Marketing Strategies

Chloé Asconi Feldman

At this stage, it is unlikely that one is active online or in the pop culture sphere without knowledge of the convicted con-artist-turned-socialite Anna Delvey. Recently making her debut on Dancing with the Stars with her bedazzled ankle monitor, Anna Sorokin, known familiarly as Anna Delvey, is known for posing as an upper-class heiress to the New York elite and swindling hundreds of thousands of dollars, eventually finding herself in jail for almost four years on the charge of grand larceny. Despite her criminality, Anna Delvey has been taken on by the general public as a new socialite, featuring on magazine covers and even gaining support from the “Eat the Rich” movement. The narrative surrounding Delvey is fascinating in itself, but her recent rebrand from con to dancer can also offer valuable insights into effective marketing strategies.

Scheming to Streaming: Swindling Scarcity

I had never given much thought to the television series Dancing with the Stars, but upon learning that Delvey would feature in the upcoming season, I found myself suddenly intrigued. This is because Delvey holds an air of alluring exclusivity; with her jail time and limited public appearances, seeing her on a television series increases the appeal of tuning in and engaging with show material. This phenomenon resembles the scarcity principle of marketing, a strategy where marketers urge customers to engage with a good or service based on its finite nature, whether numerically limited or seasonal. 

A brand notorious for its scarcity marketing is Hermès and its infamous Birkin bag. Social media frequently showcases celebrities carrying their Birkins as everyday bags; however, if one tries to buy one in a Hermès store they are met with a waiting list with an indefinite length. This scarcity of the product is what makes the Birkin so notorious, compared to other high-end designer bags – consumers are willing and able to wait to obtain a status indicator. This technique encourages customers to buy a product or service because it feels exclusive. In the case of Delvey and her limited public appearances, this comes in the form of television viewership.

Influencer Marketing: Controversy or Commonality? 

As controversial as she may be, Delvey proves once again how successful influencer marketing can be. Reaching just over a million followers on Instagram, the brands that Delvey partners with inevitably reach a wide audience. Yet what differentiates Delvey from other influencers is her status as an ex-con artist and her blurry public image. What makes influencer marketing especially differentiable is when an influencer with an indefinable allure posts about a product, compared to the typical state of the influencer world, which is plagued with fast-fashion and superficiality. 

As a brand, choosing Delvey to promote your product may seem controversial and ill-advised as she is an ex-con artist, but there is no denying the reach and influence that her posting about products would have. By simply bedazzling her ankle monitor, the concept has gone viral on social media with many claiming Delvey as their Halloween costume inspiration. By crafting a sensationalist, American-dream presenting image, Delvey stands out among influencers and those interested will seemingly follow along. 

Embracing Infamy: Brand Personas

Another marketing strategy that Delvey has executed to improve her personal brand is by embracing her controversy rather than ignoring it. While her story went viral when she was arrested in 2017, the Netflix series Inventing Anna, which documented the story of Delvey and her arrest, made it practically impossible to know about Delvey without associating her with scamming, scandal and fraud. Instead of shying away from this track record, Delvey’s Instagram bio states, “this is not financial advice”, and her bedazzled ankle monitor seems to embrace her criminal past rather than sweeping it under the rug. 

This strategy is nothing new to the world of brand management; in recent times, companies are more willing to face their criticism head-on. Ryanair for instance is a champion in the social media sphere for being bold and abrasive when considering promotion and CRM. However, this has only augmented the attention the airline receives over social media, as their cavalier remarks are in line with the brand’s persona – bare, no-frills and to the point. For Delvey, the choice to lean into and accept her criminal past creates a more authentic personal brand that invites discussion and publicity, whether good or bad. Whether talking about a convicted conwoman or an airline, there is truth in the effectiveness of using humour and marketing to address criticism rather than sugarcoating it.

Overall, Delvey’s rebrand –and her ankle monitor– offer insights into contemporary marketing strategies. She has been able to maintain the spotlight while capitalising on her controversial past and creating a personal brand, whether you love it or hate it. By using influencer partnerships, the principle of scarcity, and embracing her past, Delvey has demonstrated that even the most unexpected elements may play a significant role in the marketing narrative, including a bedazzled ankle monitor and a dance routine.

Leveraging AI in Digital Marketing

Anirudh Singh

As technological and social advancements sweep the globe, the digital marketing industry is expanding rapidly. Every day new developments in the industry appear, and artificial intelligence is no exception. AI has revolutionised the path for digital marketers; by leveraging AI in digital marketing, professionals can employ data-driven strategies, enhanced personalisation and customer targeting, improved efficiency, and cost-effectiveness, gaining real-time data insights for campaigns. Therefore, understanding the role of AI in digital marketing has become incredibly significant not only for marketing professionals but also for firms to gain a competitive edge.

Artificial Intelligence: A Background

Before delving into the application of AI in digital marketing, it is first important to highlight its history. Putting it in very colloquial terminology as many know, AI is a form of technology that has the potential to think and act like humans and complete assigned tasks in mere seconds– those which humans may take hours to complete. The evolution of AI in digital marketing is not an earth-shattering development; the phenomenon can be dated back to the 1950s when researchers applied linear programming and game theory concepts to predict consumer trends, transforming into neural networks in the 1970s. In the late 1990s and early 2000s, the boom of the Internet and E-Commerce opened the door for online marketing and advertising. From 2010 onwards, the advancement of machine learning, big data, the Internet of Things, and SAAS have changed digital marketing algorithms completely; now, marketers can leverage AI such as Chat GPT, Copilot, and many other AI-driven tools to complete tasks that would previously require many hours of labour.

Impact of AI in Digital Marketing

The impact of AI in digital marketing is very profound and visible in nearly every corner of the industry. For instance, AI has impacted the process of social listening and target marketing, especially using software like Emplify where marketers garner insights and data under one roof to streamline data management. Similarly, for search engine optimisation and content creation, AI can extract metrics from search engine databases in turn helping in the creation of content for target audiences. To enhance effectivity, AI also has a profound impact on email marketing and paid Google, Meta, Instagram and LinkedIn advertisements by formulating crafted content to audiences via optimisation of ad bidding strategies based on factors like behaviour, device type, and location. 

Benefits of Using AI in Digital Marketing

Before discussing the challenges and ethical considerations of the technology, it’s important to discuss the benefits of using AI in digital marketing. As much of the industry is aware, AI has many benefits for digital marketing; some of the most significant, however, are as follows. All of these benefits need to be properly acknowledged before a deeper discussion on the topic moves forward.

Prediction of Client Behaviour

For any business to grow, it is incredibly important to understand the behaviour of its client. Here, AI plays a vital role by making these efforts simpler and more cost-effective for marketers. AI tools can use statistical decision trees to understand customer behaviour, review past data, and suggest the best marketing strategy for marketers to better understand current and potential consumer patterns .

Customer Engagement

Understanding customer engagement is a challenging task for any marketer or agency;  it is frequently said that customer acquisition cost is far more than retention cost. Using AI-driven tools, marketers can scope out which customer segments they have to target to get the maximum acquisition. AI can also help them to track what each customer wants based on behavioural patterns, thus providing a blueprint for effective engagement that appeals to emotions.

Target Audiences

Selling a good or service to an unknown consumer is a very challenging and frustrating task. Traditional marketing saw the analysis of data and consumer preferences manually to target customers and sell their products; however, with the advancement of AI targeting customers and strategically segmenting them has become less time-consuming and more cost effective. Seemingly, all marketers need to do is feed their consumer data into AI which in turn generates tailored content, preferences and strategies to target the different segments who are interested in buying the product, thus broadening possibilities for marketers to strategise. 

Automation of Repetitive Tasks 

AI not only helps marketers and companies to engage the customer and target audiences but also helps to automate repetitive tasks. Through AI, marketers now automate pay-per-click (PPC), content for email marketing, search engine optimisation (SEO) and potentially social media content, which could have been traditionally laboursome and repetitive prior to AI’s initiation.

Customer Relations

Customer Relationships are all about loyalty and customer support, and AI has proven itself a strong candidate in maintaining these relationships. With AI assistance companies can gauge customer relationships that would require human capital traditionally. For instance, many companies have employed AI as the preliminary feature for aiding consumer queries in a format similar to texting. Although beneficial for cutting costs in many regards, employing AI for managing customer relations must be dealt with in a conscientious manner, as consumers often prefer human contact and possess queries that go beyond the scope of artificial means.

Overcoming Challenges and Ethical Considerations

One of the biggest challenges with AI’s use in marketing is the issue of transparency. In 2018, Amazon came under backlash when its AI recruitment platform collected the details of male and female candidates and favoured male candidates. Later on, Amazon relinquished that particular AI tool, but its use raises questions about transparency and bias in recruitment. If companies are using AI to collect data, they should remain transparent and inform people well ahead in advance about the purpose and application of their data collection.

Another challenge of using AI is privacy. Before collecting data to be used by AI, customers have the right to know how their data will be used and if they want to step out from this data collection. For instance, in 2020 Google was under attack when it collected the details of children under the age of 13 from YouTube without their parental consent and was fined 170 million dollars from the Federal Trade Commission. For marketers to employ AI, they must do so in a way that promotes accountability and ethical practices.

Bias is another common limitation to artificial intelligence. For instance, AI can be biassed if a marketer feeds the biassed data into it, which in turn yields untrue results which may be employed in a misconstrued way. Additionally, creators of AI software may possess inherent biases which in turn is implemented into the behaviour of their platform. For instance, AI’s use in creating photographs has perpetuated stereotypes, as seen in advertisements from EPIC museum in Dublin. Fact hallucination, reasoning errors, and use in creative sectors less driven by numeric data are all considerations that must be addressed and accounted for by marketers employing AI effectively. As such, knowledge of the technology’s limitations at the same level of its strengths is paramount to leveraging its use in marketing successfully. 

Future Trends and Challenges of AI in Digital Marketing

To conceptualise the future for AI and digital marketing, one can turn to the words of a key researcher in its field. “When it comes to how AI is shaping the future of digital marketing we need to understand its current role in digital marketing. AI not only helps us to understand consumer behaviour or enables tailored content, it’s also a great tool that enables marketers like us to anticipate future trends and needs.  But challenges are always there and will always remain there such as data privacy and biases and therefore to strike a balance between them and to ensure we remain on the right path is the hour of need for every digital marketer”, says Dr. Eamonn O’ Raghallaigh, PhD and Digital Strategist at Trinity College Dublin. As such, employing AI in a way that keeps the consumer at the heart of operations in an ethical manner can be extremely beneficial for garnering a competitive edge in the evolving marketing landscape. By employing its usage in relevant and ethical spheres while acknowledging and diverting its disadvantages, marketers can improve ROIs, provide valuable insights, and better target their consumers.

Foresight Business Breakfast: Insights from Carolan Lennon & Pioneering Equity in the Tech Sector

Ayesha Ahmed & Michael D. Mooney 

The recent Business Breakfast hosted by TCD Foresight Business Group featured speaker Carolan Lennon, Country Leader at Salesforce Ireland. Ms. Lennon, known for her trailblazing efforts in the tech industry, shared her insights on the transformative power of education, the values that drive Salesforce, and the importance of diversity, equity and inclusion within her speech. Additionally, the breakfast provided a space for getting to know professional Trinity alums who are excelling in their field and were open and ready to help current students with their questions concerning business, the job market and politics. 

In her address to the breakfast attendees, Lennon shared her experiences as a woman in a historically male-dominated field, and the significance of her work in shaping the future of business in Ireland. For those who couldn’t attend, here were Lennon’s main talking points:

Education as a Game Changer

Ms. Lennon emphasised the pivotal role of education as a game changer in her professional journey. Having studied computer science at University College Dublin (UCD) in the 1980s, Ms. Lennon recognised the need to broaden her knowledge base and pursued an MBA at Trinity College Dublin. This proved to be an invaluable decision, equipping her with the skills and mindset necessary for success in the ever-evolving tech industry.

Salesforce’s Customer-Centric Approach

Ms. Lennon shed light on Salesforce’s unique approach as a customer centric company. Since its inception in 1999, Salesforce has been at the forefront of customer relationship management (CRM), revolutionising sales, marketing and commerce. The company prides itself on bringing customers and companies together by fostering trust, promoting equality and championing sustainability. Salesforce’s commitment to social impact is evident through its pledge to donate 1 percent of its profits, time and products to charitable causes, accounting for nearly $800 million USD in donations to date.

Breaking Barriers and Building Networks

Transitioning from the telecommunications industry to technology, Ms. Lennon faced the challenge of rebuilding her professional network. She emphasised the importance of owning one’s career and taking action, advocating for clear communication with superiors about career aspirations. Her experience highlights the significance of not only focusing on learning new technologies but also actively nurturing relationships and seeking opportunities beyond the confines of one’s daily work.

Diversity, Equity, and Inclusion

Ms. Lennon passionately discussed the importance of diversity, equity, and inclusion (DEI) in the workplace. Citing research and results, she underscored the positive impact of diverse teams on performance. She recounted her experience at a previous organisation where she helped in transforming the gender ratio from 9:1 to 1:1. Additionally, she acknowledged the need for greater diversity not only in terms of gender but also in terms of socioeconomic backgrounds, emphasising that true diversity extends beyond surface-level differences.

The Rise of AI and the Future of Business in Ireland

Looking ahead, Ms. Lennon identified artificial intelligence (AI) as the next major technological evolution. While acknowledging the increased interest in AI adoption among CEOs, she highlighted the importance of understanding its ethical implications and ensuring its accessibility and applicability. She also emphasised the need to address biases embedded in AI technologies, which often mirror the biases present in society. The future of business in Ireland, particularly in the tech sector, is heavily influenced by ongoing developments in AI.

Irish Women Breaking Barriers

As a woman diversifying a historically male-dominated field, Ms. Lennon encountered her share of challenges. However, she found a supportive environment at Salesforce, aligning with the company’s values of equity and inclusion. Her advice to aspiring professionals, particularly women, is to actively engage in extracurricular activities such as networking groups and to assertively communicate career aspirations to supervisors. Research on workplace dynamics and statistics on women’s experiences in Ireland can shed further light on the progress and areas for improvement.

The Referendum and the Changing Workplace Landscape

In light of the recent referendum concerning women and working from home, her insights become even more relevant. The evolving workplace landscape demands a renewed focus on equity, flexibility and inclusivity. As Ireland seeks to create a more balanced and empowered workforce, her experiences and perspectives serve as valuable touchstones for progress. 

Conclusion

Throughout the breakfast, Ms. Lennon delved deeply into her journey from telecommunications to technology, exemplifying the power of education, resilience, and a values-driven approach. Her experiences combined with the engaging conversations of Trinity alumni helped foster a sense of community, and a reassurance that yes, other people who went through the similar courses did find light at the end of the tunnel. Thank you to all participants who helped students gain an insight on how to actively pursue career opportunities, and contribute to a more inclusive and innovative future for businesses in Ireland and beyond.

THIRD PLACE: Navigating the AI frontier: How is Artificial Intelligence Shaping the Future of FinTech? 

Grace Walsh

Introduction 

In this essay, I aim to outline the role of artificial intelligence in fintech’s future, through examining what both fintech and artificial intelligence and their relationship in the finance  industry.  

What is Fintech? 

Fintech, financial technology, is first and foremost an example of the financial world’s  tendency to use unnecessary jargon and abbreviations, but in reality, is a term used to  describe everyday tools used in a myriad of global markets. An intimidating word to the  untrained eye yet exemplified by Revolut, tapping a phone to pay for something, buying and  selling, anything online and sending or receiving money from others are all examples of  fintech. Becoming an increasingly cashless world (Sprout on Dawson Street doesn’t even  take cash) means that fintech is being used on a wider scale. It is innovative and  transformative and has revolutionised the way money is spent therefore consumption and  hence has deepened global economic integration. (Stephanie Waldon, Doug Whiteman, 2022) 

Innovation in the world of finance has been a concept around for decades, although  the rate of change now is much faster than it was before. Changes in the financial world are  hard to keep up with and it can be difficult for regulators and policymakers to understand the  full effects of these technological innovations. Companies like Stripe, make money off  transactions and are therefore making money off people spending money similarly to PayPal. People can now also gamble online and are reminded with colourful and enticing  notifications that its time for them to return to the app and give up more of their money to the  hands of fate (attached to a man named Paddy Power).  

Firms in the financial industry facilitate transactions across markets, this behaviour  has become increasingly simple and accessible in recent decades with the emergence of  companies, like those mentioned above. 

What is Artificial Intelligence? 

Over the past decade AI has made significant developments and is becoming increasingly  accessible and useful in all areas of life; including finance. The IMF claimed that AI would  have a larger impact on the financial sector than COVID-19, in 2021, a shocking estimation  at the time, but now proving to be true. (Boukherouaa, AlAjmi, Deodoro, Farias, Ravikumar,  2021). The introduction of AI through sources like ChatGPT, has changed information access  forever, to a point where anyone can ask it to explain something to them as if they are a child,  in simpler terms than most websites, books or academic papers. People can learn about more  things in a way that suits them and far quicker than before. It took ChatGPT a mere five days  to gain one million users which took Instagram almost two months to reach. (Dave Ver Meer, 2024). Google’s revenue generated via online advertisements has reduced by over 30 billion  US dollars since the launch of ChatGPT according to Statista. It is no doubt that AI means  greater access to information which may help people make better investments and ensure  markets are efficient yet it also has the power to sway opinions, depending on the prompts it  is proposed it may play a role in confirmation bias. Nonetheless, it will change the future of  finance, for better or for worse.  

Potential benefits  

The world of AI has changed methods of information access forever. With this change in  financial markets, information access and communication is also changing, which can affect the financial sector. As seen in the infamous GameStop incident whereby Reddit was the  platform used by masses of day traders who determined the fate of wealthy short-sellers. AI  can now act as advisement in terms of investment decisions or help in creating a budget based  on personal goals and needs. AI has the potential to serve as an inexpensive financial advisor,  whether it is a good one or not is up for debate but regardless its influence exists and can only  grow from here. (Gomber, Kauffman, Parker and Weber, 2018).  

AI is a useful tool which can use financial and economic models, variables and  studies to predict and estimate macroeconomic changes in an economy. This means it is a much more flexible tool than using individual models of examination on the aggregate  economy or performance of markets. AI’s access to new data sources that other models may  not consider such as data uncovered through social media and many other previously ignored  variables. (Boukherouaa, AlAjmi, Deodoro, Farias, Ravikumar, 2021). AI uses machine  learning (ML) and deep learning (DL), which are the tools it uses to translate data into  knowledge that it can use to draw conclusions to certain questions or blend with other 

knowledge that it has previously attained. They are the key traits of AI which allow it to  operate as a useful tool in the finance industry, in the form of data analysis and forecasting.  (Plummer, 2024) 

In some areas of the financial sector including investment banking fintech is the  backbone of its operation. AI offers new opportunities for reaching new market participants,  through the increased accessibility as well as a new form of customer service via the AI  chatbots, hence reducing investment banks costs and increasing its efficiency. (Boukherouaa, AlAjmi, Deodoro, Farias, Ravikumar, 2021). These uses of AI in finance, as a fintech tool  reduce the amount of human contact drastically and significantly streamline the financial  institutions normal practices. The use of fintech and AI in the banking sector is a slowly  developing relationship in most cases due to regulation although there has been, increased  adoption of chatbots as a form of customer service and ATMs and online banking are also  forms of fintech. Through the use of other forms of fintech such as banking apps or online  shopping, machine learning can then be used through machine learning as a component of  creating forecasts about the future of economic stability and financial markets. There is the  potential for banks to use it as a method of risk assessment and credit decisioning by  assessing an individual’s financial history along with other considerations to determine a risk  level. (Plummer, 2024). In a similar way, this data can be used to create personalised  recommendations to customers based on their transactions and interactions with fintech.  

Potential Risks 

This form of data access, as mentioned above through social media or other streaming and  algorithmic services may have negative effects on financial markets as it is difficult to  regulate privacy in this area. As seen in recent years algorithms, social media and even  notifications play a role in politics, as seen in the case of Cambridge Analytica where debates  on data breaches during the Trump Campaign in the U.S. came to light. (Tett, 2017). The data  acquired may also be incorrect and create errors within AI responses to certain questions or  dilute the reliability of it as a source. (Boukherouaa, AlAjmi, Deodoro, Farias, Ravikumar,  2021) The reliability of AI on accurate data is a vulnerability which requires regulation and  supervision, as well as methods of intervention in preparation for crises. It poses ethical  issues as it already has built-in biases and tendencies, if stereotypes and generalisations exist  in data, social media or in anything which AI uses as a source then the same ideology is  absorbed by AI. Since the Global Financial Crisis of 2008, there have been much higher  levels of financial regulation in the banking and non-banking sectors worldwide. The 

development of technology sometimes seems as though it is happening first and the scramble  to come up with policies and regulatory requirements happens after. While AI creates new  challenges for regulators and policy makers it can also be used as a tool for both. It is being  used more and more as an integrated part of a system to detect fraud, money laundering and any other financial crimes which may exist through its accumulation of data about  transactions and patterns of behaviour. (Plummer, 2024) 

Future of AI as a Part of Fintech and Conclusion  Technological innovation has been the key driver for growth in almost all modern, open  economies and hence the pace of innovation is growing faster. Fintech developments are  disruptive to the financial industry, the days of phoning a stock broker are over, and the same  tasks can be fulfilled from anywhere at any time. The evolution of the financial industry from  the introduction of online banking and shopping to now the incorporation of AI. (Gomber,  Kauffman, Parker and Weber, 2018). The use of AI in finance will no doubt lead to further  global integration of markets and economies, increasing the vulnerability of the global  economy to a rampant economic crisis. Regulation and policymaking must coincide with the  future of fintech. AI has only begun to change the financial sector, it will continue to expand  and become more accurate and useful as it becomes integrated into banking systems and  models. It can help understand customers better, increase productivity and market  participation, give better access to information which (if correct) will improve market  efficiency, prevent fraud, reduce costs for financial institutions and make the overall world of  finance more accessible. (Plummer, 2024). With all these benefits comes questioning around  the ethics of its use, the potential of data breaches through ML and DL. The future of AI in  finance is unknown, and will take years of understanding, regulation and integration before it  can be used optimally and safely.

SECOND PLACE: Navigating the AI Frontier: How is Artificial Intelligence Shaping the Future of Fintech? 

Gabi Svobutaite

Introduction: 

Contemporary advancements within the spheres of Artificial Intelligence (AI) are rapidly reshaping  the financial services industry by revolutionizing operations through increased security, boosted  innovation, and accelerated digitization. Artificial Intelligence is particularly pervasive throughout  the fintech industry, automating processes which formerly required considerable time debt and a  sizeable labor force. The influence of AI may be seen beyond simply advancing the current  paradigm of financial services, it is furthermore facilitating the growth of future innovations and  sustainable business models that were previously deemed unimaginable.  

This paper seeks to provide a comprehensive overview and analysis of AI and its advancements in  fintech through a multifaceted approach. Firstly, this paper provides a background on financial  technologies and the areas of such which saw the most growth at the hands of AI. Secondly, this  paper discusses the societal impacts of increased AI use in fintech. Finally, this paper details the  extent to which and how AI is shaping the future of sustainable banking models. 

Fintech: What is it? 

Fintech refers to an emergent branch of financial services where finance and technology merge. It  encompasses a new era of technology which uses specialized algorithms to digitalize fundamental  financial functions which affect how consumers store, spend and save money. Fintech also impacts traditional investment approaches, having established cryptocurrencies such as Bitcoin as a major  player in the world of trading. The term “fintech” applies to a vast variance in innovations regarding  consumer transactions, whether it be developments in mobile banking (MB) or managing  investments through an online brokerage platform.1 

The fintech market may be segmented by four major consumer classes; (i)business-to-business  (B2B) for banks, (ii)clients of B2B banks, (iii)business-to-consumer (B2C) for small businesses, and  (iv) consumers. The increased data security, digitalization and analytics precision which fintech allows for has enabled the aforementioned user parties to interact and collaborate with a new level  of efficiency. 2 

The Fintech Surge: 

The fintech sector saw staggering rates of growth in the latter half of the last decade, with venture  capital (VC) entities investing $19.4 bn into fintech startups in 2015 and an astonishing $33.3 bn in  2020. The Covid 19 pandemic furthermore brought about an era of mass digitalization, causing a  whopping $92.3 bn boost in fintech funding, as well as an expected deal activity increase of 19%.  This upsurge in investments proved to be short-lived, however. Declining geopolitical and  macroeconomic conditions in 2022 provoked a destabilization of the global business environment,  leading to fintech funding returning to standard, pre-surge levels. This devaluation, although  expected, caused many fintech companies to lose vast amounts of capital, and quickly. Venture  capital funding suffered a decrease of $459.6 bn in 2022 from $683.1 bn in 2021. Total investments  in fintech were additionally faced with a 40% decline following this, now sitting at $55 bn as  opposed to $92 bn in 2021.3 

Though the fintech sector still faces many obstacles in the future, there are also many potentials that  have not yet been fully realized. Forecasts for the development of AI technology point to a stable rise in sophistication, thus leading to a steady rise in popularity and use as opposed to more  traditional banking practices. Fintech’s will continue to profit from the dramatic shift and integration  of AI in the banking sector, the quick uptake of other emerging digital technologies, and the global  expansion of e-commerce, especially in developing nations.4 

ML and AI Chatbots: Leading Areas of Growth 

Machine learning (ML) is an emergent area of AI in fintech which utilizes data reading algorithms  and software to better analyze and individualize services provided by financial institutions. ML is  revolutionizing how Big Data is assessed and trading market risk is predicted, without the need for  human employees.  

With the rapid growth and improved computational capabilities of modern technologies, large  amounts of data are becoming more readily available for economic and governmental entities to utilize. Analyzing this data, however, would require vast amounts of capital, time and people  resources. Therefore, companies and governments alike have turned to alternative methods of  analysis like AI to identify, process and study Big Data.  

ML uses intricate coding and algorithm models to source smaller data sets from the generalized pool  of Big Data, and thus create predictions which stem from the data sets identified. The algorithm  then uses recognition technologies to identify patterns for learning and remembering data, which  allows for abnormal activity and pattern change recognition when introduced to new data sets. 

Machine learning thus has become a large player in various industries such as banking and investing, or marketing and fraud regulations. Financial sectors may use ML to recognize trading opportunities  or identify market risks for loans and investments. Marketing and advertisement industries can  utilize machine learning algorithms to learn about their consumer’s online media activities to provide  them with the best suited and individualized content recommendations.5 

AI Chatbots have spearheaded the digitalization of customer service in the domains of financial  service and fintech industries. E-commerce firms and startups now employ AI via the means of  virtual assistants and chatbots to offer immediate and around-the-clock assistance to their  customers. Through using complex algorithms and data recognition software to analyze individual  customer transaction data, the aforementioned AI-powered virtual assistants can offer customized  and instant advice to each customer.6 

AI in Fintech: Societal Impacts 

The integration of AI in the spheres of fintech and the financial services industry has and continues  to have an extraordinary impact on society both on a micro and macro level. Firstly, through the  introduction of mobile banking (MB) and other e-commerce platforms, AI has allowed for fintech  to acquire a far greater consumer base, enabling individuals from disadvantaged and thus  underbanked regions to manage their finances effectively and with ease. According to a 2021 study  by McKinsey, the demand for e-commerce structures is notably higher in developing countries;  Africa was home to virtually half of the world’s total MB accounts, approximately 800 million users  were estimated. Fintech with its adoptation of AI had additionally served to further overall economic growth. AI has allowed fintech to establish new competitors within the financial industry,  thus driving prices down and allowing for increased choice within the market.7 

However, the growing popularity and mass usage of ML, MB and virtual advisory services has  contributed to a wide scale trend of employee layoffs. Several tech firms have already quoted AI as  the reason for their staff layoffs and reconsideration of tech graduates for recent hires as Silicon  Valley, Big Tech and commercial banks seek to keep up with recent AI advances. One of the  principal ways to pivot business activities to improve key operating metrics and hit the bottom line is  reducing headcount. Cutting headcount expenses to maintain profitability whilst backing  technological innovations is especially prevalent in the current climate of slowed VC and fintech  funding. Due to the increasingly automized nature of Big Data analytics, the increased consumer  preference of mobile banking systems and e-commerce platforms for capital management and  investment activities, and of course AI-powered virtual assistants overtaking existing financial  advisors in the banking industry, the need for physical employees is becoming increasingly  nanoscopic. 8 

Fig 1: data retrieved from FRED, Federal Reserve Bank of St. Louis. 

Figure 1 shows the fluctuation in US commercial bank employees, a definite decline may be seen in  recent years with a current downward trend visible after 2023.9 

Utilizing AI to Pursue a Path of Future Sustainable Growth: 

AI and fintech have the power to mitigate the largest growing social challenges we face today,  namely climate change and reaching national sustainability goals. Such issues require highly  progressive and innovative solutions, those which artificial intelligence and machine learning systems can produce.  

Sustainable investing is an area which massively favors AI and utilizes it to aid investors in sourcing and analyzing large volumes of new information when considering the risks and opportunities  relating to ESG (Environmental, Social and Governance) investment obligations of companies and  governmental bodies. Additionally, AI algorithms allow for an in-depth analysis of all the  information available about a certain company, which can be an immense and costly task for a  human employee to undertake. This leveraging of AI and ML technologies enables potential  greenwashing companies to be discovered in a far timelier manner. 10 

Conclusion: 

To offer some parting words, there is no doubt that the integration of artificial intelligence (AI) in  fintech has revolutionized ways in which the global majority manages their finances. With its ability  to analyze vast pools of data, predict capital market risks and trends, and provide customized user  experiences, the journey of AI in fintech will undoubtedly continue to evolve, encouraging a new age  of financial innovation. 

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