Banking in Transition: Embracing AI and Competition for Future Success
Banking, as an industry, has traditionally operated in a secure environment characterized by high barriers to entry and strict regulatory frameworks which limited competition from external players. This has led banks to fall into complacency, reducing the incentive to innovate and evolve. Customers were stuck with banks and had no alternatives to them, which resulted in banks prioritizing their own interests over those of customers. However, the financial crisis of the last decade awakened concerns over the security and the monopoly of banks in the financial sector. Subsequently, governments have initiated measures to promote competition within the financial industry, opening the gates for challenger banks and innovative financial services providers, Fintechs, to disrupt the long-standing dominance of traditional banks (Carpenter, 2020).
Unlike other industries, the banks’ main cost is concentrated in their employees and not in physical assets such as factories or manufacturing plants. Therefore, significant economies can be achieved by properly managing their human capital and reducing personnel-related expenses. This is where Artificial intelligence (AI) comes into play. The technology of simulating human intelligence at scale with machines, referred to as Artificial Intelligence or AI, has evolved significantly and emerged as a solution to the banks’ challenges. It has the ability to analyse vast amounts of data beyond human capability, detect undiscovered patterns and emulate human decision-making at scale, enabling banks to operate more effectively.
How is AI being applied in banking?
In order to understand the transformative potential of AI in banking, a Master’s thesis explored the applicability of AI in banking, its benefits and challenges to adoption (Cedersund, 2023). The research followed an inductive qualitative analysis approach conducted by analysing 15 interviews that took place on 15 episodes of a podcast called “AI in financial services” (Faggella, 2019-present), which hosts key stakeholders in the banking and financial sector and discusses topics of intersection between AI and finance. The inductive analysis method allowed for data to generate insights from the bottom up and group the information into indicative categories, like adoption challenges, AI applications in banking, bank advantages, etc.
The interviews uncovered an immense number of opportunities for AI in banking. AI superior analysis capability enables more accurate credit predictions by leveraging alternative data types, like assessing a student loan based on university ranking and study major of the applicant. AI’s capability of analysing vast amounts of data in a short period, provides clients with on-the-spot lending decisions, personalized services based on the unique needs and preferences of each customer. AI can recommend potential prospects for employees to pursue that are more likely to accept a purchase. It applies efficient crime prevention measures through fraud pattern recognition and anomaly detection that identify financial crimes in real-time. In addition, its predictive power allows it to foresee cash flow and currency demands based on each client’s specific business cycle, aiding banks prepare money reserves in advance.
From the bank’s operational perspective, the benefits achieved from these intelligent systems are faster and more accurate work processes, such as reducing fraud investigations, mitigating human error, facilitating documentation and information extraction. From the client’s standpoint, AI-powered chatbots provide more meaningful interactions that contribute to an enhanced overall customer experience. From the employee’s perspective, the automation of manual and repetitive tasks will reduce workload and reallocate workers to more meaningful higher value tasks, like process supervision and deeper customer interaction, that will ultimately enhance job satisfaction.
What is the sentiment of the public regarding AI adoption in banking?
Despite existing research papers and publications on various topics concerning AI, there is still a gap in research on the attitude and perception of the public regarding AI (Vasiljeva, Kreituss, & Lulle, 2021). Therefore, the thesis sought to understand the sentiments and opinions of bank stakeholders towards AI which reflect the readiness of society to accept and support its implementation or reject it and hinder its adoption. The method consisted of conducting a sentiment analysis by deconstructing the conversations on the podcast and running each opinion into Azure Machine Learning, an AI software, capable of performing sentiment analysis. (Cedersund, 2023.)
The results showed a strong positive attitude towards the potential and capabilities of AI in banking. Nevertheless, its technological level is still nascent and not all aspects of AI can be deemed fully operational at present. Depending on the area of application, certain AI facets may be more effective than others. Certain AI applications, such as process enhancement in automation, cybersecurity, credit assessment and stock trading, received favourable sentiments, despite utilizing narrow intelligence functions. On the other hand, current chatbots elicited negative emotions due to their limited cognitive abilities, basic functionality, memory limitation and lack of contextual understanding, leading to customer dissatisfaction. Despite that, banks aspire for future chatbots to enhance customer relationship and touch points by providing high-quality conversations, better customer engagement and a uniform coherent conversations where AI remembers previous conversations, handles queries in a freeform way and delivers a seamless customer experience.
How will banks fare in the competition?
AI applications could be a game changer for banks, some interviewees viewed the general opinion on banks’ future competitivity positively, however, the sentiment was not unanimous. It was acknowledged that customers are no longer dependent on a single provider for their financial activities. Other attractive channels are brought by fintech firms who are born digital and offer specialized services using creative innovative technology at a competitive price. In addition, one interviewee highlighted the commoditized nature of banking services where all banks provide more or less the same services with no significant differentiation. In addition, it is expected that Fintechs and Big Tech companies will overtake banks’ profitable business by means of their agility and technological prowess, which will relegate banks to low profit generating activities like low interest lending and money circulation facilitators. In contrast, other interviews viewed the future of banks more brightly. Banks still possess unparalleled advantages that their competitors lack, such as reputation, trust, global reach and customer base. By capitalizing on these qualities and intensifying their efforts in AI and digitization, banks can secure a favourable position for themselves in the future. It is even possible that banks will undergo a transformative process by divesting certain segments of their operations and transforming them into standalone fintech companies. This strategic approach will allow for the emergence of hybrid fintech-bank conglomerate that can effectively compete in the evolving market landscape. Alternately banks could partner with fintech companies or acquire them as they emerge to make use of the latest AI technology and eliminate the competition at the same time. In the end, it remains to be seen how the industry will evolve, but one thing is clear, is that banks must be willing to adapt and embrace new AI technologies to stay competitive.
References
Carpenter, T. (2020). Revolutionising the consumer banking experience with artificial intelligence. Journal Of Digital Banking, 4(4), 291-300. https://hstalks.com/article/5508/revolutionising-the-consumer-banking-experience-wi/
Cedersund, M. (2023). Artificial Intelligence in Banking: The Future of The Banking Work Environment. [Master’s Thesis, Turku University of Applied Sciences]. Theseus. https://urn.fi/URN:NBN:fi:amk-2023060722333
Faggella, D. (Host). (2019-present). AI in Financial Services Podcast [Audio Podcast]. Emerj Artificial Intelligence Research. https://emerj.com/ai-in-financial-services-podcast/
Vasiljeva, T., Kreituss, I., & Lulle, I. (2021). Artificial Intelligence: The Attitude of the Public and Representatives of Various Industries. Journal of Risk and Financial Management, 14(8), 339. https://doi.org/10.3390/jrfm14080339