Early Adopters to Early Majority - What's Driving the Artificial Intelligence and Machine Learning Powered Transformation in Financial Services?

Abstract

From retail banking to corporate banking, from property and casualty to personal lines, and from portfolio management to trade processing, the next wave of digital disruption in financial services has been unleashed by the concepts and applications of Artificial Intelligence (AI) and Machine Learning (ML). Together, AI and ML are undoubtedly creating one of the largest technological transformations the world has ever witnessed. Within the advanced streams of research in AI and ML, human intelligence blended with the cognitive reasoning of machines is finally out of the labs and into real-time applications. The Financial Services sector is one of the early adopters of this revolution and arguably much ahead of its leverage compared to other sectors. Built on the conceptual foundations of Innovation diffusion, and a contemporary perspective of enterprise customer life-cycle journey across the AI-value chain defined by McKinsey Global Institute (2017), the current study attempts to highlight the features and use-cases of early-adopters of this transformation. With the theoretical underpinning of technology adoption lifecycle, this paper is an earnest attempt to comment on how AI and ML have been significantly transforming the Financial Services market space from the lens of a domain practitioner. The findings of this study would be of particular relevance to the subject matter experts, Industry analysts, academicians, and researchers focussed on studying the impact of AI and ML in the financial services industry.

Business intelligence tools in finance: A review of trends in the USA and Africa

“…The integration of artificial intelligence (AI) and machine learning (ML) in cloud-based business intelligence (BI) solutions has significantly impacted decision-making in the US financial sector (Chintalapati, 2021). These technologies have facilitated the widespread adoption of AI and ML in various industries, including the financial services sector (Chintalapati, 2021). The adoption of AI has become a key driver for the success of financial institutions, offering more personalized, accurate, and real-time products and services .…”

“…The use of AI for making decisions has sparked debates on the benefits and potential harms of self-learning technologies, ranging from hopes of fully informed and objectively taken decisions to fears of potential negative consequences (Licht & Licht, 2020). Additionally, the adoption of AI and ML has led to the next wave of digital disruption in financial services, transforming various areas such as retail banking, corporate banking, portfolio management, and trade processing (Chintalapati, 2021). The use of AI and ML techniques has been shown to lead to better financial performances by firms, as evidenced by the combined approach of ML techniques and inferential models used in evaluating public enterprises in Europe (Lucia et al, 2020).…”

Securing Tomorrow: The Intersection of AI, Data, and Analytics in Fraud Prevention

“…They can implement preventative measures before the escalation of fraud. Further, Chintalapati [7] stresses the importance of incorporating explicable AI models into MIS. In AI decision-making, transparency and openness are crucial so that humans may comprehend and interpret model outcomes.…”