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.
Highlights
Introduction and Research QuestionsStudies have revealed that with a projected overall spend of $ 58Bn by 2021 (Soni et al, 2019) and 4.6 folds increase in the deal volumes (Deloitte, 2017), and a 300% increase in external investments (Huimin Lu, Yujie Li, Min Chen, Hyoungseop Kim, 2018)- Artificial Intelligence (AI) is present and prevalent in today's world
As observed from the growing interest and opportunities outlined in this study, the adoption of AI and Machine Learning (ML) in the financial services industry is here to stay and disrupt the extant and the deep-rooted traditional business models
There are multiple antecedents of successful AI and ML lead transformation in any financial services institution- starting from data acquisition, analysis, technology adoption, and most importantly the cultural alignment
Summary
Studies have revealed that with a projected overall spend of $ 58Bn by 2021 (Soni et al, 2019) and 4.6 folds increase in the deal volumes (Deloitte, 2017), and a 300% increase in external investments (Huimin Lu, Yujie Li , Min Chen, Hyoungseop Kim, 2018)- AI is present and prevalent in today's world. The study of Innovation Diffusion by Everett M Rogers (2010) has been further elucidated by Jeoffrey Moore in his book "Crossing the Chasm" (Moore & McKenna, 1999) that believed to have helped the technology researchers and marketers channelize their thinking and efforts towards advancing an innovation/product in the Technology Innovation life-cycle. With this theoretical underpinning, it is important to assimilate two critical definitions that are relevant in the current study 1) Early adopters 2) Early majority. Crossing the chasm (Moore & McKenna, 1999) between the early adopters to the early majority and advancing to the latter is considered to be a significant breakthrough in any product/Innovation life-cycle
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