Transforming Paradigms: A Global AI in Financial Services Survey
128 Pages Posted: 18 Mar 2020
Date Written: February 4, 2020
This report presents the findings of a global survey on AI in Financial Services jointly conducted by the Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School and the World Economic Forum in Q2-Q3 2019. Representing one of the largest global empirical studies on AI in Financial Services, a total of 151 respondents from 33 countries participated in the survey, including both FinTechs (54% of the sample) and incumbent financial institutions (46% of the sample). The study was supported by EY and Invesco. The study’s objective was to analyse and understand the current state of AI adoption in Financial Services, as well as its subsequent implications. This was done through the comparative analysis of empirical data collected via a web-based questionnaire.
This research provides a comprehensive picture of how AI is currently being applied in Financial Services by both FinTechs and Incumbents; driving different business models; underpinning new products and services; and playing a strategic role in digital transformation. The findings also reveal how financial service providers across the globe are meeting the challenges of AI adoption with its emerging risks and regulatory implications, as well as the impact of AI on the competitive landscape and employment levels.
The overarching findings of the study suggest that AI is expected to transform a number of different paradigms within the Financial Services industry. These anticipated changes include how data is utilised to generate more actionable insights; business model innovation (e.g., selling AI as a service); changes to the competitive environment with the entrance of ‘Big Tech’ and consolidation; various impacts on jobs and regulation; impacts on risks and biases; and the further development and adoption of game-changing technologies.
Keywords: Artificial Intelligence, Financial Services, FinTech
JEL Classification: G00, G20, G21, G23, G28, M13, M15, O10, O30, O31, O32, O33, O38, Y10, Y20
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