Forewords Forewords
In 1950, five years before the term ‘Artificial Intelligence’ (AI) was coined by John McCarthy, Alan Turing already posed the question “Can machines think?” and devised the Turing Test. 70 years on, the world’s computational capability has grown by leaps and bounds, and so has the application of AI across a wide array of industries, including Financial Services. However, beyond the news headlines and opinion pieces, there is still very limited empirical evidence available on the current state of AI adoption in finance and its implications. This global survey, jointly conducted by the Cambridge Centre for Alternative Finance (CCAF), at the University of Cambridge Judge Business School and the World Economic Forum, is aimed at going beyond the hype and hyperbole, to provide some empirical data and shed light on the evolving landscape of AI-enabled Financial Services. Based on a survey sample of 151 firms which included both FinTechs and Incumbents, this study was able to depict a global Financial Services sector that is undergoing profound digital transformation underpinned by the advancement in AI. The research findings point to increasing adoption of AI in finance, as firms are leveraging AI to revamp existing offerings and create new products and services. AI is helping firms transform practices, processes, infrastructure and underlying business models, for example selling AI as a service. This research unveils how Financial Services firms are facing hurdles to AI implementation, including access to data, access to talent, and regulatory uncertainties. This study also examined potential and realised risks with growing adoption of AI in finance, the impact on workforces in both the short and long term across industry verticals, and strategic learnings from the current frontrunners of AI implementation. Nevertheless, it is evident that more research needs to be done in order to better understand the opportunities and challenges brought about by the eventual mass adoption of AI in Financial Services. For instance, how can finance firms open up the ‘black box’ of AI and facilitate more explainable and transparent applications? As AI is becoming increasingly autonomous, what will the roles of humans be and how would an effective human-in-the-loop AI system manifest itself? What are some socioeconomic repercussions and ethical implications of AI-induced biases and risks? How can regulators and policymakers harness technology solutions to effectively regulate and supervise AI in finance? This report, therefore, marks just the beginning of a long journey for us to collectively comprehend the potential, possibilities, and boundaries of AI in finance. We are profoundly grateful to EY and Invesco for enabling us to produce this empirical study and for their helpful feedback during the research process. We are also very thankful to the financial service providers who took part in our global survey. Finally, we would like to thank the interdisciplinary CCAF-Forum research team led by Lukas Ryll, which over the last many months worked tirelessly and collaboratively to create this study. Matthew Blake Head of Financial & Monetary Systems World Economic Forum
Bryan Zhang Executive Director Cambridge Centre for Alternative Finance
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