Artificial Intelligence in Finance: Possibilities and Threats

Abstract

Artificial intelligence (AI) alongside one of its main subsets, machine learning (ML), is no longer a sheer propaganda, it has nearly become a household name, though the use of the term AI by the public and at times technologists is often a misnomer. This paper explores AI and ML, outlining the main categories of extensive ML algorithmic techniques. Importantly, it provides handy timeline and distinction between the duo, whilst also introducing multiple lens views as to their potentials in the finance industry, covering the triad of financial, regulatory and insurance technologies (FinTech, RegTech, InsurTech). Certainly, AI/ML has found practical applications in finance; whether it is generating insights on customer spending, obtaining informed underwriting risk outcomes, detecting anomalous fiscal transactions or interacting with customers using natural language, AI/ML potentials in finance is gaining significant momentum in today’s world of near ubiquity Internet of Things (IoT), advanced computing and telecommunication technologies. Without downplaying the potential capabilities, what is less certain however is whether there are any frontiers to its applications in finance, and whether it will provide panaceas to the pressing challenges, especially in relation to transparency from a collective viewpoint of AI/ML solution design, development and implementation.