Implications, risks and considerations for successful and scalable AI development and deployment for the financial sector
AI is already replacing humans in fraud detection, risk management, trading, lending and investment advice – with pressures on the sector to cut costs, this is of course only set to rise. As a result, the rapidly growing capabilities and increasing presence of AI-based systems in our lives raise pressing questions about the impact, governance, ethics, and accountability of these technologies around the world. On top of this, consumers are increasingly mindful of the security of their data and how it is being used, and institutions are aware that new capabilities can also create new potential liabilities.
Advances in data science and artificial intelligence are transforming business practices across the financial sector. Relevant technological developments and their applications in banking, insurance, lending and asset management promise significant benefits to firms, consumers, and society at large, but also give rise to a wide range of ethical questions and concerns, including issues of regulatory importance. There is also growing interesting in the ethical use of AI and challenges for financial institutions over how to operationalize guidelines that have been developed so far and also which function of the business should ‘own’ such a project.
So how do we manage the associated ethical risks, challenges and governance implications present by AI development and deployment within an international, dynamic and fast-moving financial sector?