AI could lead to global financial meltdown - WEF
Increased use of machine learning and cloud services could place the financial world in jeopardy
Artificial intelligence will reshape the world of finance over the next decade or so by automating investing and other services—but it could also introduce troubling systematic weaknesses and risks, according to a new report from the World Economic Forum (WEF).
The problem, according to the WEF, stems from the way global financial markets are incorporating machine learning and AI. “The dynamics of machine learning create a strong incentive to network the back office,” says the report’s lead author, Jesse McWaters, head of the AI in Financial Services Project at WEF. “A more networked world is more vulnerable to cybersecurity risks, and it also creates concentration risks.”
Compiled through interviews with dozens of leading financial experts and industry leaders, the report concludes that artificial intelligence will disrupt the industry by allowing early adopters to outmaneouvre competitors. It also suggests that the technology will create more convenient products for consumers, such as sophisticated tools for managing personal finances and investments.
Key findings include:
• From cost centre to profit centre: Institutions will turn AI-enabled back-office operations into external services, both accelerating the rate at which these capabilities improve and necessitating others to become consumers of those capabilities to avoid falling behind
• A new battlefield for customer loyalty: As past methods of differentiation erode, AI presents an opportunity for institutions to escape a "race to the bottom" in price competition by introducing new ways to distinguish themselves to customers
• Self-driving finance: Future customer experiences will be centred around AI, which automates much of customers’ financial lives and improves their financial outcomes
• Collective solutions for shared problems: Collaborative solutions built on shared datasets will radically increase the accuracy, timeliness, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system
• Bifurcation of market structure: As AI reduces search and comparison costs for customers, firm structures will be pushed to market extremes, amplifying the returns for large-scale players and creating new opportunities for niche and agile innovators
• Uneasy data alliances: In an ecosystem where every institution is vying for diversity of data, managing partnerships with competitors and potential competitors will be critical but fraught with strategic and operational risks
• The power of data regulators: Regulations governing the privacy and portability of data will shape the relative ability of financial and non-financial institutions to deploy AI, thus becoming as important as traditional regulations to the competitive positioning of firms
• Finding a balanced approach to talent: Talent transformation will be the most challenging speed limit on institutions’ implementations of AI, putting at risk the competitive positioning of firms and geographies that fail to effectively transition talent alongside technology
• New ethical dilemmas: AI will necessitate a collaborative re-examination of principles and supervisory techniques to address the ethical grey areas and regulatory uncertainties that reduce institutions’ willingness to adopt more transformative AI capabilities
This report is the culmination of one year’s worth of research, including over 200 interviews with subject matter experts and seven global workshops, prepared by the World Economic Forum in collaboration with Deloitte.