In my view, there are similarities that yield useful policy lessons for the euro area. But there are also differences that need to be kept in mind. What can we learn from the Asian crisis? What are the parallels between the Asian crisis in 1997–1998 and the euro area crisis? The economies of emerging Asia were characterised by buoyant growth and a brisk expansion of credit (see Chart 1). This rise in debt was facilitated by considerable inflows of foreign capital, which financed significant external deficits (see Chart 2). This led to growing financial imbalances, and in particular to currency and maturity mismatches on the balance sheets of local banks. In addition, the economic boom prevailing at that time was accompanied by a loss of competitiveness of the region’s export sector. Investors typically under-priced potential risks as they had overly optimistic expectations of the medium-term growth prospects. They did not identify systemic vulnerabilities such as the risk of sudden stops in capital flows or of twin crises of the banking system and the balance of payments, which eventually materialised.1 Except for currency mismatches, similar developments were evident in the euro area before 2009 – if not at the regional level, at least in those countries that later ran into financial difficulties. It was widely believed that sudden stops in capital flows, not to mention twin  1  See Calvo, G. (1998). “Capital Flows and Capital-Market Crises: The Simple Economics of Sudden Stops”, Journal of Applied Economics 1(1), pp.
The story is a clear example of how artificial intelligence can produce bad outcomes for all concerned. It also offers a case study for exploring the root causes that lead to bad outcomes - and so in turn offers insights for boards on how to govern the introduction of artificial intelligence. The art of managing technology is an increasingly important strategic issue facing boards, financial services companies included. And since it is a mantra amongst banking regulators that governance failings are the root cause of almost all prudential failures, this is also a topic of increased concern to prudential regulators. In my comments, I will provide a quick overview of the scale of introduction of artificial intelligence in UK financial services; then make three observations about it, and suggest three principles for governance derived from them. Artificial Intelligence Technological innovation is inevitable and welcome. As the Governor noted during this year’s UK Fintech Week,1 we are shifting towards a new economy, which is powered by big data, advanced analytics, smartphone technology and more distributed peer-to-peer connections. This new economy will go hand in hand with fundamental changes to the structure and nature of the financial system supporting it. Indeed some of the largest international investment banks are now declaring that they are technology companies with banking licences. Some of the most important recent developments in technology are associated with the introduction of automation – by which I mean the replacement of humans by machines for conducting repetitive tasks.