zealand sweden peru chile south africa hong kong norway uk uk israel india eurozone brazil peru sweden czech rep. mexico norway australia south korea israel malaysia iceland new zealand south korea australia eurozone poland hong kong colombia indonesia philippines canada mexico poland india switzerland china czech rep. indonesia china turkey philippines south africa usa hungary hungary brazil malaysia argentina russia russia japan iceland argentina - 1, 000 ( percentage ) - 800 - 600 - 400 - 200 at 19 oct. 2009 between 4 sep. 2008 and 19 oct. 2009 source : bloomberg. figure 6 interest rates in pesos and dollars in the local market ( percentage ) jan. 08 apr. 08 jul. 08 oct. 08 stock exchange - 90 days jan. 09 apr. 09 jul. 09 oct. 09 libor + 90 - day on - shore spread sources : bloomberg and central bank of chile. table 1 monetary policy rate and expectations according to ees ( percentage ) actual level expected for expected 2 same month months ahead expected for dec. 09 oct. 2008 8. 25 8. 50 8. 50 7. 00 dec. 2008 8. 25 8. 25 7. 75 6. 25 feb. 2009 4. 75 6. 25 5. 00 4. 00 nov. 2008 8. 25 jan. 2009 8. 25 7. 25 mar. 2009 8. 25 7. 50 2. 25 6. 75 3. 13 2. 50 6. 63 5. 50 2. 00 source : economic expectations survey ( ees ), central bank of chile. figure 7 foreign credit flows to residents ( billions of dollars ) 3. 0 3. 0 2. 5 2. 5 2. 0 2. 0 1. 5 1. 5 1. 0 1. 0 0. 5 0. 5 0. 0 0. 0 - 0. 5 - 0. 5 - 1. 0 - 1. 0 - 1. 5 - 1. 5 - 2. 0 jan. 07 jul. 07 jan. 08 new credits to banks jul. 08 jan. 09 - 2. 0 jul. 09 new credits to non - banks net flow ( * ) ( * ) discounting bank and non - bank amortizations from total new credits. source : central bank of chile. figure 8 world growth ( annual change, percentage ) - 3 - 6 - 9 - 12 world at market exchange rate - 3 - 6 - 9 - 12 chile ( 1 ) gray area shows projections as from 2009. ( 2 ) figures for growth in 2009 and 2010 stand for

techniques to make informed decisions and evaluate their effectiveness, in turn supporting the promotion of monetary and financial stability. but, as producers as well as users of data, central banks have to cope with the advent of new technologies and the proliferation of data sources. on the one hand, the data revolution, the development of artificial intelligence and it innovation are opening up exciting new possibilities, for instance of making use of non - conventional and / or 1 / 3 bis - central bankers'speeches unstructured information and dealing effectively with " big data ". on the other hand, these rapid changes are bringing new ethical challenges to ensure a trustworthy use of ai, such as responsibility, explainability, accountability, bias, privacy, and data protection. another key challenge is to preserve the relevance of good statistics in today's societies in front of alternative facts and fake news. the ifc has been already working actively to shed light on these issues and to facilitate central banks'cooperation in addressing them. our most recent contributions are dealing with the topics of micro data, data science, statistical communication, data governance and climate change statistics. the event today will allow us to learn more of so many experts from around the globe and make further progress. before turning to the presentations of this conference, let me share with you some thoughts on important aspects that will be covered more extensively during the various sessions during the following days. first, we are living in an era of unprecedented changes. new forces are reshaping our world in ways we could not have imagined a few decades or even years ago. therefore, we are facing new challenges at a greater speed. for example, digitalisation is transforming every aspect of our lives, in turn questioning the way payments are organised and recorded. the development of sustainable finance is attracting a lot of interest in order to help track and mitigate the impact of climate change ; but the availability of relevant, good - quality environmental data has become a key concern for central banks and financial supervisors. second, and fortunately, data science can help us tackle the various issues we are facing. in particular, new tools can support the development of and dealing with large, complex and unstructured information data sets. moreover, untapped, " alternative " information sources can provide more real - time, frequent, timely and detailed insights. no wonder that central banks have been actively exploring the adoption of data science tools in recent years, especially in the context of the ifc. as we will hear today, there