the real economy? platform ecosystems create new challenges to financial stability, as they comprise of a highly complex matrix of digital products and services. firms may offer advanced solutions that are built on a product of one key supplier, or may be heavily dependent on processing data on the information architecture that is rented from one key infrastructure provider. the more complex these networks become, the more vulnerable these ecosystems become to more unconventional security risks. vulnerabilities in data have so far been less pronounced, largely due to the fact that most datasets have been so - called structured datasets, where the relationships between different data points are clearly defined and specified. massive datasets are usually less rigidly specified, and encompass much less structure. for example data obtained from the web by scraping websites, or by reading in social media feeds, are good examples of modern unstructured data. there are no simple ways of certifying the authenticity and origin of these unstructured datasets, which makes them highly vulnerable to manipulation. these types of security issues are also vulnerable to hybrid security threats. it is therefore extremely important that we stay vigilant to new developments in technology and understand what kind of security vulnerabilities these create. central banks can also play a role in maintaining a high level of cybersecurity by promoting cybersecurity awareness and knowledge in among the financial market participants. ladies and gentlemen, 2 / 3 bis central bankers'speeches let me conclude. all in all, the financial industry is going through a major transformation, driven by the whole range of digital technologies and the explosive growth of data. regulators, including central banks, are aiming at finding the right balance between regulation and innovation, so that consumers and businesses can benefit from new possibilities, while maintaining financial stability and a level playing field. we also want to make sure that the society remains inclusive. that ’ s why we want to look at digital transformation from the citizens ’ point of view, in order to identify what is real and what is only hype. from that angle, we can see that there are different developments going on : those that clearly increase societal welfare and should be benefitted from, such as mobile and real - time payments – as long as we also take care of enhancing financial literacy ; those that should be watched, or even prevented, such as booms and busts related to crypto - assets ; and those that can be further developed, such as machine learning and artificial intelligence. this makes

olli rehn : data - driven financial stability - challenges and opportunities opening remarks by mr olli rehn, governor of the bank of finland, at the “ data - driven financial stability ” conference, helsinki, 28 november 2019. * * * ladies and gentlemen, dear friends, it is my great pleasure to welcome you all to our conference entitled data driven financial stability here at the finlandia hall. we have recently had quite busy “ tech weeks ” in helsinki. just a few weeks ago helsinki hosted one of the leading startup and tech events in the world – slush. the programme of this year ’ s slush was particularly topical, as it focused on the ethics and regulation of technology. likewise, we at the central banking community consider ethics and regulation vital. hence, we are working hard to form a solid understanding of all the potential consequences that the widespread use of e. g. artificial intelligence and mass volume data may have on finance. from this angle, i will address three issues regarding the role of advanced technologies in finance. first, i will ask how advancements in technology could be used to provide new digital products and services. second, i will turn to risks related to the widespread use of new technologies that may hamper the proper functioning of markets. third, i will finish by looking at how the potential impact of new technologies on competition and diversity do call for greater domestic and international policy coordination. let me start with a question : what do we mean when talking about artificial intelligence and big data? in the absence of a generally agreed definition, artificial intelligence can mean anything from a simple script to a very complex combination of automated processes and machine learning models. what comes to massive or big data, there are no universally accepted criteria on how large of a volume of data counts as ‘ big ’. yet, while emerging technologies have some novel features, they are still largely based on the same technologies and statistical methods that we ’ ve been using for years. hal varian recently described artificial intelligence and big data as “ just doing the same sort of thing we did before, but at a much larger scale ”. from where do the potential benefits then stem? firstly, with the help of new technologies, companies improve their existing processes and create new products, services and distribution channels. the low marginal cost of software solutions allow digital products to be customized, and thus to satisfy the unique preferences of each individual client. secondly, the digital footprints that customers generate allow companies to better understand when and where digital