Raimond Maurer, Dean of Goethe University’s Faculty of Economics, and Jan Pieter Krahnen, Director of SAFE, opened the conference and welcomed the speakers and the audience. Peter Praet (photo), Board Member of the European Central Bank (ECB), delivered the subsequent keynote address. Praet argued that central bankers, especially in the euro area, are currently confronted with different types of uncertainty when taking monetary policy decisions. There is uncertainty about the current state of the economy, the structure of the economy and, in particular, the transmission mechanism of monetary policy instruments, he said. Also, central bankers do not know how economic agents form their expectations about future economic developments and economic policy actions. In this situation, Praet explained, the ECB is using data to analyze medium to long-term effects and developments to guide its decisions. He argued that a better institutional framework or improved mechanisms in the euro area would help to manage potential mistakes made by the central bank.

High volume, highly unstructured data

The first of three ensuing panel sessions dealt with “High volume, highly unstructured data – finance’s new background conditions”. The session was chaired by Hans-Helmut Kotz. Loriana Pelizzon, SAFE Professor of Law and Finance at Goethe University, stated that currently massive amounts of data are being produced – for example in the context of high frequency trading – which are hard to store, clean and investigate. Pelizzon made the point that classical econometric approaches are not appropriate to handle these amounts of data. Stefan Mittnik from LMU Munich agreed with Pelizzon that we need new empirical approaches for analyzing big data. According to him, big data offers big opportunities when used purposefully and properly. However, he also cautioned that coordinated regulatory action based on the same big data pools could lead to a synchronization of economic agents’ actions and thereby become a threat to financial stability, when risks are no longer spread evenly across economies.

From left: S. Mittnik, P. Robinson, H.-H. Kotz, A. Schubert, L. Pelizzon

Paul Robinson, Head of Advanced Analytics at the Bank of England, explained how the strategy of the Bank of England (BoE) and its methodological approach to using data changed when Mark Carney became the new Governor of the central bank in 2013. The BoE established the advanced analytics unit as a centralized resource for the bank. The unit uses cross-sectional micro-econometrics, network theory and agent-based modeling to investigate the large amounts of data available, also from social media sources, Robinson said. For instance, when the referendum on the independence of Scotland took place in 2014, the BoE monitored the development because a vote in favor of independence could have threatened financial stability. In order to assess the likelihood of a vote for or against independence, the BoE analyzed data from social media channels, Robinson said. The challenges to big data analytics in Robinson’s view come from the fact that big data is basically about data-mining. Good structural explanations for any empirical findings do not naturally arise from the analysis. Rather, all analyses need to be complemented by structural interpretations derived from a good understanding of the policy processes.

Aurel Schubert, Director General Statistics at the ECB, stressed that data and good statistics form the basis for taking decisions on monetary policy and assessing the implications of these decisions. They substantiate the trust that is placed in central bank decisions. Before the financial crisis, the ECB had focused more on aggregate euro area data, Schubert noted. However, it had turned out that euro area countries are very heterogeneous and therefore the ECB now focuses more on granular than on aggregate data. Besides, Schubert demanded that data collected in the euro area should be more standardized to simplify the analysis.

FinTechs – Disrupting and performance enhancing?

The second panel “FinTechs— Disrupting and performance enhancing?”, chaired by Jürgen Schaaf from the ECB, turned to the question whether FinTechs are complements or competitors of banks. Andreas Hackethal, Professor of Personal Finance at Goethe University and SAFE, made the point that FinTechs usually do not provide new financial services, but rather offer the same functions in a radically new way and in a different institutional set-up. According to him, FinTechs are small, tech-driven, explorative firms with a narrow focus. These firms can compete with banks, he said, because they offer new and cheaper ways to invest money or to manage risks.

From left: A. Wieandt, J. Schmalzl, J. Schaaf, A. Isakov,  A. Hackethal

Joachim Schmalzl from the Sparkasse KölnBonn and incoming Member of the Executive Board of the German Savings Banks Association (DSGV), stated that savings banks have, in the past, neglected to build a culture of innovation. The strategy to keep pace with new technological developments will therefore be to copy technical solutions from Fintechs. He described FinTechs as “external innovation labs” for savings banks. In his view, it is not FinTechs that pose a threat to established banks, but regulation, if it does not provide for a level playing field for banks and FinTechs. In his view, FinTechs do not have to apply to the same regulations as banks which could be a competitive advantage. Axel Wieandt, Honorary Professor at WHU, expects a restructuring of financial markets. He believes that surviving FinTechs will co-exist with the surviving banks in a system of collaboration and partnership. How each institution reacts to the FinTech challenge will determine its survival in the market, he stated. Alexander Isakov from Pallantius stressed the fact that it will become critical for businesses not only to have access to data but also to understand how to use this data for making things easier for consumers, governments and companies.

Banking on big data – different policy issues?

The third panel “Banking on big data – different policy issues?” was chaired by Günter Beck, Professor for European Macroeconomic Studies at the University of Siegen and Associate Research Professor at the SAFE Policy Center. In this session, Andreas Dombret from Deutsche Bundesbank argued that FinTechs will not make banks obsolete but, according to him, there will be a different composition in the banking sector in the future. Dombret believes that banks will definitely come under pressure with respect to their profits and visibility. However, he sees also many chances for cooperation between banks and FinTechs. Andreas Wolf from McKinsey agreed with Dombret that banks and FinTechs will more and more collaborate and learn from each other. However, they also compete with each other, for example, when hiring new people who are able to deal with the new technologies, he said.

From left: T. Weimar, S. Rüping, G. Beck, A. Wolf, A. Dombret

Theodor Weimer from HypoVereinsbank – UniCredit Bank AG added that banks currently face large transformational challenges, probably the largest for decades. These challenges stem not only from digitization but also from higher regulations, low interest rates and the loss of trust in the banking business. A clear advantage for established banks when competing with start-ups is their long-term knowledge of the sophisticated banking business, he argued. FinTechs therefore do not worry him. However, he sees a potential threat in the fact that digitization leads to opportunities for big players like Google and Amazon to enter into financial services provision. Stefan Rüping from the Fraunhofer-Institut IAIS stated that his institute observes that especially the finance and insurance industry are becoming more interested in big data. However, he warned that it is difficult to use personal data in these highly regulated markets, where strict rules for data protection apply.