A Review of Selected Aspects of Big Data Usage in Banks’ Risk Management

Contemporary banks operate in a changing environment influenced by regulatory requirements, emerging new risk types and high competition on the market. At the same time banks have on their disposal large datasets from internal and external sources – the question arising is whether banks are using adequate analytics to gain value from big data. Big data has been used in banking for some time, mostly in the marketing field, but the usage of big data in banks’ risk management has not been a subject of extensive scientific research. The goals of this paper are twofold. Firstly, the authors are presenting an overview of existing research on the topic of big data usage in banks’ risk management by discussing selected aspects of this topic. Secondly, the authors are formulating a proposal on how to strategically use big data in risk management in banks by merging literature based extracted usage of big data with risk management phases. Expected contributions of this paper are systematization of knowledge from available literature and increasing scientific and professional awareness on the topic and potential of big data in banks’ risk management

(So) Big Data and the transformation of the city

The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality