Data intelligence and risk analytics
Data intelligence is the analysis of various forms of data in such a way that it can be used by companies to expand their services or investments(Waller and Fawcett, 2013). Data intelligence is used widely in lots of fields, such as O2O service(He et al., 2016), recommendation system(Pan et al., 2019), energy system (Wen et al., 2019; Xiao et al., 2018), supply chain fields(Corbett and de Groote, 2000; Wu et al., 2019), forecasting management(Yu et al., 2008; Zhang et al., 2009), machine learning(Abadi et al., 2016; Wu and Dash Wu, 2019), and risk identification(Wu and Chen, 2017). The risk exists on many aspects in managemental and economic insights(Chod, 2016; Tang et al., 2017) and so on. Risk analytics combined with data intelligence will provide a brand-new perspective to facilitate industry and society development. However, such massive and invaluable data from risk analytics may bring new challenges such as data processing, data visualization, data-driven decision models, risk decision support systems, etc. in the era of big data.
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