A data-driven approach is emerging across the banking sector, affecting banks’ business strategies, risks, technology and operations. Corresponding changes in mindset and culture are still in progress. Following the cross-sectoral report by the Joint Committee of the European Supervisory Authorities (ESAs) on the use of big data by financial institutions, and in the context of the EBA FinTech Roadmap, the EBA decided to pursue a ‘deep dive’ review on the use of big data and Advanced Analytics (BD&AA) in the banking sector. The aim of this report is to share knowledge among stakeholders on the current use of BD&AA by providing useful background on this area, along with key observations, and presenting the key pillars and elements of trust that could accompany their use.
The report focuses on BD&AA techniques and tools, such as machine learning (ML) (a subset of Artificial Intelligence (AI)), that go beyond traditional business intelligence to gain deeper insights, make predictions or generate recommendations using various types of data from various sources. ML is certainly one of the most prominent AI technologies at the moment, often used in advanced analytics due to its ability to deliver enhanced predictive capabilities. …
Quelle / Link: EBA report identifies key challenges in the roll out of Big Data and Advanced Analytics
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EBA identifies trust challenges from growing use of Big Data and AI in finance