In January, the European Banking Authority (EBA) published a report identifying four key pillars for the development, implementation and adoption of big data and advanced analytics (BD&AA), which interact with each other and are thus not mutually exclusive.
These pillars require review by institutions to ensure they can support the roll-out of advanced analytics.
The first, data management, enables the control and security of data for enterprise purposes, taking into account data types and data sources, data protection and data quality. A successful data management approach, which builds trust and meets legal requirements, could lead to improved decision-making, operational efficiency, understanding of data and regulatory compliance.
The second is technological infrastructure, which entails processing, data platforms and infrastructure that provide the necessary support to process and run BD&AA.
Appropriate internal governance structures and organisational measures was the third area highlighted, along with the development of sufficient skills and knowledge to support the responsible use of BD&AA across institutions and ensure robust oversight of their use.
Finally, a methodology needs to be in place to facilitate the development, implementation and adoption of advanced analytics solutions. The development of an ML project follows a lifecycle with specific stages (data preparation, modelling, monitoring) that differs from the approach adopted for standard business software.
©The Science of Investment 2020
TOP OF PAGE