By Jaya Vaidhyanathan
Recent banking reforms are forcing the industry to relinquish age-old techniques of data analysis and modelling, and adopt more rewarding technologies. With digitization, the volume of data has increased in leaps and bounds. The technology available with most banks is no longer adequate to process all of this data. Not only is an alarming amount of data going to waste, along with it, valuable insights are being lost to the industry.
Enabling the paradigm shift
Luckily, technology advances have facilitated the creation of tools that could handle previously unimaginable amounts of data. There is no longer a dependence on data that is “clean” and computationally manageable. The banking industry is adopting such new and emerging technologies – like big data, AI/ML and analytics – to:
Make sense of unstructured data: Massive volumes of unstructured data are being generated every day. Traditional risk management practices that rely heavily on structured data are rendered inefficient. Using advanced technologies like big data, data analysts can make order out of the chaos and extract critical insights.