Big Data analytics for transaction banking: The differentiator

Abstract

In the wake of increased regulatory compliance and intense competition, transaction banks today have been emphasising differentiating themselves by improving customer experience and offering relationship-based value-added services. Traditionally, transaction banks have stored large pools of data sourced from financial transactions, exchange rate feeds and customer information. Burdened by ageing IT applications, fragmented infrastructures and archaic data extraction technologies, banks have not been able to derive value from these data pools. But this trend is likely to change with the emergence of Big Data analytics technologies. Given the advantages such technologies offer, we believe Big Data analytics will play an important role in shaping the future of transaction banking, especially in enriching customer experience and offering new revenue streams. This paper presents an awareness of how transaction banks can leverage the benefits of Big Data analytics and apply these within their organisational boundaries. We have focused on a number of analytics tools available in the market that may be of interest for transaction banks. We have also highlighted some of the challenges transaction banks might face when implementing a Big Data analytics framework and have presented our point of view on how best to manage them. Finally, drawing experiences from the transaction banking industry, we have highlighted some business cases/use cases of value.