The ability to leverage and profit from new technologies is at the core of future growth and survival in the transformation journey of banking. The digitization of banking is happening at a faster pace than most organizations can handle. Customer expectations are increasing as well. Innovation is playing a critical role.

Data and advanced analytics have arrived. The volume of available data is growing exponentially, with more added every day from billions of phones, sensors, payment systems, and cameras. Machine learning is becoming ubiquitous, but banks are struggling to turn data into value. The big data revolution happening in and around 21st century has found a resonance with banking firms, considering the valuable data, they’ve been storing since many decades. This data has now unlocked secrets of money movements, helped prevent major disasters and thefts and understand consumer behaviour. Banks reap the most benefits from big data and machine learning as they now can extract good information quickly and easily from their data and convert it into meaningful benefits for themselves and their customers.

Banks internationally are beginning to harness the power of data in order to derive utility across various spheres of their functioning, ranging from sentiment analysis, product cross selling, regulatory compliances management, reputational risk management, financial crime management and much more.

In this article, we are going to identify the current challenges and the need of adoption of new technology by replacing the existing one due to the digital disruption has become essential. It has become imperative for banks to use the Machine Learning and Data Sciences lifecycle for 360 degrees’ view of customer experience and for improved decision making.