According to Bjorn Cumps (digital banking professor and director of the Centre for Financial Services at Vlerick Business School), retail banks would find it very challenging to increase net bank income because of the recent financial crisis. So, the only way these banks can look for possible future growth is via technology. Retail banks have been testing with new technology like mobile banking apps, prepaid cards, QR-code based payments, digital advisors, social media analytics tools and location-based services etc. The true winners in retail banking will not be the ones who approve new technology but is the one with new financial ecosystem, including tech companies, energy companies, retailers, real estate agents, notaries, lawyers and many other service providers, offering integrated services that create genuine customer value. Read more at: http://www.theguardian.com/sustainable-business/2014/oct/07/retail-banks-growth-hopes-technology-value-customer-apple-pay

Generally people think that the role of a data scientist is just to examine the relationships between diverse sets of data as well as the disparate systems, processes and locations which store them. But the role is actually mature across certain sectors like retail. With the help of this, Amazon, for e.g., is able to analyze the behavior across multiple accounts, and knows exactly when and why to push a certain product to a customer. But the case is somewhat different in financial services where the role is not properly organized. Though Big Data analytics is used across the retail banking industry from fraud and sanctions management to improving account management processes, analysis of Big Data provides the potential for banks to create new income streams and the sector as a whole is benefitted when it comes to deriving value from vast quantities of information. Thus financial services, in spite of having people with good skills to do modeling and statistical analysis, need people who are able to spot key trends and focuses on looking for the relationships between data across disparate sources. Once these two skills are combined, the financial sector will start to see the rise of data scientists in it like other industries. Read more at:http://www.banktech.com/business-intelligence/piecing-together-the-data-scientist-puzz/240168604

In India, banking industry plays an important role in ensuring the sustainable growth through more credit flows and reaching out to more people by financial inclusion. Thus, the retail banking systems has to handle several issues like customer identity, managing credit risk, fraud detection and prevention, customer relationship maintaining etc. Data analytics helps in this way by ensuring organizations in achieving their growth objectives. It also enables them to manage and automate large volumes of day-to-day decisions. Data analytics draws inferences from large amount of data and use these inferences within banking processes transparently. Data analytics (DA) has an effective use in the following stages of customer lifecycle- Customer targeting -DA helps to develop right offer to right customer by understanding their behavior. Customer Acquisition- DA benefits banks by acquiring profitable customers at low cost and also helps to understand the affordability status of customers. Customer Management- DA helps banks to ensure responsible lending and to undertake effective risk management measures which in turn provide better customer services. Collection- Banks can use DA to reduce delinquency, manage cost of collections, and reduce wasted time by knowing the right value of the customers according to their worth retaining for the future. Read more at:http://www.informationweek.in/informationweek/perspective/287791/indian-banks-improve-customer-lifecycle-analytics?utm_source=rss&utm_medium=rss&utm_campaign=how-indian-banks-can-improve-the-customer-lifecycle-by-using-data-analytics