History of banks is older than all of us. In earlier times, banks used to connect with their customers directly and create customer value by cross-selling and upselling new products. But given the hyper-connected world, we are in today, banks certainly have realized lately the importance of strategizing digitization. While keeping a certain degree of weight to mobile strategy to enhance the customer experience, since, mobility enables banks to reduce operational costs – essentially replacing the branch banking with user-friendly apps.
Mobility helps banks as it
However, the top line growth for these banks is still dependent over mobile analytics which make them realize that the potential for mobile banking extends beyond a cost optimization and customer experience.
Mobile Analytics, thus, becomes most essential. Also for the reasons like:
Analytics is the key differentiator to shift from a “product-centric” approach to a “customer-centric”. It can also help banks to take more proactive measures in retaining and developing their best customers by giving them accurate insights on customers’ needs, propensities to buy new products and potential attritions.
The staggering digital shift in mobile application and platforms has led to the dramatic increase in the potential consumer spectrum and enabled a new cost-effective channel that is available “anytime, anywhere”. In next five years, it is being projected that Internet banking will take the center stage as far as retail-banking transactions are concerned. Wherein, social media will also play a considerable role as a mainstream form of communication playing a potent player to provide information about consumers, their preferences and other important aspects about their personal as well as professional lives. This information is very crucial for banks since this gives a clear understanding of consumer and his behavioral patterns leading them to customize their product and service offerings accordingly. However, to truly leverage on these alternate customer touchpoints, banks need to strengthen their analytical capabilities.
It is assumed that risk-and-fraud management is one of the most common usages of analytical models traditionally. This is true to a large extent, as it enables a bank to assess customer risk profiles more accurately. With this kind of accuracy, they can move from average pricing towards risk-based pricing, while allowing loyal customers to seek better credit terms. Also, analytics allows more sophisticated models using transactional patterns as well as external data which leads to better decision making.
In the current scenario, it has become mandatory to stay competitive, for which banks need to transform their traditional labor-intensive structures into analytics-driven ones for quicker turnaround, consistent outcomes and reduced costs per transaction. It is considered as necessary to integrate operational systems and analytical models so that banks can become self-correcting, thereby providing more accurate results. More so, limited growth in credit expansion and stringent regulatory norms on liquidity have created a low-margin model for banks forcing them to reduce operational costs by driving higher efficiencies and greater automation in customer decisions.
Whenever there is any financial crises occurs, it leads an crushing pressure on banks to meet multiple regulatory requirements in a wide range of areas. Ever increasing requirements make this task even more difficult, and without strong analytics capabilities, these requirements can put a substantial trough on a bank’s resources.
Conclusion: Analytics, this is an indisputable requirement for a bank to be able to compete in an industry governed by economic limitations and increased competition. They can build their capacity to create real-time, targeted offers through the digital channels that their customers are using by gaining insights from social and mobile engagement with their customers. And analytics is the key to success for customer segmentation, campaign, cross-sell and upsell. Some of the other key areas in which analytics can make a significant impact are: efficient capital deployment, improved speed and accuracy of customer decisions, development of differentiated products based on customers’ needs and risk profiles, and reduction in operational costs; thereby allowing banks to become more consistent, competitive and customer-centric.