Age old, static pricing strategies no longer work in the modern banking context. Customers are not interested in vanilla services and expect their banks to offer personalized, relevant, and on demand services and products. At the same time, there is increased competition from Fintechs and tech majors. Pricing based on classical methods like cost plus, segment based, or competition based are too risky in the new digital environment. And as seen during the 2008 financial crisis, net interest margins can contract quickly, impacting profitability. Mature banking products make it difficult for banks to pursue volume-based revenue models, and products like credit cards, mortgages, brokerage and checking accounts are turning into commodities. Banking in the complex new digital era calls for dynamic and relationship-based pricing models, and now is the time for banks to reimagine their strategies for better profitability and customer retention.
The Emergence of Value Based Models
The future of pricing lies in the ability of the banks to implement innovative pricing models which are aligned closely to the value crated by the product or service. At this juncture, banks need to consciously move away from older pricing principles to focus on the value delivered by their products. The future of banking is value based and if they do not focus on this essential step, banks will not be able to compete in a value driven market. It is important to understand the true drivers of value for customers to create a successful pricing model. Also, the understanding of what constitutes value is evolving and dynamic. The sector must leverage sound data analytics solutions like AI to drive greater discipline, and structure to their pricing approaches. Effective implementation of future forward pricing models will depend on cutting-edge next gen pricing platforms. These should be able to seamlessly integrate people, technology, process, and governance to roll out comprehensive pricing models that drive better value and RoI.
New age pricing models begin with a shift in focus and approaches – from the bank and product to the customer. Value based pricing models need to understand customer willingness to pay for different products based on value offered, and AI powered platforms are perfectly placed to carry out this exercise. As with most aspects of business today, the key to effective pricing strategies lies in the reams of data in the bank’s repositories. Banks must unify data from across organizational silos and use advanced analytics solutions like Artificial Intelligence to draw usable insights from the data. AI powered technology platforms offer real time analysis of data that can drive better segmentation, and dynamic real time pricing. This can increase customer loyalty, improve customer experience, and would give opportunity to cross sell based on contextual needs to maximize customer lifetime value.
Cost calculations can be expanded out of the traditional parameters to include factors like infrastructure (ATMs, call centers) maintenance costs, cost of technology, product development cost. With this holistic insight into costs and context, banks can come up with better, faster, data driven pricing decisions. This is also the right time to consider strategically unbundling products to establish clear and unambiguous value of each product. This will help the bank to tweak pricing according to the value that product generated for customers. The insights generated from analyzing each product can be utilized in the future as well.
Pricing is central to almost every purchase decision and finding the right balance without getting into a ‘race to the bottom’ with competition is critical. Moving away from outdated models to a technology powered, value-based pricing strategy is now unavoidable as banks seek to navigate an increasingly competitive and complex market landscape.