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Enhancing long-term customer value has always been at the top of every banking executive’s priority list. However, the rules of convenient banking have changed. No longer does it mean having a branch near your home or office that is open during the time you could get there. It is now about being as close as the nearest mobile device 24x7.

With real-time mobile access to banking services and products, the expected customer experience is rising to new levels. Banks must now understand exactly what their customers want and how they want it delivered. And this is especially important in mature, highly competitive markets – where every customer relationship counts.

Many banks find it difficult to obtain this type of insight. For the most part, they are chained to their outdated, legacy IT applications that are not integrated with each other. There may be one solution just for customer-centric banking processes, while another holds data on transactional banking processes.

Just imagine. Wouldn’t it be great to take this information, consolidate it in one place, and analyze it to find correlations between marketing, sales, and service efforts and resulting customer transactions? What if you had the insight to target each customer with the right product at the right time? Better yet, how would your bank benefit from identifying patterns of customers who might decide to terminate their banking relationship with you?

Of course, all of these capabilities would be ideal and advantageous. As a result, many banks have decided to integrate their various applications to improve business process, enhance insight, and reduce costs. However, having all of this data in one place does present its own challenge – analyzing the data in a manner that generates actionable insight quickly.

In-memory computing gives real-time insights into customer needs and behaviors

With in-memory computing technology, banks can gain a deep, detailed, and real-time understanding of their customers by analyzing a massive amount of data in real time. Doing so enables banks to make responsive – even proactive – business decisions quickly that help minimize customer turnover, detect fraud, and prevent money laundering. Plus, it transforms how all customer-facing lines of business maintain customer relationships.

For a quick win, banks can first implement in-memory computing in existing customer-centric and transactional banking systems. Linking sales, service, and marketing processes to transactional data enables banks to gain a 360-degree, committed view of customer relationships. This enables banks to segment real-time data into target customer groups and give all sales and service reps in every channel immediate access to relevant information on their mobile devices. Plus, banks can create added value by offering customers tools that can help analyze financial habits.

But to create a lasting, positive impact on operations and customer relationships, banks need to go a step further. For example, decision making can be further improved by applying new business rules and other analytical features to the shared database. This setup accelerates end-of-day processing, providing greater flexibility during work hours and increased availability of services. Plus, simulating patterns of customer churn and identifying customers that might defect to other institutions can help reduce losses from account loss, fraud, and money-laundering activities.

To find out how in-memory computing can bring your operational, analytical, and business processes together, please read thought leadership paper “In-Memory Computing for Customer-Centric and Transactional Banking” (registration required).

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