How to Use In-Memory Computing to Improve Your Bank’s Performance
By Eric Stine
How much do you know about your customers? Can you capture every interaction they have with your bank and act on the information?
Imagine a customer who is logged on to your website. She has significant savings. Over the past six months, she’s moved to a higher yield account, ramped up her savings and made fewer purchases on her bank-issued credit card. She’s looking at home mortgage rates on your website right now. She currently rents her apartment. Perhaps she’s even asked colleagues on LinkedIn about buying a first home, or complained to her Facebook friends about a rent increase.
Would you offer her a mortgage? More importantly, which product? Does her behavior indicate she’d be more comfortable with the predictability of a fixed rate? Or does the data indicate that she is likely to be in the home for only a few years before moving to a larger home or another neighborhood? Perhaps a larger down payment and an adjustable rate mortgage or interest-only product with a lower rate would enable her to have both equity and the lower payments that permit saving towards a larger investment down the road.
Finally, what does your data tell you about channel behavior? Does she meet the profile of a researcher that you should push a targeted direct mail to? She appears to be tech-savvy, though – perhaps a timely live interaction via web chat would increase the chance you’ll take the application today? And would other products or services, like a high-yield savings account that reduces her interest rate by one-eighth or one-quarter, secure her business and increase your share of wallet?
Like every other business, banks today are focused on knowing as much as possible about their customers. In other industries such as retail where large volumes of data are collected and analyzed, in-memory technology is already being adopted to manage offers, enhance customer loyalty, and improve consumer sentiment. Similarly, the banking industry is adopting this technology to provide the kind of personal service that builds trust and loyalty, and boosts wallet share.
In-memory computing is helping banks surpass traditional models of customer service. It is fundamentally changing the way banks collect, store and use their vast capacity of data. The technology uses a central database and enables banks to rapidly process massive amounts of customer-centric and transactional banking data across channels, creating holistic, real-time profiles of customers and groups of customers.
The data can be used to develop targeted marketing campaigns; prevent defections by identifying customers at risk of moving to a competitor; detect identity fraud and prevent money laundering; and quickly identify new trends, segments or behavioral patterns.
In-memory computing can provide insight into how branches, ATMs, products and personnel are performing, overlaying that information with customer and segment data. The result is better decision-making about hiring and training, staffing and hours, and branch and ATM openings and closures. Most importantly, the ability to make decisions about which products and services to create, maintain or discontinue – along with the ability to identify affinities, halo effects and target markets for those products and services – better enable banks to make the right offer to the right customer through the right channel.
In-memory computing improves on many banks’ existing technology. It’s extremely fast, as much as 3,600 times faster than standard analytical computing. It replaces outdated, patchwork IT systems that segregate data and store it on different servers, making fast retrieval and analysis difficult or impossible. It is also more efficient and can help control costs.
While the benefits are substantial, building an in-memory computing system can appear daunting. But banks can start small and still achieve significant benefits. They can use a phased approach, such as starting with one or two channels or business functions, and then expand the effort over time.
Whatever route a bank chooses, it should have a road map for each in-memory use case that aligns with its overall business strategy. It should also create a prioritized list of business objectives. The four-step assessment that follows answers important questions and can serve as a guide.
Step 1: Where can in-memory computing deliver additional benefits and create value?
The first phase includes analyzing current business strategy, existing business processes, impacted lines of business, and software assets – aligning business and IT strategies towards a common set of goals. It also explores the business requirements and opportunities in the use cases where in-memory computing could be best applied.
Step 2: What would a target IT architecture using in-memory computing look like?
The second step involves developing a target application portfolio and the target architecture for both in-memory computing solutions and supplemental solutions. This step also focuses on creating high-level prerequisites for the technical infrastructure and its blueprint, as well as identifying the potential risks, strengths and weaknesses of the new landscape.
Step 3: Which is the best transformation path to integrate in-memory computing?
The third phase of the assessment centers on defining implementation and migration scenarios for the new landscape. It also establishes a project framework and master plan that include organization structure and required governance.
Step 4: What are the benefits and risks of implementing an in-memory computing system and when will the investment pay off?
The last assessment phase weighs one-time investment and recurring costs against potential tangible and intangible benefits using a return-on-investment calculation and high-level risk analysis.
Enhancing long-term customer value and reducing the cost and complexity of operations top the agenda of many bank executives today. In-memory computing has emerged as an essential advantage. Imagine what could have happened with the prospective homeowner described above if the bank didn’t have the technology needed to capture and analyze her behavior from multiple angles. It would have been impossible to be the first bank to get in front of her at a pivotal time with the right product.
In-memory computing takes customer insights to a new level. If banks aren’t feeling a sense of urgency, they run the risk of falling behind. In a competitive marketplace, in-memory computing can offer the rapid, personal service that cements customer relationships, and help banks find new opportunities for growth.■