Published on March 11, 2014
To understand your customers more fully and create exceptional banking products and services that drive long-term customer rela- tionships, you need information that is timely, reliable, and robust. In-memory computing helps you quickly process massive amounts of data related to your customers and their transactions.You get the information you need to make rapid business decisions, minimize customer turnover, detect fraud, and prevent money laundering. CREATING PROFITABLE CUSTOMER RELATIONSHIPS FOR THE LONG HAUL Enhancing long-term customer value tops the agenda of every bank executive today. It’s especially important in mature, highly competitive markets – where each customer relationship must be as proﬁtable as possible. Real-time access to banking services and products via mobile devices creates a new level of customer expectations. To stay in the game, you must oﬀer innovative products and services quickly and ﬂexibly using accurate, real-time knowledge of customer preferences and banking habits. MULTIPLE SYSTEMS GIVE WAY TO A CONSOLIDATED LANDSCAPE Many banks ﬁnd it hard to get useful information because they are chained to outdated IT architectures. Applications for customer-centric banking processes (for marketing, sales, and service) and transactional banking processes (for deposits, loans, investment, collateral, and payments) have increased signiﬁcantly in recent years. As a result, you’re probably using a variety of technologies and databases from diﬀerent vendors. In addition, your customer-facing information is probably not integrated with your transactional data. In-Memory Computing In-Memory Computing for Customer-Centric and Transactional Banking Creating a Holistic View of Customers for Timely, Innovative Oﬀerings
Most banks use a single repository to handle customer-related data. For transactional banking, there are usually silos of appli- cations for individual products and organizational units (see Figure 1). You have to adapt this heterogeneous landscape to integrate data, analyze it holistically, and create uniﬁed proﬁles of indi- vidual customers or groups of customers. Most banks ﬁnd it very costly and time-consuming to normalize data into a single format for calculations and other analysis. To enhance perfor- mance, they may strip down or aggregate information. This makes it diﬃcult to target customers with the right products at the right time or identify patterns of customers who might terminate their banking relationships. A distributed system can also be very expensive to maintain. As a result, many banks have realized that consolidating their software is vital to improv- ing their business processes and reducing costs. IN-MEMORY COMPUTING GIVES YOU REAL-TIME CUSTOMER INSIGHTS In-memory computing technology can provide deep, real-time insight into your customers by helping you analyze massive quantities of data in local memory. Up to 3,600 times faster than standard analytical computing, in-memory computing also gives you highly granular insight into data.You can manage larger volumes of data while reducing IT complexity. As you gather reliable information from a single source, you reduce the cost of operating your analytical systems. You can move into in-memory computing in several steps, according to your needs. For a quick win, you can ﬁrst use in-memory computing in your existing customer-centric and transactional banking systems. In addition to creating a 360-degree,“total commitment” view of relationships with your most valuable customers, you can link sales, service, and marketing processes to information held in transactional- banking systems. You can also give customers tools for analyz- ing their own ﬁnancial habits – thereby enhancing satisfaction, revenue, and proﬁtability. In addition, you can segment real-time data into target customer groups and give sales and service employees immediate access to this and other information on their mobile devices. Access to multiyear payment transactions helps service employees and sales representatives manage cross-selling and up-selling activities. Figure 1: Typical Architecture Pattern for Customer-Centric and Transactional Banking Today Customer-Centric and Transactional Banking Customer information management Business partner/ opportunities/ total commitment Sales Service Customer-Centric Banking Transactional Banking Master data and business trans- actions Master data and business trans- actions Master data and business trans- actions Master data and business trans- actions Master data and business trans- actions Loans Invest- ments Collat- erals Deposits Pay- ments Replication Marketing
In a second step, you can use the shared database to build new rules engines and other analytical features that improve decision making. You can simulate patterns of customer churning and identify those who might defect to other institutions. Over time, you can integrate your customer-centric and transactional banking processes with your processes for analytical banking. In this scenario, your applications for customer-centric and transactional banking share a common database. This includes applications that handle information on business partners, new market opportunities, and total customer commitment as well as those that manage your product-related master data and business transactions (see Figure 2). This setup lets you accelerate end-of-day processing, which can provide greater ﬂexibility during working hours and increase the availability of services. It can also help you identify patterns of fraud and money-laundering activities in real time and signif- icantly reduce losses in these areas. FINDING THE RIGHT PATH TO IN-MEMORY COMPUTING The in-memory computing technology oﬀered by SAP HANA® appliance software can drive business and IT transformation at your bank by signiﬁcantly streamlining data analysis. SAP HANA combines an in-memory computing engine with commodity hardware systems designed to process massive quantities of real-time data. We can help you get the greatest beneﬁt from in-memory computing by discussing where you want to use the software and assisting in its implementation. Together we can: • Use in-memory computing to align your business and IT strategies • Discover areas in which SAP HANA can deliver additional beneﬁts and value • Develop a business case for SAP HANA • Develop a target architecture for your business processes and the applications that support them • Choose the best transformation path for integrating SAP HANA into your business We help you deﬁne a road map for each in-memory use case that aligns with your overall business strategy, create a priori- tized list of objectives for in-memory support, and determine how to meet those objectives. This road map answers the following questions: • Where can in-memory computing deliver additional beneﬁts and create value? • What would a target IT architecture using in-memory computing look like? • Which is the best transformation path to integrate in-memory computing? • What are the beneﬁts and risks of implementing SAP HANA, and when will the investment pay oﬀ? Figure 2: Future Architecture for Customer-Centric and Transactional Banking with In-Memory Computing Business partner/opportunities/total commitment/ product-related master data/business transactions (in-memory) Customer-Centric Banking Transactional Banking Customer-Centric and Transactional Banking Loans Invest- ments Collat- erals Deposits Pay- ments Customer information management Sales ServiceMarketing
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