IBM Grid Offering for Analytics Acceleration: Customer Insight in Banking

Grid Computing

customers. Often, banks may pur- chase lists and acquire external data to improve their models. This data, although useful, can be expensive to acquire and will require additional resources for cleansing, integration and analysis.

Because acquiring new customers is more expensive than keeping existing ones, and because customer bases are under constant attack from com- petitors, customer retention is a key issue. Banks must be able to predict The challenges facing customer which customers are likely to leave, Highlights insight in banking what incentives would urge them to stay and when to stop investing in an In an environment of intense global ■ Helps improve the use of compute unprofitable customer. As well, banks competition, banks today are faced and information resources across are trying to expand existing cus- with higher customer attrition caused an organization tomer relationships and create cross- by increased competition. They are sell or upsell opportunities without ■ Accelerates time to results and under pressure to acquire new cus- further driving attrition. increases the number of modeling tomers and retain existing ones in the iterations achievable within a most cost-effective manner possible. To be successful, then, banks must given timeframe understand and predict customer However, new customer acquisition is needs by combining products and ■ Offers an affordable, flexible and difficult, with extremely low response services and applying them consis- resilient IT environment for fast, rates. To reduce customer acquisition tently through appropriate distribution large-scale analysis costs, banks must create efficient models to determine which customers ■ Enables secured and immediate are high value and what marketing access to derivative information strategies will best draw those desired Grid Computing

channels and networks. In addition, between winning or losing a cus- IBM has created an integrated grid- banks must attract customers that tomer. To overcome these barriers, based technology and service will maintain their profitability while banks require a technology infra- offering that can enhance a bank’s reducing their risk. However, to apply structure that can accelerate cus- competitiveness by accelerating these strategies, they must sift tomer insight applications in a customer insight applications. A grid- through tremendous volumes of resilient, scalable and cost-effective enabled infrastructure reduces the customer data that may be stored in manner. cycle time for executing statistical disparate data formats and located models, leading to more sophisti- in repositories scattered across the IBM Grid Offering for Analytics cated analyses and increased enterprise. Acceleration: Customer Insight in accuracy of customer acquisition, Banking retention, cross-sell and upsell by Coupled with the difficulty in handling The IBM Grid Offering for Analytics enabling a larger number of modeling customer data, banks may discover Acceleration provides an efficient, iterations in a shorter timeframe. that their IT infrastructures for cus- scalable and standards-based solu- tomer insight are siloed and ineffi- tion to the most pressing issues fac- The IBM offering provides a cost- cient. Because of resource limitations ing banks today. IBM, working with effective model for acquiring, de- and inefficient use of available com- key partner SAS, the first enterprise ploying and managing resources. pute power, these infrastructures business intelligence vendor to join Because the existing infrastructure have a limited ability to run multiple the Global Grid Forum, built a new that supports customer insight does affinity analyses within a needed grid offering for customer insight in not need to be replaced, firms can timeframe—which can be real time. the banking industry. The SAS® leverage their existing capital invest- Their limitations prevent banks from Credit Scoring application, part of ments, optimizing the efficiency of obtaining timely, accurate models SAS Banking Intelligence Solutions, their customer insight business and that can make the difference showed that complex credit scoring applications while migrating to a applications can be grid-enabled. higher performance, lower cost, stan- such as compute resources, data Use case: gaining a competitive dards-based infrastructure. In addi- storage and filing systems to create a edge through target modeling tion, this grid infrastructure can be single, unified system and to address IBM and SAS developed a means to used for compliance, fraud detection fluctuating workload requirements. extend the value of the SAS Credit and other risk management functions. Scoring application to the grid envi- As required by an opportunity man- ronment, as demonstrated in a real- The IBM Grid Offering for Analytics ager’s analyses, the grid makes addi- world scenario involving a financial Acceleration allows businesses to run tional compute capacity available on services institution that offers a full their existing analytics software, a full-time or part-time basis. It helps range of banking products and serv- whether custom-built management banks leverage available, under- ices to its member customers, includ- systems, best-of-breed commercial utilized compute capacity within their ing wireless and Internet banking, applications or a combination thereof. existing IT infrastructures, thus help- loans, credit card services and sav- The offering’s open, flexible infra- ing them to reach end results far ings and investment services. Having structure supports a wide range of more rapidly than within conventional already acquired more than 70 per- packaged and custom analytical computer environments. Compared to cent of its established market in its applications, including SAS applica- a non-grid solution, the required com- geographic area, the institution tion software. pute resources are fewer and easier wanted to expand its membership to manage—contributing to reduced charter to the larger community. The IBM offering centers around grid total cost of ownership (TCO). The However, to compete effectively in computing, an architectural approach IBM offering also provides a level of this new market space, the financial that enables distributed computing resilience to help guarantee workload services institution needed to under- over the Internet, an intranet, a virtual execution. stand how to attract new prospective private network or some combination members and tailor profitable prod- thereof. This approach can help ucts to meet their needs. aggregate disparate IT elements Grid Computing

IBM first assessed the business The institution’s customer insight IBM ^ BladeCenter was inte- processes, available customer infor- application was enabled to leverage grated with the grid by GridServer mation and IT infrastructure of the computational services by using to create an on demand, dynamic financial services institution. The the DataSynapse GridServer™ ap- provisioning capability that could results of the assessment determined plication programming interface assure the right resources were avail- that the financial services institution (API) to connect and parallelize ap- able at the right time to meet the run- had a wealth of information about its plication service requests to scale time servicing requirements of the current customer base, but needed to effectively when distributed across an risk applications. In addition, the acquire additional customer informa- available infrastructure. The solution IBM WebSphere® Application Server tion from a third party. The institution implemented the policy-driven man- was integrated with GridServer and needed to organize this data so that it agement functions of GridServer to Avaki Data Grid to provide portals for could be accessed using business handle application workload servic- grid users. These portals were devel- intelligence tools that generate target ing, resiliency and service provision- oped using the WebSphere Studio modeling applications. IBM further ing. The grid infrastructure used Application Developer tools. determined that running the target UNIX® systems—Sun Solaris and modeling applications in a grid envi- IBM AIX®-based servers—along Improved productivity and efficiency ronment would give the financial insti- with the Microsoft® Windows® through a multistage implementation tution a greater degree of flexibility for operating system, Linux-based Banks can take their existing virtual fine-tuning the models, because it IBM ^™ BladeCenter™ pool of compute resources for cus- would be able to run these models on servers and Linux-based workstations tomer insight and gradually grow it demand. to satisfy the performance, scalability into an integrated, highly efficient grid and systems management integration system. As shown in Figure 1, an requirements. existing customer insight infrastructure may comprise disparate islands Figure 1. Customer insight infrastructure before applying the grid Grid Computing

of statisticians, administrators and Statisticians can access these all applications can become com- heterogeneous compute and storage resources through a single, common pletely grid-enabled; all compute and resources, along with various ver- interface. In addition, a single admin- storage resources across the enter- sions of a customer insight applica- istrator can manage the grid through prise become one large resource tion. Additionally, users (subscribers) an administrative portal. All sub- pool for the applications. cannot monitor the progress of a sta- scribers can access the grid to view tistician’s analyses. their results and actively participate in IBM services to support grid the development of the information computing Using its existing infrastructure, a product, leading to a tighter inter- IBM Global Services provides world- bank deploying the SAS Credit action with the business process. class, worldwide support for all ele- Scoring application can utilize inte- Finally, based on established priori- ments of the grid architecture— grated SAS technology to parallelize ties and rules, a shared pool of servers, storage, operating systems, the application across heterogeneous resources can be provisioned when middleware and networks—with a full computers and data. The result is a needed to handle the peak require- range of grid-related services. As a SAS application that runs significantly ments of the combined group. The first step toward grid implementation, faster by distributing the workload run time for the application can be IBM Global Services offers assess- across the compute and storage dramatically improved in a linear ment services that help identify resources supporting that application. fashion. whether an application qualifies for grid enablement. An assessment will By adding middleware from The bank can then apply the same look at historical resource consump- DataSynapse and Avaki (Figure 2), a process with another application, for tion by identified applications, the grid is created by joining disparate example, a simulation application for application architecture and the sup- application installations, heteroge- customer value modeling. Over time, porting infrastructure platform. In neous computers and data (Figure 3). addition, the IBM grid valuation tool, Figure 2. Adding grid middleware to virtualize resources Grid Computing

Figure 3. Customer insight infrastructure after applying the grid IBM Grid At Work, can perform a Technologies powering the grid scheduling so that applications can high-level cost-benefit analysis on The workhorses of the IBM analytics run much more efficiently across the the migration to a grid computing acceleration grid infrastructure are grid, drawing idle capacity from the platform. the grid engines—desktop PCs or virtualized resources. Centralized servers that run the UNIX, Microsoft scheduling also improves the appli- If a grid infrastructure is warranted, Windows or Linux operating systems. cation’s resiliency; in case of machine IBM Global Services creates a com- These compute resources execute failure, the grid simply moves a job prehensive implementation plan, various jobs submitted to the grid, from one server to another. which includes architectures and and have access to a shared set of designs for application enablement, storage devices. The IBM Grid Offering for Analytics data modeling, grid middleware, Acceleration can include SAS tech- infrastructure and management tools, To accelerate an application, the nology and relies on grid middleware grid management process and compute and storage resources sup- from DataSynapse and Avaki to cre- support-organization skill require- porting that application must be virtu- ate distributed sets of virtualized ments. IBM Global Services, working alized. For SAS applications, SAS resources. SAS is a market leader in with IBM Business Partners, then technology exploits the power of providing a new generation of tests and installs the various compo- many computers in a network to solve business intelligence software and nents of the grid system, including a problems requiring a large number of services that create true enterprise portal, grid middleware, scheduler processing cycles and involving huge intelligence. This project builds on a and security. In addition, IBM Global volumes of data. Grid middleware quarter century of successful SAS Services will enable existing hard- provides dynamic, policy-based and IBM collaborations. ware and aid in skills transfer. Grid Computing

The production-proven, award- customer insight applications access has defined an open source grid winning DataSynapse GridServer data directly from distributed produc- reference architecture and a set of application infrastructure platform tion sources, transparently and in real tools to assist grid deployment. extends applications in real time to time. operate in a distributed computing IBM Design Centers use the latest environment across a virtual pool of IBM as a leader in grid computing grid technologies, including the Open underutilized compute resources. IIBM is committed to open standards Grid Services Architecture (OGSA), GridServer application interface and is working with The Globus which merges the open protocols modules allow customer insight Alliance open source development used for grid computing with the pro- applications and next-generation community, the Global Grid Forum tocols used for Web services. IBM development of customer insight and the Interoperable Informatics Design Centers provide access to application platforms to be grid- Infrastructure Consortium (I3C) to pro- the latest software from leading enabled. mote the adoption of open standards grid software companies, such as and accelerate the availability of grid DataSynapse and Avaki, and the For the virtualization and integration technology. latest open source grid technologies of distributed data, the IBM Grid from The Globus Alliance. Offering incorporates the Avaki Data IBM is a strong supporter of The Grid information integration software. Globus Alliance, a multi-institutional A strong foundation for successful This application enables fast, easy research and development effort customer insight and secure access to structured and to address the technical and busi- IBM is the industry-leading supplier of unstructured data across depart- ness challenges of grid computing. grid solutions, services and expertise ments, locations and companies. Founded by a team of technicians to the scientific and technical commu- The software also lets users and and researchers, The Globus Alliance nities, as well as to the financial services sector. IBM Grid Computing is currently engaged with more than wide array of products and serv- In addition, IBM has established 20 major financial institutions in North ices—as well as its multiplatform strong working relationships with America, Europe and Japan, and expertise—IBM is taking an inte- leading-edge partners, including more than 100 organizations world- grated and comprehensive approach SAS, Avaki and DataSynapse. Thanks wide. Leveraging its considerable to this new computing paradigm. to these relationships, IBM can pro- experience in implementing commer- vide banks with a full set of tools and cial grids worldwide, IBM has created Years of experience and solid expert- capabilities to enable a grid solution. the IBM Grid Offering for Analytics ise enable IBM Global Services to Acceleration: Customer Insight in help banks adapt grid computing to Backed by IBM, companies world- Banking to meet the unique grid com- serve their unique business environ- wide are discovering how grid puting needs of the banking industry. ments. IBM Global Services has computing enables them to capture trained grid computing technology customer loyalty and value and to In an ongoing effort to support the experts in the Americas, Asia Pacific generate sustainable competitive establishment of open standards, IBM and Europe, allowing companies advantage in financial services. is designing its systems to participate worldwide to take advantage of a in grid computing. Leveraging the comprehensive range of IBM assess- breadth and depth of the company’s ment, design, implementation, opti- mization and support services. For more information To learn more about grid computing for analytics acceleration in banking, contact your IBM representative or © Copyright IBM Corporation 2003 IBM Business Partner, or visit IBM Systems Group ibm.com/grid. Route 100 Somers, NY 10589 Produced in the United States 09-03 All Rights Reserved IBM, the IBM logo, the e-business logo, AIX, BladeCenter, eServer and WebSphere are trademarks or registered trademarks of International Business Corporation in the United States, other countries or both. GridServer is a trademark of DataSynapse, Inc. in the United States, other countries or both. Microsoft and Windows are trademarks of Microsoft Corporation in the United States, other countries or both. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. UNIX is a registered trademark of The Open Group in the United States and other countries. Other company, product and service names may be trademarks of others. References in this publication to IBM products or services do not imply that IBM intends to make them available in all countries in which IBM operates. Performance estimates based on laboratory testing may not be typical, and may not be achievable in all customer computing environments. IBM hardware products are manufactured from new parts, or new and used parts. In some cases, the hardware product may not be new and may have been previously installed. Regardless, our warranty terms apply. All information in these materials is subject to change without notice. ALL INFORMATION IS PROVIDED ON AN “AS IS” BASIS, WITHOUT ANY WARRANTY OF ANY KIND.

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