Today I’d like to talk about how banks can gain insights from data. In the past, banks have struggled with financial systems that are outdated, expensive to maintain, inflexible, and unable to support growth and innovation. The data has been fragmented and lacked structure. But in today’s customer-centric banking environment, it’s important for banks to be able to work with all types of data to attract and retain new business.
For banks undergoing IT transformation, IBM systems and storage technologies often play a crucial role in data integration. The integration starts with the storage technologies, which can include DS8800, XIV, SAN Volume Controller, and Storwize V7000. These advanced storage products are supported by the complete portfolio of IBM servers. IBM zEnterprise continues to rank as the definitive data warehouse platform for structured, unstructured and operational data.
Depending on a bank’s IT budget and regional requirements, the IBM PureSystems platform, specifically the PureData processors, offer transactional, high-speed query and operational analytics on an integrated, hybrid frame. Successful management of data can no longer depend on monolithic computer processing. Rather, successful financial sector IT organizations are adopting hybrid architectures that allocate data retrieval and analytic applications across a spectrum of processors best suited for specific workloads.
But installing the latest hardware is not enough. Massive volumes of structured and unstructured financial and operational data (often referred to as “big data”) must be organized and filtered so it can be easily referenced and efficiently transmitted. Using master data management (MDM) techniques, banks can plan, design, and implement information management systems that can connect disparate pieces of customer information across departments, branch locations, and lines of business into a single view. To achieve this efficiency, system architects and database administrators at some major banks are realizing the value of locating their data warehouses close to MDM applications.
For example, Bank of America adopted an MDM Transaction Hub as the system of record for customer, account, interactions, campaign data, and integrated master data records across over 90 applications. By co-locating the data warehouse with the MDM application, Bank of America:
- Reduced IT infrastructure costs because of rationalization.
- Increased revenue and improved product-to-customer ratio through targeted, customer-centric product offers.
- Established a foundation for future product innovations for targeted customers.
The most significant differentiator for managing big data in banks is the ability of IBM storage technology to automatically adapt to information access activity. Real-time data compression and EasyTier technologies provide an adaptive mechanism that automatically monitors data access activity, identifies hot spots within this activity, and reallocates data to meet the information access requirements.
Ken Muckenhaupt is an Executive IT Specialist and Financial Services Sector CTO. He has 35 years experience in IBM hardware and software development. His past assignments include microcode development on IBM’s mainframe processors, management of a mainframe microcode development department, a technology leader assignment for the introduction of object-oriented technology on OS/390, a 3-year assignment in the development and test of IBM’s Component Broker on OS/390, and an 8-year assignment as an e-business on-demand consultant at the IBM Design Center and Center for Solution Integration.
To effectively compete in today’s changing world, it is essential that companies leverage innovative technology to differentiate from competitors. Learn how you can do that and more in the Smarter Computing Analyst Paper from Hurwitz and Associates.