SMU has embarked on a multiyear programme entitled “SMU Bank for Financial Services Education”, referred to as “SMU Teaching Bank“ (or “SMU tBank”). Starting from a clean sheet, we are building a “teaching bank” from the ground up, using today’s architecture best practices.
“The mission of SMU tBank is to become a world class ‘teaching bank’, generating an on-going supply of undergrad and postgrad student projects whereby classroom learning outcomes can be put into practice, leveraging industry leading banking software and enterprise platforms.”
Principle 1 - SMU tBank shall exist for academic purposes only, to support banking related coursework, labs, and student projects.
Principle 2 - SMU tBank shall align to, and inform, SMU’s Unified Banking Process Framework.
Principle 3 - SMU tBank shall be assembled using a mixture of vendor products, in order to demonstrate real world large-scale change scenarios, for example:
Retail Banking – Students use SMU tBank to learn banking processes such as; account opening, credit evaluation, loan repayments, fund transfers, foreign exchange, standing instructions, GIRO, mobile payments, Two-Factor-Authentication, ATM network management, real-time customer specific promotion offers. Lab questions assess the students understanding of both bank processes as well as financial accounting.
Enterprise Integration – Students use SMU tBank to learn integration technologies such as; Message-Oriented-Middleware, and Service-Oriented-Architecture. Labs exercises include; building integration components that allow different applications in the bank to communicate, and drill-down visualizations of what is actually happen in the integration layer when a fund transfer is executed, for example.
Architectural Analysis – Students use a “lite” version of SMU tBank which is deployed on their laptops, to demonstrate their understanding of 3 main architecture principles; “resiliency” (ability to failover to a standby system), “concurrency” (handling large number of users), and “performance” (response time of the application).
Enterprise Architecture in Banking – Covers EA best practices in a banking context; alignment to business strategy, EA frameworks and tools, banking industry information models, enterprise platforms (SOA, BPM, BRMS, MDM, EDW), EA principles and design patterns, EA blueprints and roadmaps. Case studies on EA practices in banking. Case study on SMU tBank.
In-Memory Data Grid Use Cases in Banking – Covers performance improvements of data caching, eg; characterization of response times with and without a data cache in front of the core banking system, and the resulting impact on customer satisfaction. Also covers the economics of caching data in front of the core banking system, eg; the cost saving in MIPS incurred on mainframe systems. Covers how massive-scale in-memory data grid technology is used to enable real-time cross-sell to banking customers, eg; next best offers pending in memory, triggered on the next customer interaction. Covers real-time fraud detection.
Core Banking System Replacement – Covers the scenario where a core banking system is replaced, eg; Oracle Flexcube is replaced with Infosys Finacle. The transition from one system to the other can be done with minimum impact to banking channel applications, by using a flexible service oriented architecture. Using SMU tBank as a test bed, specific scenarios can be trialed in conjunction with actual banks in Singapore that want to participate in the study.
Bank Mergers: Technology Migration or Coexistence – Covers the scenario whereby one bank acquires another, and the combined bank needs to make decisions about which technology to keep or discard, and which technologies can coexist. The coexistence of different technologies across the two banks can be achieved with minimal impact to banking channels, by using a flexible enterprise platforms such as; SOA, BPM, BRMS, and MDM. Using SMU tBank as a test bed, specific scenarios can be trialed in conjunction with actual banks in Singapore that want to participate in the study.
Banking Industry Information Model – Covers the adoption of the Banking Industry Architecture Network (BIAN) Service Landscape as the enterprise data model for SMU tBank. The study will demonstrate, in actual practice, how an industry model can inform and optimize the decomposition of banking processes into reusable services.