公司规模
Large Corporate
地区
- Asia
国家
- Japan
产品
- IBM® WebSphere® Message Broker
- IBM® zEnterprise® 196
技术栈
- IBM WebSphere
- SUSE Linux Enterprise Server
- IBM logical partitioning
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Cost Savings
技术
- 基础设施即服务 (IaaS) - 云中间件与微服务
- 基础设施即服务 (IaaS) - 混合云
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 过程控制与优化
- 实时定位系统 (RTLS)
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
三菱东京日联银行 (BTMU) 是日本资产规模最大的银行,拥有 4000 万个个人银行账户和 50 万家企业客户。该公司在 40 多个国家/地区提供金融服务。在当今的银行业环境中,金融机构的竞争重点在于快速推出产品和服务并通过新渠道交付的能力。银行客户希望能够随时随地在任何设备上自由地执行各种交易。当 BTMU 开发面向服务架构 (SOA) 平台来实现这一“云银行”概念时,它发现长期有效利用现有业务系统和信息至关重要。
挑战
三菱东京日联银行 (BTMU) 需要满足客户随时随地通过任何设备访问金融服务的需求。该银行试图仅使用其现有的 IT 资产来推出这些新服务。在当今的银行业环境中,金融机构的竞争重点在于快速推出产品和服务并通过新渠道交付它们的能力。当 BTMU 开发面向服务架构 (SOA) 平台来实现这一“云银行”概念时,它发现长期有效使用现有业务系统和信息至关重要。该银行的首要任务是确保对现有系统零影响。
解决方案
该银行采用了 IBM® WebSphere® Message Broker,它拥有基于 MQ 的高吞吐量消息传递主干,在金融领域有着成功的记录。SOA 解决方案采用 IBM zEnterprise® 196 大型机作为平台,以 SUSE Linux Enterprise Server 作为操作系统,并由 IBM 逻辑分区划分。然后使用 IBM WebSphere Message Broker 构建基于 MQ 的高吞吐量消息传递主干。SOA 平台还将 BTMU 系统与日本银行的系统相链接,使该银行能够在 Zengin 系统(日本银行的支付清算网络)内清算大量资金转账数据。
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”