Quintillion 在保持精简人员配置水平的同时，业务量翻倍，投资者服务增强
公司规模
Mid-size Company
地区
- Europe
国家
- Ireland
产品
- IBM Case Manager
技术栈
- Enterprise Content Management
- Business Process Management
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
技术
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 金融与保险
适用功能
- 商业运营
服务
- 软件设计与工程服务
- 系统集成
关于客户
Quintillion 是一家总部位于爱尔兰都柏林的对冲基金管理公司。作为 US Bancorp 的间接全资子公司，Quintillion 为从大型跨国公司到精品私营公司的客户提供各种基金管理、后台支持和股东服务。Quintillion 以提供高度响应、亲力亲为的基金管理方式而自豪，通过一支专业的专家团队为每一位客户提供服务。对于这些团队来说，提供优质端到端服务的关键是确保所有客户疑问都能得到迅速而专业的解决。
挑战
Quintillion 是一家对冲基金管理公司，该公司希望在保持业务盈利增长的同时，不牺牲客户所期望的高质量个性化服务。对于他们的每只基金，都有大量相关文档需要处理和持续访问，例如电子邮件、申请表、财务报表等。他们的团队需要即时访问这些内容，以便有效地为客户提供服务——他们不能浪费时间在系统中筛选特定信息。
解决方案
Quintillion 与 IBM 业务合作伙伴 Insight 2 Value 合作，部署了一个基于 IBM® Case Manager 软件的定制平台，用于管理端到端基金管理和客户互动。该解决方案为各种格式的内容提供了一个集中存储库，包括电子邮件、扫描图像、电子表格、PDF 等。该解决方案允许工作人员将相关内容分组到单个电子记录中，帮助加快对关键信息的访问，并确保始终有效处理客户查询。除了加快信息访问速度外，Quintillion 还使用 IBM Case Manager 创建自动化工作流程，指导工作人员完成每份文档所需的流程步骤，并通过复杂的检查表功能提供每个案例当前状态的概览。
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.”
