Behind happy customers, reliable fintech services
---nyse--hpe_1.jpg "Hewlett Packard Enterprise (HPE) Logo")
公司规模
200-1,000
地区
- America
产品
- HPE Alletra dHCI with HPE Alletra 6030 storage array
- HPE ProLiant DL380 Gen10 servers
- HPE StoreOnce backup appliances
- HPE Alletra dHCI software stack
- HPE InfoSight
技术栈
- VMware
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
技术
- 基础设施即服务 (IaaS) - 云计算
- 基础设施即服务 (IaaS) - 云存储服务
- 基础设施即服务 (IaaS) - 私有云
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 网络安全
- 远程资产管理
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
Redpagos is a regional fintech company in Uruguay that enables its customers to pay bills and taxes, deposit and withdraw money from their bank accounts and pension plans, re-up cell phone balances, and even purchase concert tickets or place bets on horse races. Over 2000 companies and virtually all major regional and international banks allow customers in Uruguay to transact business with them via Redpagos. The company attributes its success to its customer-focused culture and its reputation for high-quality services. Customers who prefer the convenience of conducting business over smartphones can use Miredpagos, the Redpagos mobile app. Customers who enjoy a more personal, face-to-face experience can visit any of the company’s national network of over 500 brick-and-mortar franchises.
挑战
Redpagos, a regional fintech company in Uruguay, was facing growing business requirements that prompted the need for new infrastructure. The company's vision was to ensure customer satisfaction and loyalty, and to grow market share by creating compelling new benefits for franchisees. However, the existing infrastructure was not sufficient to support the increasing transaction volumes and protect the company from outages, malware, and natural disasters. The company's IT infrastructure could only accommodate a tenth of its total workforce with virtual desktops, which was not enough capacity to support a work-from-home model. Furthermore, the company's databases house sensitive customer information, and the legacy cloud environment was inadequate due to potential regulatory concerns and customer data privacy concerns.
解决方案
Redpagos decided to work with HPE channel partner Intec Asociados to implement a new private cloud, allowing remote management, ease of use, and enabling the setup of digital workplaces and virtual machines (VMs) in less time. The company chose an infrastructure built on HPE Alletra disaggregated HCI (dHCI) comprised of HPE Alletra 6030 dual controller base array and HPE ProLiant DL380 Gen10 servers, as well as HPE StoreOnce backup appliances. The platform enables Redpagos to achieve the operational simplicity of HCI, with the flexibility to independently scale both compute and storage resources. The company's infrastructure now features an on-premises data center with a duplicate hot backup stack housed by a third-party telco provider. The new HPE infrastructure is much easier and faster to manage, compared to the company’s legacy platform.
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.”
