Download PDF
Avatrade
Technology Category
- Application Infrastructure & Middleware - Data Visualization
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- System Integration
- Software Design & Engineering Services
The Challenge
With its multiple systems, Avatrade has been generating and gathering large amounts of data for years. Former CTO with a strong technical background, Mr. Lee Levenson, currently VP Operations of AvaTrade, took it upon himself to search out a better Business Intelligence solution for his company. “Our goal was to give a single view from different angles to different people that previously had taken three or four windows from different systems, with business analysts having to export reports into CSV or Excel to generate beforehand. We wanted to replace the need to manually mash all the data together,” explained Levenson. This huge quantity of data, spread over multiple platforms, meant that getting any report done was laborious. “R&D was writing queries, and making very simple reports for whoever needed them before. As is typical in any developed solution, when a report had to be changed or a new report had to be done, it went back to the R&D queue. These requests had to be prioritized. At times this was a huge bottleneck for us,” said Levenson. It was very important to the company to find a tool that would be cost effective, and quick and relatively easy to deploy. A key factor in choosing a BI software was that it be almost exclusively driven by the business user: meaning that anyone in the organization could create their own reports or drill down in dashboards without having to keep running to R&D for every question. “What we wanted from a tool,” summarized Levenson, “was the wow factor. We wanted people to look at it and say wow, where has this been all my life?”
About The Customer
AvaTrade is an innovative online trading company headquartered in Dublin, Ireland. The company was founded in 2006 by financial professionals and experts in web commerce with the goal of perfecting the online experience for retail traders. The company has tens of thousands of registered customers in over 120 countries around the world, and executes more than two million trades per month. AvaTrade provides everyone from experienced traders to novices with an adaptable trading platform and trading services around the world.
The Solution
To really understand the viability of Sisense as the tool for AvaTrade, a POC was required. A small internal team created a set of demo dashboards that relied upon information from two of the company’s current disconnected applications. “I was checking to see, am I writing script, or am I using the tool out of the box? Did I have to go to a programmer to help me out? How much do I have to go to IT or R&D to do anything? We were also measuring how much time it was taking to create each dashboard. We had connected two sets of data to see how Sisense would work with all our different sources,” explained Levenson. “Other tools were dropped right away because they need you to already have a single database underneath. Others were also thrown out due to the prohibitive cost structure, which required 12 or more months for a ROI realization that would justify our investment.” AvaTrade was able to promote quick adoption throughout the organization and achieve some amazing results: • Standard set of dashboards • Even better customer retention because the company has a better view of what is happening with clients and call them to help faster, adding to a better customer experience • Rendering data from multiple sources has brought up data anomalies, allowing for proper care on a timely basis • Sisense is saving significant time per day for each report “Any mismatched or disparate data is bubbling up and allowing for appropriate actions to be carried out, which has been an added value from the use of Sisense, aiding in the adoption process of the solution,” stated Levenson.
Operational Impact
Quantitative Benefit
Related Case Studies.
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.”
