下载PDF
BioCatch Effortlessly Scales Its Fraud Detection Platform with Redis Enterprise
技术
- 平台即服务 (PaaS) - 数据管理平台
- 基础设施即服务 (IaaS) - 公共云
- 分析与建模 - 机器学习
适用行业
- 金融与保险
- Software
适用功能
- 商业运营
- 质量保证
用例
- 欺诈识别
- 实时定位系统 (RTLS)
服务
- 云规划/设计/实施服务
- 系统集成
- 数据科学服务
挑战
Before Redis Enterprise, the BioCatch operations teams were struggling to keep pace with the company’s rapid growth. As the platform reached and then surpassed five billion transactions per month, the issue of scaling consumed everyone’s attention, leaving no resources to focus on new product features. “Version one of our solution was built to go to market very fast,” says Dekel Shavit, BioCatch VP of Operations & CISO. “It wasn’t designed with 70 million users in mind and so efficient architecture and data models weren’t initially top of mind.” But it was clear that a redesigned technology stack needed to be top of mind for the solution’s next incarnation. Of particular priority was decoupling compute and state to make the system more elastic. Session state was being kept across many virtual machines; if a machine fell down, all of its sessions were lost. This configuration was not only proving to be a liability within the context of critical real-time fraud detection, but also very difficult—and expensive—to scale.
关于客户
BioCatch is a world leader in behavioral biometrics. Its innovative fraud detection technologies are redefining digital identity through unique behavior characteristics such as how a user holds their phone, types, swipes across the screen, or scrolls down the page. As more and more top tier financial institutions and enterprises worldwide adopted the company’s groundbreaking biometrics tracking solutions, BioCatch turned to Redis Enterprise VPC from Redis Labs to overcome the significant database scaling issues it faced as a result of extreme rapid growth. Today, BioCatch relies on Redis Enterprise to service more than 70 million platform end users of its platform with zero downtime, zero operational hassle, and near-zero latency.
解决方案
As BioCatch undertook the much-needed redesign of its technology stack, Redis Enterprise, known for its ease of implementation and exceptionally high performance, became the centerpiece—and remains so today. “Since its implementation more than a year and a half ago, Redis Enterprise has kept latency to an average of less than .96 milliseconds, even at peaks of 40,000 operations per second,” says Shavit. “And it has done so without spikes, a key driver for us, and, incredibly, with zero downtime.” BioCatch uses Redis Enterprise VPC, a fully managed database-as-a-service from Redis Labs. Redis Enterprise VPC is installed inside BioCatch’s virtual private cloud within the Microsoft Azure public cloud. It serves an average of three terabytes of data and 200 million keys at any given moment to the many microservices that power the company’s applications and is currently the only stateful component of BioCatch’s redesigned stack. The biometrics company runs a few other databases alongside Redis Enterprise including Microsoft SQL Server, Apache Cassandra, and Apache Impala, but has been migrating more and more data into Redis Enterprise. “We looked to Redis Enterprise for caching initially, but quickly discovered that it is really good as a database—not just a simple database, but also a system configuration database,” says Shavit. “Most of our data now resides in Redis Enterprise because it’s always available, and it’s always highly responsive no matter how you query it.”
运营影响
数量效益
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.”
