Keywords: Shiny modules, HTMLWidgets, HTMLTemplates, openCPU, NoSQL, Docker
Webpages:
https://www.friss.eu/en/ FRISS is a Dutch, fast growing company with a 100% focus on fraud, risk and compliance for non-life insurance companies and is the European market leader with over 100+ implementations in more than 15 countries worldwide. The FRISS platform offers insurers fully automated access to a vast set of external data sources, which together facilitate many different types of screenings, based on knowledge rules, statistical models, clustering, text mining, image recognition and other machine learning techniques. The information produced by the FRISS platform is bundled into a risk score that provides a quantified risk assessment on a person or case, that enables insurers to make better and faster decisions.
At FRISS, all analytical applications and services are based on
R. Interactive applications are based on
Shiny, a popular web application platform for
R designed by RSTUDIO, while
openCPU, an interoperable HTTP API for
R, is used to deploy advanced scoring engines at scale, that can be deeply integrated into other services.
In this talk, we show various architectures on how to create high performance, large scale
Shiny apps and scoring engines, with a clean code base.
Shiny apps are based around the
module pattern,
HTMLWidgets and
HTMLTemplates. Shiny modules allow a developer to compose a complex app via a set of easy to understand modules, each with separate UI and server logic. In these architectures, each module has a set of reactive inputs and outputs and focuses on a single, dedicated task. Subsequently, the modules are combined in a main app that can perform a multitude of complex tasks, yet is still easy to understand and to reason about. In addition, we show how
HTMLWidgets allow you to bring the best of
JavaScript, the language of the web, into
R and show how
HTMLTemplates can be used to create
R based web applications with a fresh, modern and distinct look.
Finally, in this talk, we show various real-life examples of complex, large scale
Shiny applications developed at FRISS. These applications are actively used by insurers worldwide for reporting, dashboarding, anomaly detection, interactive network exploration and fraud detection and allow insurers to combat fraud, risk and compliance. In addition, we show how the aforementioned techniques can be combined with modern NoSQL databases like
ElasticSearch,
MongoDB and
Neo4j, to create high performance apps and how
Docker can be used for a smooth deployment process in on-premises scenarios, that is both fast and secure.
