Applications for SMEs

Real-time Anti-Fraud Service

The SME E-COMPASS project designs and develops a “Real-Time Anti-Fraud Service for online European SMEs under a “Software-as-a-Service” framework. The platform is designed to work as the core engine of a merchant's fraud detection strategy and everyday work, demonstrating the following components:

 

  • Fully-functional web-based platform for order assessment, combining prior expert knowledge with automatic mechanisms for improving the cost-efficiency of the overall fraud detection process for SMEs;
  • Reputation database exposing transactional attributes related to “Card Not Present (CNP)” fraud, aiming to increase connectivity, information sharing and collaboration efforts between a wide network of online SME merchants and antifraud professionals;
  • Knowledge database of order scoring rules, empowered with a blend of supervised learning and intelligent models, for extracting patterns of fraudulent activity targeting online SMEs.

 2016 07 19 16 36 53 Applications

The S.a.a.S. has two major components: the inference engine and the knowledge base. The knowledge base consists of various fraud detection modules (expert rule engine, supervised learning algorithms and anomaly detectors), whereas the inference engine is the coordinator of the classification process.

2016 07 19 16 45 19 Applications Microsoft Word

Each newly arrived order flows through the inference engine and receives a risk score (RS) depending on its characteristics. This score reflects the confidence by which the order can be regarded as fraudulent. Once scoring is completed, the transaction is routed according to the three-level assessment protocol:

2016 07 19 16 46 03 Applications Microsoft Word

 

Online Data Mining Services

 

The fundamental idea behind the SME E-COMPASS Online Data mining Services is to support small and medium e‑shops in increasing their conversion rates from visitor to customer by improving the:

-       understanding of the customers and their expectations/motivation,

-       knowledge about competitors and their activities, especially concerning their prices and price trends,

-       examination of potentials for improvements by analysing some selected information of both, customers and competitors,

-       initiation of appropriate actions depending on the identification of certain patterns in the analysis results above-mentioned.

 

Online Data Mining Services create additional value for the e-shop owners by collecting, consolidating, analysing and visualising all data which is relevant to run their SME. To this end they provide data analytics and functionalities useful for the SMEs, such as:

  1. Comparison of the owners’ e-shop prices with those of its competitors;
  2. Clustering of visitors’ data for being able to correctly assess visitors interested in the e-shop products and to provide them with the right products, offers and information
  3. Definition of actions based on consolidated data of visitors, customers and competitors.

The SME E-COMPASS data mining service comprises five different modules for collecting, analysing and visualising relevant e-commerce data in order to support e-shop owners in daily business. The data is collected from the analytics service of the e-shops, from the own e-shop website and from the e-shop websites of the competitors. 

2016 07 19 16 46 27 Applications Microsoft Word

The functions of the modules are described in short in the following listing.

  1. E-COMPASS Cockpit (ECC): This module provides the graphical user interface, forms for the registration and the account and user management.
  2. Competitor Data Collector: Collects the product and price data from the e-shop websites of the user and its competitors and provides it to the Data Collector & Consolidator in a structured form (JSON).
  3. Data Collector & Consolidator: Collects the data from the Competitor Data Collector and the analytics services of the registered e-shops (users). It consolidates the collected data by the semantic concept of a domain specific ontology (domain: e-commerce).
  4. Data Analyser: The data analyser processes the data provided by the Data Collector & Consolidator by using novel clustering techniques in order to identify specific types of visitors, products and competitors.

Notification & Action Engine: The Notification & Action engine provides a set of pre-defined rules which can be individually adapted by the user through defining specific thresholds. It fires actions based on a condition defined by the user. Those actions are e.g. the sending of notifications or the real-time displaying of vouchers within the e-shop of the user. For checking the fulfilment of the conditions the module analyses the data provided by the data Collector & Consolidator as well as the data of the analytics services of the users’ e-shops.

2016 07 19 16 48 16 Applications Microsoft Word

 

 

 

Consortium

Halton Chamber of Commerce and Enterprise (HALTON) – UK
http://www.haltonchamber.co.uk

University of Malaga (UMA)-Spain
http://www.uma.es

ASOCIACIÓN DE EMPRESARIOS TEXTILES DE LA COMUNIDAD VALENCIANA
http://www.atevalinforma.com/

Centro de Investigación Cooperativa en Turismo (CIC)-Spain
http://www.tourgune.org

GAIA-ASOCIACIÓN DE INDUSTRIAS DE LAS TECNOLOGIAS ELECTRÓNICAS Y DE LA INFORMACIÓN DEL PAIS VASCO - SPAIN
http://www.gaia.es

Korinthos Chamber of Commerce (EPK)-Greece
http://www.korinthcc.gr

Fraunhofer IAO (FRA)-Germany
http://www.iao.fraunhofer.de

Fornaro Business Agency OE (FBA)-Greece
http://www.fornaro.gr

Estudio Cero Soluciones Informaticas S.L. (CERO)-Spain
http://www.e0web.com

EXUS
http://www.exus.co.uk

E-TRAVEL SA (ETR)-Greece
http://www.e-travel.gr

MeetNow (MTN)-Germany
http://www.meetnow.eu
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