Multimedia Knowledge and Social Media Analytics Laboratory

PROFIT

The PROFIT (Promoting Financial Awareness and Stability) project aims to develop a platform towards promoting the financial awareness and improving the financial capability of citizens and market participants. The platform will be built on Open Source components and will provide the following functionalities:

  • specialized financial education toolkits available to the wider public
  • advanced crowd-sourcing tools to process financial data, extract & present collective knowledge
  • advanced forecasting models exploiting the market sentiment to identify market trends & threats
  • novel personalized recommendation systems to support financial decisions according to the user’s profile

The PROFIT platform will be designed and pilot-tested via the collaboration with the members and partners of the European Federation of Ethical and Alternative Banks (FEBEA), an institution committed to the responsible banking and finance agenda.

Role of MKLab:

MKLab is responsible for the design and development of incentive mechanisms, based upon a reputation scheme which will promote the most reputed/contributive users of the platform by providing them certain privileges like social status gained in the platform, access to more data and advanced services, and certain other benefits provided by the FEBEA member organisations (i.e., discounts in certain products, better financing terms in bank services etc). MKLab will also lead the efforts towards the design of a novel personalized recommender system that will provide recommendations to each user targeting her/his specific interests and financial literacy level and also point to other users that share similar interests and views. In addition, MKLab will develop data scrapers for specific financial websites and collectors for social media data and will be involved in the development of a framework for semi-automatic alignment of ontologies by combining different matching algorithms using late fusion and supervised learning.

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