FAME’s main goal is to develop, integrate, validate and offer as a publicly accessible service Europe’s first federated, decentralized, trusted and energy efficient data assets marketplace for EmFi.
Decentralized, programmable, data assets trading and pricing leveraging blockchain tokenization Integration of trusted and EE analytics based on innovative technologies such as Quantitative Explainable AI (XAI), Situation Aware Exploitability (SAX), incremental energy efficient analytics, and power-efficient edge analytics.
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Pilot 1 – FaMLy – A powerful financial recommendation engine for families
During the last two years, the BNPL model illustrates how retailers can use data assets to
offer value-added, finance related services to their customers. These services can become very powerful as the amount of
collected data from diverse sources grows in an exponential pace. In several cases, data assets are produced by entire data
ecosystems operated by the retailers. In these ecosystems, retailers are able to manage, price, and trade data assets, which
EmFi providers can use to provide value-added services for customers.
Pilot 2 – Embedding Finance Services in a Personalized Citizen Wallet
Since 2019 the City of Athens (DAEM) and its technology partner NOVO have re-branded
the popular smart parking app of the city (myAthensPass). The new app enables drivers to buy parking time quickly, easily
and conveniently. It also enables motorists to find their exact location, to select their desired parking duration, to extend their
parking time remotely, to access information about how much they need to pay, and to parking time in advance. Relevant
payment transactions can be carried out via NOVO’s app, which serves as a mini citizen wallet. DAEM is also collecting
large amounts of data about citizens’ parking activity, including their payments. DAEM and NOVO are interested in using
the collected data for offering more citizen-centred financial services and for extending the paradigm in additional services
(e.g., transport, medical needs).
Pilot 3 – Personalized Collaborative Intelligence for Enhancing EmFi Services
In the era of Open Banking, payment providers have significant opportunities to gain valueadded information about their services and their customers based on the aggregation, consolidation and sharing of data across
institutions and organizations. The consolidation of analytics across financial organizations enables them to gain timely and
accurate insights for processes like onboarding, services personalization, and credit risk scoring.
Pilot 4 – The EU Funds Application Process Made Easy
The advent of Next Generation EU (NGEU) funds has resulted in an increase in public grants
and therefore a unique opportunity for self-employed, SMEs and companies to finance the twin (digital, green) transformation
their businesses. Nevertheless, identifying and processing these grants is no mean feat and, on many occasions, put the brakes on investment.
Pilot 5 – ESG Scorecard Ranking & Sustainable Portfolio Optimisation
Despite the rising interest in ESG, there is still a lack of data and analytical tools for assessing,
benchmarking, and comparing ESG portfolios. This is a setback to constructing “alpha” portfolios that can lead to excess
returns above the average benchmarks. Asset managers need accurate and transparent tools, which could help them shape
effective investment strategies and protect their capital during crises. In this direction, they can leverage ESG data from
marketplaces, along with tools for accurate risk analytics and benchmarking.
Pilot 6 – Embedding Climatic Predictions in Property Insurance Products
Nowadays, natural disasters and climate change hazards remain mostly uninsured, which is
a major challenge for the insurance industry [McKinsey20]. One of the insurance areas that will be significantly affected by
climate change is property pricing. Despite the relatively low likelihood of hazardous events, devastating events can cause
significant economic damages in real estate properties. The latter are constantly increasing in frequency due to the on-going
change in climatic patterns and the absence of strong mitigation measures. Hence, there is a need for novel data-driven
insurance services that incorporate climatic parameters in the estimation of insured liabilities, while facilitating climate aware
investment decisions.
Pilot 7 – Assessing the Quality and Monetary Value of Data Assets
For nearly a decade MOH is heavily investing in the digitization of its production based on
the introduction of sensors and cyber-physical systems in its oil refineries and on the implementation of novel use cases. The
company manages a great amount of raw data from various sensors (e.g., pressure, thermometers, vibration, axial
displacement), which is analysed hourly to identify abnormalities, to predict compressors’ behaviour for the next 24 hours
and to identify potential problems ahead of time. The company’s experience from the deployments has unveiled the
importance of the quality of the data assets, which is critical for implementing effective ML systems that can accurately
predict assets’ behaviours. Leveraging the FAME marketplace, MOH is interesting in extracting valuable insights on the
quality and potential monetary value of its data assets, to drive the exploitation and use of these assets in processes like cyberinsurance contracts.
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