What we do

Personalise

The ��¼� Fintech AI Innovation Consortium (FAIC) drives cutting-edge research and collaboration at the intersection of artificial intelligence and financial technology. We publish impactful studies, host industry and academic events, and share insights through videos that explore responsible, explainable, and scalable AI solutions. By connecting researchers, regulators, and industry leaders, FAIC fosters innovation that shapes the future of fintech.

Publications

Samarasekara, Iromie; Bandara, Madhushi; Rabhi, Fethi; Benatallah, Boualem; and Meymandpour, Rouzbeh, "LLM Driven Approach for Capability Modelling with Context-enriched Prompt Engineering" (2024). ACIS 2024 Proceedings. 38.

Ng SL; Rezaei HB; Rabhi F, 2024, SLEGO: A Collaborative Data Analytics System with LLM Recommender for Diverse Users,

Yu M; Rabhi FA; Bandara M, 2024, 'Ontology-Driven Architecture for Managing Environmental, Social, and Governance Metrics', Electronics (Switzerland), 13,
Rabhi F; Yu M; Ng A; Lim E; Tan F; Hsiao A, 2023, 'Building an ESG Decision-Making System Challenges and Research Directions', in Advances in Complex Decision Making: Using Machine Learning and Tools for Service-Oriented Computing, pp. 38 - 51,

Ng SL; Rabhi F, 2023, 'A Data Analytics Architecture for the Exploratory Analysis of High-Frequency Market Data', in Enterprise Applications, Markets and Services in the Finance Industry, Springer Nature, pp. 1 - 16,

Manchanda C; Hussain W; Rabhi L; Rabhi F, 2023, 'Towards an API Marketplace for an e-Invoicing Ecosystem', in Enterprise Applications, Markets and Services in the Finance Industry, Springer Nature, pp. 82 - 96,

Bandara M; Rabhi FA; Bano M, 2023, 'A knowledge-driven approach for designing data analytics platforms', Requirements Engineering, 28, pp. 195 - 212,
Chen W; Al-Qudah I; Rabhi F, 2022, 'A Framework for Facilitating Reproducible News Sentiment Impact Analysis', in ACM International Conference Proceeding Series, pp. 125 - 131,
Shi S; Mangioni V; Ge J; Herath S; Ouysse R; Rabhi F, 2021, House Price Forecasting from Investment Perspectives

Ng SL; Rabhi FA; Whyte G; Zeng A, 2021, 'Introducing the BrewAI AutoML Tool', in Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Sydney, Australia, pp. 198 - 207, presented at 7th EAI International Conference, IoTaaS 2021, Sydney, Australia, 13 December 2021 - 14 December 2021,