With the rapid adoption of Internet technologies, digital footprints have become ubiquitous and versatile to revolutionise the financial industry in digital transformation. This paper takes initiatives to investigate a new paradigm of the unified credit assessment with the use of federated artificial intelligence. We conceptualised digital human representation which consists of social, contextual, financial and technological dimensions to assess the commercial creditworthiness and social reputation of both banked and unbanked individuals. A federated artificial intelligence platform is proposed with a comprehensive set of system design for efficient and effective credit scoring. The study considerably contributes to the cumulative development of financial intelligence and social computing. It also provides a number of implications for academic bodies, practitioners, and developers of financial technologies.
CITATION STYLE
Hoang, M. D., Le, L., Nguyen, A. T., Le, T., & Nguyen, H. D. (2020). Federated artificial intelligence for unified credit assessment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12195 LNCS, pp. 44–56). Springer. https://doi.org/10.1007/978-3-030-49576-3_4
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