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Federated Artificial Intelligence for Unified Credit Assessment

arXiv 2105.09484 ↗First posted 20 May 2021cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 30 references that are in the map. First posted on arXiv 20 May 2021.

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References · 4

  1. 2018An Interpretable Model with Globally Consistent Explanations for Credit Riskcited by 33
  2. 2020The Value of Big Data for Credit Scoring: Enhancing Financial Inclusion using Mobile Phone Data and Social Network Analyticscited by 21
  3. 2019dpUGC: Learn Differentially Private Representation for User Generated Contentscited by 5
  4. 2019Generic Multilayer Network Data Analysis with the Fusion of Content and Structurecited by 1

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