SocialCredit+

Thabassum Aslam, Anees Aslam
6/12/2025
cs.CYcs.AI

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Abstract

SocialCredit+ is AI powered credit scoring system that leverages publicly available social media data to augment traditional credit evaluation. It uses a conversational banking assistant to gather user consent and fetch public profiles. Multimodal feature extractors analyze posts, bios, images, and friend networks to generate a rich behavioral profile. A specialized Sharia-compliance layer flags any non-halal indicators and prohibited financial behavior based on Islamic ethics. The platform employs a retrieval-augmented generation module: an LLM accesses a domain specific knowledge base to generate clear, text-based explanations for each decision. We describe the end-to-end architecture and data flow, the models used, and system infrastructure. Synthetic scenarios illustrate how social signals translate into credit-score factors. This paper emphasizes conceptual novelty, compliance mechanisms, and practical impact, targeting AI researchers, fintech practitioners, ethical banking jurists, and investors.

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Cite this paper

@article{aslam2025socialcredit,
  title  = {SocialCredit+},
  author = {Thabassum Aslam and Anees Aslam},
  year   = {2025},
  eprint = {2506.12099},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.12099v1}
}

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