SocialCredit+

TL;DR

SocialCredit+ is an AI-driven credit scoring system that integrates social media data, ethical compliance checks, and explainable AI to provide a comprehensive and transparent credit evaluation method.

Contribution

It introduces a novel multimodal, socially-aware credit scoring framework with ethical compliance and explainability features, enhancing traditional methods.

Findings

Effective integration of social media data improves credit assessment accuracy.

Sharia-compliance layer successfully flags non-halal indicators.

Retrieval-augmented generation provides clear explanations for decisions.

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.