The system establishes a privacy-preserving credit evaluation framework that eliminates exposure of user financial data during creditworthiness verification. Conventional credit scoring requires complete visibility into a borrower’s income records, liabilities, repayment patterns, and transaction histories, creating structural risks related to data theft, unauthorized sharing, profiling, and large-scale breaches.

The proposed architecture replaces disclosure-based assessment with Non-Interactive Zero-Knowledge (NIZK) proofs. Users locally compute cryptographic attestations that assert compliance with predetermined financial thresholds—such as debt-to-income ratio, repayment consistency, or minimum balance stability—without revealing source data.

Verifiers check the proof deterministically, without bidirectional communication or access to underlying financial artifacts. The model reduces attack surface, removes centralized exposure of sensitive records, and aligns credit scoring processes with modern expectations of confidentiality, verifiability, and regulatory trust. It offers an adaptable foundation for digital lending, embedded finance, decentralized platforms, and cross-institution credit portability.

Keywords: Privacy-Preserving Credit Evaluation, Non-Interactive Zero-Knowledge Proofs (NIZK), Cryptographic Verification, Financial Data Privacy, Secure Credit Scoring, Digital Lending.