Design of a Modular Architecture Based on AI and Blockchain for Personalized Microcredits Using Open Finance

This paper presents the design and validation of a modular architecture for smart microcredits, aimed at expanding credit access for populations excluded from the traditional financial system. The solution integrates three key technological components: data acquisition through Open Finance, automated risk assessment using Artificial Intelligence (AI) models, and the execution of smart contracts on blockchain. A functional prototype was developed to process applications manually submitted by users without prior financial history, utilizing a LightGBM model trained on real, anonymized data. The model was integrated into the system workflow to generate automatic credit conditions and register decisions on the blockchain without direct human intervention. During the validation phase, the model achieved an Area Under the Curve (AUC) of 0.94, supporting its discriminative power within the automated flow. The overall technical validation demonstrates the feasibility of offering personalized, traceable, and secure credit services through open and decentralized technologies. The use of alternative unstructured data, as well as the expansion into production environments, is proposed as a future line of development. In our system, Open Finance provides consented financial data off-chain; the ML model estimates default probability and outputs an eligibility decision; a rule engine maps the score to personalized loan terms; and blockchain smart contracts only record loan terms and execution events on-chain (no personal data). This separation ensures auditability (on-chain) and privacy (off-chain).