Publication Details
Abstract
General Background: Open banking can make post-disbursement credit monitoring more timely, but repeated data access also raises questions of lawful purpose, optional consent, data reliability, explainability, and adverse decisions based on missing digital traces. Specific Background: Uzbekistan’s loan portfolio rose from UZS 277.0 trillion at year-end 2020 to UZS 604.0 trillion at year-end 2025. Remote-banking customer registrations also expanded sharply; these are bank-level registrations rather than a count of unique citizens and are reported at dates that may differ from year-end banking stocks. Knowledge Gap: Existing digital creditworthiness models focus mainly on origination, while monitoring frameworks rarely separate genuine financial deterioration from consent withdrawal, stale data, or source failure. Aims: This study develops a consent-gated early-warning framework for open banking credit monitoring in Uzbekistan. Methods: Documentary analysis, banking-system trend analysis, process mapping, indicator design, and a synthetic borrower case were combined. An optional-consent gate and a data-reliability gate precede a four-domain Financial Trajectory Score covering recurring inflows, debt-service burden, payment discipline, and cash-flow volatility. Compliance and identity events are treated through a separate categorical flag. Results: The synthetic case produces a baseline score of 53.3 and remains in the review band under alternative weights (50.0–59.8). A stricter coverage or freshness requirement can fail the data gate and route the account to manual review without treating missing evidence as higher risk. Novelty: The framework combines a non-adverse-use rule for optional consent withdrawal with reproducible component transformations, a separate compliance flag, boundary safeguards, and a validation protocol. Implications: Banks can integrate the framework with open banking, Chief Data Officer functions, model-risk validation, restructuring workflows, and RegTech reporting.