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FedIncome: Federated Learning for Income Estimation in Digital Lending Under Data Sovereignty Constraints

arXiv · AI, language, vision and robotics · article · Sep 23, 2026 · UTC

Verified income is often unavailable in digital loan applications, forcing lenders to rely on reported income and potentially leading to over-lending, overly conservative offers, or rejection of creditworthy applicants. Cross-institutional data-sharing constraints make this problem especially difficult for smaller lenders with limited training data. We introduce FedIncome, a federated learning framework for income estimation that enables institutions to train a shared model without pooling raw borrower records. Using more than one million LendingClub loans partitioned into $50$ state-level cli

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