Sequence-Aware Behavioral Credit Engine (SABRE): Deep Learning for Continuous Affordability and Early Distress Detection in Digital Lending

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Authors: Praveen Kumar Sabbineni
Cited by: 0

Abstract

Traditional credit risk assessment methodologies suffer from temporal limitations that prevent effectivedetection of emerging financial stress and behavioral changes in borrowers. The Sequence-AwareBehavioral Credit Engine (SABRE) framework addresses these constraints through deep learning sequence models that process time-ordered financial event streams to generate continuous

Fields of Study & Subjects

Financial Distress and Bankruptcy Prediction Credit Risk and Financial Regulations Imbalanced Data Classification Techniques

Publication details

Journal / source
Journal of Computational Analysis and Applications
Publication date
8 January 2026