Beyond traditional metrics: How AI is redefining lending acquisitions valuations modeling

Arora, Aditya (2025) Beyond traditional metrics: How AI is redefining lending acquisitions valuations modeling. World Journal of Advanced Research and Reviews, 26 (1). pp. 1273-1293. ISSN 2581-9615

Abstract

Artificial intelligence is fundamentally transforming lending practices, shifting from traditional linear models to sophisticated deep learning architectures. This article explores how AI enhances customer acquisition and valuation through neural networks, synthetic persona modeling, alternative data integration, and hyper-personalization strategies. We examine how deep learning enables lending institutions to capture complex financial behavior patterns, process diverse data sources, and deliver personalized offerings at scale. The integration of reinforcement learning and real-time decisioning systems creates dynamic customer journeys, while advanced recommendation algorithms optimize product offerings. Throughout the examination of these technological capabilities, the article address critical ethical considerations including fairness, transparency, and data privacy, demonstrating how ethical AI implementation represents not merely a compliance requirement but a strategic competitive advantage that benefits lenders, borrowers, and the broader financial ecosystem.

Item Type: Article
Official URL: https://doi.org/10.30574/wjarr.2025.26.1.1171
Uncontrolled Keywords: Artificial Intelligence; Deep Learning; Alternative Data; Hyper-Personalization; Ethical Finance
Date Deposited: 22 Jul 2025 23:56
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/1781