Unlocking value with deep learning: The future of financial services

Arora, Aditya (2025) Unlocking value with deep learning: The future of financial services. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 677-690. ISSN 2582-8266

The financial services industry is experiencing a revolutionary transformation through deep learning technologies. As data volumes expand exponentially across market transactions, customer interactions, and regulatory filings, traditional analytical methods have reached their limitations. Deep learning, with its sophisticated neural network architectures, offers unprecedented capabilities to extract value from complex, multi-dimensional financial datasets. This article explores how various neural network architectures—including CNNs, RNNs, GANs, and Transformers—are being applied across critical financial domains. From enhancing credit risk assessment with alternative data to detecting fraud through real-time transaction monitoring, deep learning is fundamentally changing operational paradigms. The article examines technical foundations, training methodologies, current applications, and emerging trends. Despite challenges in interpretability, privacy, and model robustness, innovative solutions are emerging. With integration opportunities in blockchain, quantum computing, and AutoML, deep learning is positioned to become the defining technology shaping the future of financial services.