The convergence of Open Banking and Artificial Intelligence (AI) is re-inventing the global financial services domain, offering both opportunities and challenges. Open Banking has already disrupted conventional financial ecosystems by enabling secure, and standardized data sharing between banks and third-party providers via APIs. This shift has enabled new options for collaboration, better consumer experience, and higher financial inclusion. At the same time, AI—powered by large language models (LLMs) —has demonstrated massive potential by automating processes, personalizing services, and supporting regulatory compliance. Together, these innovations will be building a customer-centric financial ecosystem. LLMs require access to vast and often sensitive datasets for optimal performance, yet the regulatory environment governing Open Banking emphasizes strict control, and limited data access. This underscores a challenge: how to realize the full benefits of AI without compromising data security and regulatory issues. This paper addresses these gaps by introducing a structured framework by placing AI into Open Banking without allowing sensitive financial data to leave enterprise boundaries. The approach emphasizes data governance, the deployment of metadata-driven data catalogs, the data profiling and documentation, and the integration of AI models through API interactions. Ultimately, this paper illustrates a balanced model for complementing Open Banking with AI: one that leverages capabilities of AI while safeguarding data integrity and data trust.
Vishal Sharma (Wed,) studied this question.