Uncovering hidden fault lines in artificial intelligence strategy: A data-driven risk framework for digital banking

Artificial intelligence (AI) is rapidly transforming digital banking, promising efficiency, personalisation and competitive advantage. Nevertheless, most AI strategy failures in financial institutions are rooted not in algorithmic shortcomings but in weaknesses at the intersection of data governance, data quality and AI lifecycle management. This paper introduces a diagnostic framework designed for senior banking executives to uncover hidden fault lines in AI strategies by examining their underlying data practices. Drawing from regulatory guidance, industry case studies and scholarly research, the framework offers actionable methods to detect, trace and mitigate risks across the AI value chain. By placing data governance at the center of AI risk management, digital banks can ensure compliance, protect customer trust, maximise return on AI investment and safeguard operational resilience. This article is also included in The Business & Management Collection which can be accessed at https://hstalks .com/business/.