Standard Chartered is taking a careful approach to using AI in banking. The bank faces tough questions before building any AI system. Can the data be used? Where can it be stored? Who is responsible once the AI is live? These privacy concerns are now central to how the bank develops and deploys AI technology. For a global bank operating across many countries, these decisions are especially complex. Privacy laws differ from one market to another, and the same AI system might have to meet different rules depending on where it is used. This has led the bank’s privacy teams to play a more active role in guiding AI projects from start to finish.

Privacy Rules Shape AI Deployment

At Standard Chartered, privacy considerations influence every stage of AI development. Privacy teams help decide what kind of data can be used, how transparent the AI systems should be, and how to keep track of the systems once they are operational. David Hardoon, the bank’s Global Head of AI Enablement, explains that data privacy functions now often serve as the starting point for regulatory compliance in AI projects. In practice, this means the bank must carefully select data sources, ensuring they meet privacy standards and don’t compromise customer trust.

When moving from small pilot tests to full-scale deployment, the challenges grow. During pilots, data sources are limited and well-understood. But in real-world applications, AI systems pull data from multiple platforms, each with its own quirks. Ensuring the quality and consistency of this data becomes more difficult as the amount of data increases. Hardoon notes that schema differences and data quality issues can cause problems when AI systems shift from testing to live environments. Addressing these issues is key to maintaining reliable and fair AI operations.

Regulations and Geography Influence AI Use

The location of AI deployment is another critical factor. Different regions have varying data protection laws that impact where and how AI systems can operate. Some countries impose strict rules on data storage, requiring data to stay within borders or limiting access to certain information. These laws influence whether AI systems need to be deployed locally or if data can be shared across borders with proper controls. Hardoon emphasizes that data sovereignty is a major consideration for the bank’s operations in diverse markets.

In countries with data localisation rules, the bank often has to set up local data centers or design systems that keep sensitive information within specific regions. This can add complexity and cost but is necessary to comply with legal requirements. When rules allow, the bank uses shared platforms with robust controls to manage data securely across different jurisdictions. These choices ensure that the bank stays compliant while still being able to deliver innovative AI solutions to its clients.

Overall, Standard Chartered’s approach shows that balancing innovation with privacy laws requires careful planning and ongoing oversight. The bank’s strategy aims to build trustworthy AI systems that respect customer privacy and legal boundaries. By involving privacy teams early and considering regional regulations closely, the bank strives to deploy AI responsibly at scale. This approach helps ensure that the benefits of AI can be realized without compromising trust or compliance.

Inspired by

• https://www.artificialintelligence-news.com/news/how-standard-chartered-runs-ai-under-privacy-rules/

Sources

• unsplash.com
• ai-expo.net
• techexevent.com
• techforge.pub
• techforge.pub