Impressive Early Results of AI Integration in Banking

Artificial Intelligence isn’t going to replace company CEOs any time soon. But what AI is already doing is pretty impressive: uncovering unique connections and relationships that can help businesses become more efficient at what they do, developing insight into new products and solutions, and creating a more frictionless trading landscape.

Adopting the advantages of AI can also present challenges, from providing customers with “explainability” for AI decision-making to ensuring that users understand both its disruptive possibilities and its limitations. That’s why developing AI to leverage Big Data has been a major focus for HSBC Global Banking and Markets (GBM).

Matthew Sattler, director of business development & data science, data analytics at HSBC Bank plc (“HSBC”), GBM in London, has been working on a far-reaching plan to collect, organize and synchronize the bank’s data assets across all of its global markets, then leverage that data to create value for HSBC and its clients.

“Generative AI, where we picture machines programming themselves without a human intervention, doesn’t exist in practicality,” says Sattler. “But we are pushing the envelope of using machine learning, a subset of AI where we can derive tremendous value for our clients. For example, we can deploy deep learning models where a machine is weighing the importance of hundreds of features in large and complex data sets to build new insights through hidden patterns that are perfect for a machine to mine. With enough data, it can then make decisions similar to a person and becomes more accurate over time, using more data. The result means data becomes a strategic business asset and helps put the client first through more tailored products and services and allowing the data to speak to us in new ways.”

This story was created by Content Works, Postmedia’s commercial content division, on behalf of HSBC Bank Canada.