The bank is using software from startup CognitiveScale to monitor its AI algorithms for bias, data drift, and other business risks, says CIO Gavin Munroe.
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Businesses in highly regulated industries often stumble over the so-called “black box” problem when they try to deploy artificial intelligence technology, which often automates tasks and generate outputs that cannot be readily explained.
Banks, in particular, are struggling to vet the transparency and interpretability of machine learning (ML) models and AI software that inform everything from fraud detection to asset traceability and provenance. HSBC is no different, but the British bank is using software that helps it instill trust in its algorithms, which are subject to biases, data drift and other issues that pose risks to businesses.
The bank’s efforts are critical in increasing trust at a time when more consumers are adopting digital services during the coronavirus pandemic, says HSBC CIO Gavin Munroe.
“There is a balance between showing them what’s in the model and what’s in the AI, to explain what we’re using, that it has the right quality, lineage and most accurate data we need,” Munroe tells CIO.com. “We don’t think we can work in an environment without trust.”
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