One of the attractive things about machine learning, in theory, is that it approaches tasks in a more human way – checking new information against past experience and getting smarter as it goes – while also having a superhuman capacity to process that data. It can be too efficient, though.
When applied in the world of risk monitoring, the always-on, always-willing, never-tired machines can generate more alerts than their human colleagues are able to investigate. Some of the winning vendors in this year’s Risk Technology Awards (RTAs) have been trying to solve this problem, creating something of a cognitive revolution, where humans and machines work side by side to tackle some of the biggest challenges to the safe and stable operations of financial markets and services.
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