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Digitizing the risk function

Harmony Internal - McKinsey

'Slowly' doesn’t mean 'never' ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌   ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ 

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McKinsey Classics | November 2022
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Digitizing the risk function

Our readers well know that digital technologies are blazing a trail through all corporate functions. Risk is no exception, but the extreme sensitivity required to manage it has some important implications: tolerance for bugs and errors is necessarily low, and the cost of errors may be unacceptably high. Progress in digitizing the risk function and its processes has therefore proceeded slowly. But “slowly” doesn’t mean “never.”

The most fundamental challenge is managing a culture of innovation in a way that’s appropriate for risk. Robust controls must constrain the test-and-learn pilot projects common in digital transformations. Minimum viable products refined over successive iterations generally aren’t appropriate. And organizations must build digital risk management processes incrementally: specific capabilities are usually developed and released one by one. For all these reasons, it takes longer to digitize the risk function than, say, customer service. Yet at a time of rising costs, it really must be digitized.

To learn more, read our classic 2017 article “Digital risk: Transforming risk management for the 2020s,” which focuses on the banking industry but has many lessons for every kind of business.

—Roger Draper, Editor, New York
Learn how to digitize risk
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Related Reading

Jim Boehm, Lama Sabbagh, Jan Shelly Brown, and Karim Thomas, “Lessons from banking to improve risk and compliance and speed up digital transformations” 
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Andreas Hefter, Olivia Loadwick, Thomas Poppensieker, and Anke Raufuss, “Risk transformations: The heart, the art, and the science” 
Computer abstract image

Ignacio Crespo, Pankaj Kumar, Peter Noteboom, and Marc Taymans, “The evolution of model risk management” 

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