Artificial intelligence (AI) is transforming key components of asset managers’ operational processes, and nowhere is that more evident than in their risk management practices, new research from Clearwater Analytics shows.
For an industry where speed and precision of risk identification often determines whether exposure is managed or missed, the shift AI is driving matters well beyond efficiency, the firm says.
Almost all fund managers (95 per cent) surveyed across a broad spectrum of fund managers including insurance asset managers, hedge funds, private markets specialists, and general asset managers, have seen improvements in the level of real-time insights being generated since adopting AI into their risk management systems, while 17 per cent said those changes had been dramatic.
Managers using AI in risk management in this function want to develop a more proactive model, the firm reports, one built to predict and prevent risk in real time. Almost a third (32 per cent) said their process had become much more proactive, while a further 60 per cent said they had seen a slight increase in proactivity. Only 8 per cent had seen no change from using AI.
Predictive analytics is where the shift becomes most concrete. AI offers the ability for managers to develop their risk management systems to deliver greater predictive analytics. Supported by machine-learning models that can analyse vast data sets to identify patterns and predict future trends with greater accuracy than traditional methods, this will be highly beneficial for forecasting risk
Since they began to use AI, the vast majority of fund managers (87 per cent) said their ability to use predictive analytics as part of their risk management had improved, with a fifth (20 per cent) claiming the improvement was dramatic. Some (12 per cent) had seen no change, and only 1 per cent said it had worsened.
The gains extend into reporting as well. In addition to offering better predictions, 88 per cent of managers said the ability to process vast amounts of data had increased the turnaround of regulatory and accounting reports. Almost half (42 per cent) said they had increased the speed of report production by between 10 per cent and 24 per cent, while a further 30 per cent said it had increased between 25 per cent and 49 per cent. Almost a tenth (9 per cent) had seen the speed they could generate reports increase by between 50 per cent and 74 per cent.
Manual reconciliation tells a similar story. More than half of managers (55 per cent) have seen a reduction in the need for manual reconciliations. A fifth (20 per cent) have seen these reduce by up to10 per cent, 19 per cent have seen them reduce between 10 per cent and 24 per cent, and 15 per cent have been rewarded with reductions of between 25 per cent and 49 per cent.
Only 2 per cent of managers said they had not yet used AI within this function. Almost a quarter (24 per cent) said using AI had actually slowed their process down, a reminder that these gains depend on how well the technology is implemented, not simply on whether it’s adopted.
Souvik Das, CTO at Clearwater Analytics, says: “None of this works without the data underneath it. Real-time insight, sharper prediction, and faster reporting depend on a foundation of clean, reconciled data feeding the system. The number worth paying attention to is the 24 per cent who saw their reconciliation process slow down. It’s a sign that the technology only delivers on this shift when the data and systems underneath it are ready to support it. The firms getting this right are the ones who can move the moment they see something, because they already trust what they’re seeing.”
