Clearwater Analytics: Asset managers worried about the quality of AI data
Asset managers are broadly confident in the quality of the data being used to train artificial intelligence (AI) models being deployed in their organizations, new research from Clearwater Analytics shows.
The study, which covered a broad spectrum of fund managers including insurance asset managers, hedge funds, private markets specialists, and general asset managers, reveals that nearly three quarters of asset managers (70%) surveyed believe their data is good or excellent (32% said it is excellent). That confidence isn't evenly spread. It depends heavily on which part of 'data quality' is being asked about.
As far as accuracy and reliability is concerned, only just over half (56%) said their data was good or excellent, the lowest score of any dimension tested. Yet on the matter of completeness and coverage, almost eight out of 10 (79%) said it was good or excellent, (48% said it is excellent). The gap between the two, roughly 23 percentage points, is the clearest sign that firms have more data than they fully trust.
The majority of fund managers surveyed (69%) said that their data sets are complete, while 12% of those said they were very complete. However, more than a fifth (21%) said they were incomplete.
Despite the overall confidence in the quality of the data, there remains quite high levels of concern about the potential use of poor quality data in an organization's AI operations, and those concerns escalate quickly once the conversation turns to consequences. Almost three quarters (72%) said the risk of this made them concerned or very concerned (36% in each group).
Four out of five (80%) were concerned – 20% of them very concerned – that the use of poor quality data could erode trust in the effectiveness of their AI tools, rather than placing the blame on the quality of the data that has been used to develop it. That's the risk compounding on itself: a data problem gets misread as a technology problem, and the tool takes the blame the data deserves.