AI causes cost shift from operations to tech and data

Nearly two-thirds (63%) of decision-makers employed by financial services firms said that AI would be likely to result in an increase in the cost of data within their organisation. This figure rises to 69% among firms in the UK; and 73% among asset owners more widely. That is according to new research commissioned by Alveo, surveying senior decision-makers working for financial services organisations in the UK, US and DACH region (Germany, Austria and Switzerland).

Commenting on the results, Martijn Groot, VP Marketing and Strategy, Alveo, said: “As the human element in data workflows diminishes due to the next wave of automation, there is a larger premium on good quality data. To achieve and maintain the high standard of data quality necessary for effective AI implementation, firms will need financial data management expertise in order to design, oversee, and refine the infrastructure and processes that feed into AI systems, and ensure all data is accurate, relevant, and timely.”

IT (hardware and licenses) spend in data management is likely to be on an upward curve also thanks to the advent of AI, according to more than four out of five of the sample (81%) who projected an increase because of the technology. That is potentially because, as financial institutions adopt more AI technologies, there is a growing need for data scientists, AI model developers and data management experts as well as the necessary data management technology infrastructure to ensure AI models work efficiently and the data feeding into those models is accurate.

Although the majority of firms expect operations headcount to decrease, the results are somewhat mixed with a sizable minority (40%) projecting an increase in operational headcount in data management. This figure is highest among firms in the DACH region (48%) and lowest among organisations in the UK (34%).

Groot added: “The onward march of AI will bring enhanced operational efficiencies and improved decision-making capabilities to organisations across the world. Goals stated for AI adoption differ somewhat regionally with the US scoring higher on “innovation in developing new services/products” and “enhancing operational efficiency” and Europe scoring higher on “improving data quality” and “improving customer service. Every role in financial services involves data management to some degree.” Firms will need to ensure staff have the right skillsets and that their data management processes are fully optimised to drive operational efficiencies and deliver enhanced productivity,” added Groot.

AI offers huge potential to drive productivity across data management, of course. More than half (53%) of the sample rank data quality management as the area of data management over which AI is likely to have the greatest impact here. Among asset owners, this capability was well down the list, however, with just 40% referencing it, compared to 57% of asset owners.

51% of the survey sample overall put data collection and aggregation in this category, while 48% reference data operations.

The survey also found financial services firms are already using AI for many different aspects of their financial data management. 55% of firms are using it for risk data management; 49% for client data management; 47% for portfolio data management and 46% for master data management.

The use of AI for risk data management is most popular in the UK, with 68% of decision-makers in the region say their firms are currently doing and more generally among firms with more than 5,000 employees, among which it is referenced by 65% of relevant respondents.

Yet for many firms, inhibitors remain. 50% of decision-makers rank technological limitations among the biggest roadblocks to implementing AI in financial data management while 46% referenced a lack of skilled personnel. The former was a particular problem for decision-makers working for firms in the DACH region, (56% of whom referenced it). The latter was seen as a major obstacle by asset owners, among which it was cited by 54%.

“Financial services organisations are increasingly attuned to the benefits that AI can bring to their businesses and, in particular, to the way they manage financial data,” Groot added. “Yet, they are still faced by multiple barriers in terms of skills shortages; the way they use technology and with respect to infrastructure and data management. That’s where drawing on the services of an expert in this area can play such a key role.”