Financial services introducing AI but hindered by data issues

According to research by EXL, around 89 percent of insurance and banking firms in the UK have introduced AI solutions over the past year. However, issues with data optimisation could hinder their impact.

The researchers surveyed executives at top UK insurers and lenders about their AI strategies and found that 44 percent have deployed AI across eight or more business functions—especially in marketing, business development, and regulatory compliance. 

Nearly 9 in 10 financial services leaders reported investing upwards of £7.9 million in AI over their last fiscal year. Over a third invested £39 million or more, exemplifying the industry’s willingness to commit major capital to AI implementation.

Despite the positive strides in AI integration, the study suggests that organisations might be overlooking the importance of prioritising their data operations. Nearly half (47%) admitted their organisations are only “minimally data driven,” raising concerns about the effectiveness of AI implementation without a solid data foundation.

“It’s clear industry leaders recognise AI’s potential, but external pressures to implement quickly can lead to unchecked investment,” commented Kshitij Jain, EMEA Practice Head at EXL. “The risk is that ensuring operations are truly data driven gets deprioritised, which can prove very costly.”

The research also identified a group of “Strivers,” representing 45 percent of respondents, who are implementing AI more narrowly across around four functions. Their focused approach has allowed them to efficiently leverage AI for cost-cutting, outperforming early AI adopters by 23 percentage points.

Additionally, over half of respondents are investing more in AI specifically due to advancements in generative AI. However, 70 percent voiced deep concerns about risks related to generative AI like potential brand damage and inaccurate data outcomes.

“The key with any AI rollout is a measured, strategic approach—getting the data architecture right, testing solutions, and training employees,” Jain concluded. “For enterprise adoption to succeed, boards must buy into AI’s capabilities and ensure investment is being used effectively.”  

A full copy of the research can be found here (registration required)

(Photo by Alev Takil on Unsplash)

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