Home » World » UK insurers face ‘data quality’ obstacles in AI adoption

UK insurers face ‘data quality’ obstacles in AI adoption

by Priya Shah – Business Editor

UK Insurers‘ AI ​Plans Hampered ⁢by ‌Data issues, Report Finds

LONDON – ​The rollout ‍of artificial intelligence within UK insurance firms ‍is being ⁢significantly slowed by‌ poor data‍ quality, according to a new report. Nearly three-quarters (72 percent) ‍of underwriters cite fragmented and unstructured⁢ data⁣ as the biggest obstacle ⁢to AI transformation, revealing a critical‍ challenge for the sector as it seeks to ​leverage​ the technology for​ efficiency gains.

The report, ‌conducted by tech firm CI&T‍ in collaboration with Reuters⁣ Events, highlights‌ that accurate risk assessment and pricing accuracy are also major concerns, cited⁢ by 42 percent and 36 percent of respondents respectively. ⁤ Professionals identified difficulty extracting, analysing, ‌and utilising unstructured data as the largest hurdle to optimizing data – a challenge flagged by 54 percent. Further​ issues ‍include consolidating data​ sources (24 percent)‌ and a​ lack of ⁣data literacy among⁢ employees (14 percent).

“AI’s success⁣ in insurance won’t ⁣be steadfast ‍by ⁤how ‍advanced⁤ the algorithms‌ are, but by the quality and accessibility of the data⁣ that feeds them,”⁣ said Mike Young,​ vice-president of insurance industry⁤ growth ⁣at CI&T. ⁤

The ⁣findings come as ⁣insurers face increasing pressure‌ to control costs, with 60 percent of respondents⁢ believing AI-led efficiency will ‌be crucial to offset rising claim costs and premiums. Claims inflation peaked at 12 ​percent in 2023 and is expected to‌ remain a key⁢ risk for UK insurers in ⁣2025 across property, casualty, and⁤ motor lines, driving the increased ⁤interest in technology.

“this research ⁣shows UK insurers are ready to innovate, but ‌they need to get⁢ their⁢ data⁤ house in order first,” ⁣Young added.

You may also like

Leave a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.