Artificial intelligence now finance sector’s ‘connective tissue’
Artificial intelligence now finance sector’s ‘connective tissue’
Publish Date: 2026-02-10 04:03:00
Source Domain: www.computerweekly.com
Artificial intelligence (AI) technology is used by all but 1% of UK financial services firms as the debate over its use in the sector comes to an end, according to a major annual study by Finastra.
In its Financial services state of the nation 2026 report, the IT supplier described AI as the “connective tissue” of the finance sector and revealed that the technology’s evolution is also driving up spending in other areas, such as security and cloud.
Finastra CEO Chris Walters said institutions are no longer debating whether to adopt AI, but are focused on where it delivers tangible value and how it can be deployed responsibly.
“Only 2% of [global] respondents say they are not using AI at all, which underscores how decisively the industry has crossed the threshold,” he said.
The report said: “AI now sits at the heart of financial innovation. No longer confined to back‑office automation, it is powering real‑time fraud detection, personalised product recommendations, intelligent underwriting and dynamic customer engagement.
AI is becoming the connective tissue of banking – the intelligence layer that links data, channels, and services into something coherent and responsive
Finestra report
“[AI] reduces friction, accelerates decisions and tailors experiences in ways that feel intuitive to customers. It is becoming the connective tissue of banking – the intelligence layer that links data, channels and services into something coherent and responsive.”
The report revealed the top AI use cases finance firms are currently running or piloting. These include risk management and fraud detection (71%), data analysis and reporting (71%), customer service and support assistants (69%) and document intelligence management (69%). It said the top three priorities for the year ahead are AI-driven personalisation, agentic AI for workflow automation, and AI model governance and explainability.
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