Manish Sood , CEO at Reltio , explores how banking enterprises can get their data in order to harness and utilise AI in the most effective way . he global banking industry is finally catching on

T to Artificial Intelligence

( AI ), digital and cloud transformation , thanks partly to digital upstarts that have found innovative ways to grow amidst challenging markets . For example , digital-only and some datadriven regional banks have grown their deposits by as much as ten percent . In contrast , traditional banks have experienced deposit declines of three to five percent over the same period , according to research by McKinsey . Top-performing institutions have excelled by focusing on relationship banking and superior digital service in consumer finance while using data-driven interest rate pricing as another example .

The global banking and financial services sector has taken note of these opportunities . It is undergoing rapid digital transformation driven by the adoption of AI solutions . According to The Bank of England , 75 % of financial organisations were using AI in 2024 , with a further ten percent planning to use this technology over the next three years .

However , this surge towards using AI risks being undermined by a perennial problem in enterprise IT – a proliferation of siloed data linked to legacy and modern applications and systems . Whilst much of the impetus for AI in banking is to improve operations and customer service by collecting and analysing data , the reality is that for too many banks , www . intelligentfin . tech

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