Keep pulling the thread on Ido Segev.
Ido Segev predicts that challenger fintechs will likely be the first to drive customer adoption of AI banking services by offering clear value propositions, such as optimizing deposit interest rates.
Citing the McKinsey Global Banking Annual Report, Ido Segev predicts there will be 1-3 big winners among global banks (G-SIBs), 5-6 among super-regionals, and 10-15 among regional banks in the race to adopt AI.
A McKinsey report scenario analysis concluded the most likely outcome for AI in banking involves banks reaching a ratio of 20-30 agents per employee.
Under its most likely scenario, McKinsey projects that AI adoption could lead to a 25% reduction in a bank's overall costs, after accounting for increased IT spending.
McKinsey's analysis suggests a 20-25% cost improvement from AI translates to an additional $250 million to $500 million to the bottom line for every $100 billion in assets a bank holds.
The McKinsey Global Banking Annual Report estimates that AI-driven consumer optimization tools will cause overall banking industry profit pools to compress by 9-10%.
The projected 9-10% compression in banking industry profit pools due to AI is expected to translate to a 1-2% reduction in Return on Equity (ROE) for the average bank.
The McKinsey Global Banking Annual Review identifies artificial intelligence as one of its biggest themes for the banking industry this year.
Ido Segev observes that major LLMs like ChatGPT, Gemini, and Anthropic are surpassing each other in capabilities with new, more intelligent versions being released every 3 to 6 months.
Ido Segev suggests a key metric for AI adoption in banking is deploying agents to become "virtual employees," achieving a ratio of 20 virtual employees to one human employee.
According to Ido Segev, banking regulators are more conservative regarding the use of AI for credit decisions but have less concern about its use in operational areas like call centers.
Ido Segev uses the analogy that Formula 1 cars can drive quickly because of their amazing brakes to argue that strong AI safety and governance will accelerate, not hinder, adoption in banking.