JPMorgan ranks first for AI among banks with its systematic innovation approach

JPMorgan is topping the list for AI readiness and leadership among all banks globally for the third year in a row. According to think tank Evident AI ’s Bank Index report published today, the $3.7 trillion bank is followed by the following financial institutions to round out the top 10 spots: $648 billion Capital One; $1.5 trillion RBC ; $850 billion CommBank ; $239 billion Morgan Stanley ; $1.7 trillion Wells Fargo ; $1 trillion UBS ; $2.9 trillion HSBC ; $625 billion Goldman Sachs ; and $2.6 trillion Bank of America. [caption id="attachment_57382268" align="aligncenter" width="1165"] (Courtesy/Evident AI)[/caption] JPMorgan’s continued lead in the index is due to its consistency and conviction, Alexandra Mousavizadeh , co-chief executive at Evident AI, told FinAi News . The bank invested early and steadily across every dimension of AI capability the report tracks, from research and talent to infrastructure and governance, and continues to accelerate while others are trying to catch up, she added. Evident AI’s rankings are based on a weighted index that includes talent (45%), innovation (30%), leadership (15%) and transparency (10%). A systematic approach “What truly sets JPMC apart isn’t size or spending power, but its systematic approach to innovation,” Mousavizadeh said. “Anticipating, rather than reacting, to the ‘ChatGPT moment,’ they launched a dedicated AI research team back in 2017, and have since built a relentless innovation engine that tackles complex problems with specialist expertise, constantly pushing the boundaries of the business in parallel with what technology can do.” The “ChatGPT moment” was the November 2022 public launch of the OpenAI app that grabbed global markets by storm. The New York-based JPMorgan Chase was among the first to establish AI testing environments, centralize use case selection and define clear frameworks for ROI, Mousavizadeh said, adding that now the bank is focused on expanding deployment of AI for scale. JPMorgan is deploying AI for: Software development; Fighting fraud; Planning and knowledge management; and Streamlining embedded payments . JPMorgan has more than 15 active AI use cases, according to the report, while the second bank on the list, Capital One, has fewer than five. Cap One ‘scales at pace’ Capital One maintained its second place position on the list with its growing number of patents and deep bench of AI talent on the heels of its acquisition of Discover Financial Services . [caption id="attachment_57382266" align="aligncenter" width="1031"] (Courtesy/Evident AI)[/caption] Capital One’s position reflects depth of capability rather than breadth of disclosure, Mousavizadeh said, adding that the bank has consistently prioritized sharing only the most sophisticated examples, such as its multiagent Chat Concierge . “Behind the scenes, Capital One continues to scale at pace,” Mousavizadeh said. “It has doubled the size of its AI research team and increased AI headcount by 73% post-Discover acquisition, building one of the strongest AI talent bases across the banks.” Capital One, in fact, ranks first for talent on the index ahead of JPMorgan second place, according to the report. Early investment pays off Banks, globally, that started in the AI race before the “ChatGPT moment” are pulling ahead compared with banks that started focusing on it later, Mousavizadeh said. Scores for the top 10 banks in the index rose an average of seven points year over year, compared with 3.7 points across the entire Index. [caption id="attachment_57382267" align="aligncenter" width="987"] (Courtesy/Evident AI)[/caption] “These are the institutions that made early, deliberate investments in people, strategy and central orchestration, and those decisions are now paying off,” Mousavizadeh said. “We’re seeing this reflected in the growing number of use cases moving into production and in disclosures showing measurable business impact.” Banks that lack board-level alignment on AI strategy or centralized investment are struggling to get organized, and the longer they wait, the harder it becomes to catch up, she said. “If you’re very small, or very late, you can’t simply turn this on,” Mousavizadeh said. Evident AI isn’t seeing just a widening gap between large and small banks, she said, adding that the results are due to more than capital expenditure alone. The $178 billion Ally Financial, for example, has a small asset size compared with the top 10 banks, which have more than $1 trillion in assets. However, Ally is challenging banks in the list of the top 20 banks with its AI leadership and execution, Mousavizadeh said. “The differentiator isn’t spending power, but culture, leadership focus and an organizationwide commitment to AI and data. Smaller banks can’t do everything, but by placing focused bets on the right areas, they can compete effectively against far larger peers.” U.S. banks seem to have an edge on AI deployment compared with banks in other parts of the world, accounting for five of the top 10 in the index, Mousavizadeh said. U.S. banks “dominate on almost every input metric: 44% of all AI talent tracked across the index, 67% of research output, 89% of patents and 46% of venture [deals],” she said.

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