{"id":5827,"date":"2026-10-02T02:15:56","date_gmt":"2026-10-02T02:15:56","guid":{"rendered":"https:\/\/www.vaultinsider.top\/?p=5827"},"modified":"2026-10-02T02:15:56","modified_gmt":"2026-10-02T02:15:56","slug":"ai-in-regulated-industries-bofa-and-sp-on-the-huge-gains-to-be-had-and-the-risks-of-rushing-in","status":"publish","type":"post","link":"https:\/\/www.vaultinsider.top\/?p=5827","title":{"rendered":"AI in regulated industries: BofA and S&#038;P on the huge gains to be had, and the risks of rushing in"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/fortune.com\/img-assets\/wp-content\/uploads\/2026\/10\/55563689899_8028688390_3k.jpg?w=2048\" \/><\/p>\n<p>Bank of America\u2019s chief technology and information officer said one of the most common AI mistakes is reaching for it first. His bank also plans to double its AI budget next year.<\/p>\n<div>\n<p class=\"wp-block-paragraph\">\u201cOne of the biggest mistakes we see us and others doing is rush to AI as a solution,\u201d Hari Gopalkrishnan said at <em>Fortune<\/em>\u2018s AIQ Summit in New York, \u201cwhen deterministic models do a plenty good job.\u201d<\/p>\n<p class=\"wp-block-paragraph\">Gopalkrishnan appeared with Sally Moore, S&amp;P Global\u2019s chief client officer and co-head of Kensho Data &amp; Platforms. <em>Fortune<\/em> Editorial Director Andrew Nusca moderated.<\/p>\n<h2 class=\"wp-block-heading\"><strong>Bank of America: simple tools first<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">Gopalkrishnan said the bank starts with what clients need and a \u201cprocess inventory\u201d of the steps behind their requests. It often decides against AI \u2014 \u201cplenty of times,\u201d he said. A mobile app or a real-time decision rule can be the better answer.<\/p>\n<p class=\"wp-block-paragraph\">Every AI project also goes through a review that covers 16 \u201cpillars\u201d of risk, including privacy, bias, workforce impact and intellectual property. \u201cWe\u2019re not going to implement a chatbot that only answers to certain accents,\u201d he said.<\/p>\n<p class=\"wp-block-paragraph\">He said the bank has used AI for more than a decade, starting with fraud models. Its Erica virtual assistant has handled 3.6 billion transactions, he said, and without it the bank would need 11,000 more people to answer the calls. A March bank press release counted Erica\u2019s client interactions at more than 3.2 billion.<\/p>\n<p class=\"wp-block-paragraph\">The caution comes with heavy spending. CEO Brian Moynihan said in September that about 140 AI uses cost $400 million and generate $800 million in benefit, and that the AI expense budget will double next year. <\/p>\n<p class=\"wp-block-paragraph\">That spending is routed carefully, and Gopalkrishnan said the bank is model-agnostic. An orchestration layer (called Orchestra, naturally) sends simple classification tasks to approved open-weight models running on the bank\u2019s own GPUs, and harder reasoning to proprietary models. He said this also helps control token costs. In wealth management, advisors can now prepare for client meetings in \u201cseconds and minutes,\u201d work that used to take days and weeks, he said.<\/p>\n<p class=\"wp-block-paragraph\">On agents, the bank isn\u2019t hurrying toward autonomy. \u201cThere is so much juice to be squeezed right now with assistive agents that are actually working with humans in the loop,\u201d he said. The bank will go further as control infrastructure improves.<\/p>\n<p class=\"wp-block-paragraph\">He also addressed security, and said AI models are getting better at finding software vulnerabilities, so patching and secure development matter whether or not a company uses AI. The stakes go beyond any one bank, he said: if a small bank somewhere has a problem, people lose faith in the financial system.<\/p>\n<h2 class=\"wp-block-heading\"><strong>S&amp;P: data as the currency<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">Moore said her 160-year-old company is repositioning itself \u2014aggressively and carefully. S&amp;P is the world\u2019s largest credit rating agency, and one of the largest index providers, and much of its financial data feeds regulated workflows, she said. \u201cData is the currency within AI,\u201d she said. Clients need accuracy, citations, and auditability and traceability back to the source.<\/p>\n<p class=\"wp-block-paragraph\">She credited an early bet. S&amp;P bought the AI company Kensho in 2018, and that has \u201cgiven us an advantage,\u201d she said, explaining that S&amp;P has since put Kensho at the center of the business. On July 6, it split Market Intelligence into two units. The first, Kensho Data &amp; Platforms, pairs \u201cKensho Data,\u201d the client-facing data and AI delivery layer, with a Platforms group that houses Capital IQ, Ratings Direct, Visible Alpha and With Intelligence. The second unit is Enterprise Solutions. CEO Martina Cheung said the changes should support revenue growth and better margins. <\/p>\n<p class=\"wp-block-paragraph\">About two years ago, S&amp;P also created a chief client office, which Moore leads, to work more closely with clients. It has a labs group and what it calls forward-deployed experts, who work with clients on AI.<\/p>\n<p class=\"wp-block-paragraph\">S&amp;P serves 60,000 clients at different stages of AI adoption, she said. It works with frontier AI labs, puts its data into large language models and productivity tools, and now builds its own agents. Use runs from broad tasks, such as bankers preparing for meetings and pitch books, to specialized agents built for one job.<\/p>\n<p class=\"wp-block-paragraph\">She gave one example. A tier-one bank with 8,000 bankers was combining S&amp;P content sets in its own platform. S&amp;P helped bring it to production \u201csix times quicker,\u201d she said, and accuracy rose from about 60% when the bank started to 98% afterward. (She didn\u2019t name the bank, and the figures are S&amp;P\u2019s own.) S&amp;P also built a \u201ccredit memo builder\u201d agent that keeps humans in the loop and relies on confidence in the underlying data.<\/p>\n<p class=\"wp-block-paragraph\">Like Gopalkrishnan, she talked about using the right tool for the job. S&amp;P\u2019s deterministic option for language models is an API, so it doesn\u2019t run up heavy token costs, she said. More complex \u201cadaptive data retrieval at scale\u201d costs more. Clients also pay for data, technology and people efficiency from different budgets, so S&amp;P talks with them about a range of outcomes.<\/p>\n<h2 class=\"wp-block-heading\"><strong>Where they part ways<\/strong><\/h2>\n<p class=\"wp-block-paragraph\">Asked whether he ever chooses against AI, Gopalkrishnan said the simplest answer is often the best one. \u201cAI is not always the right answer,\u201d he said.<\/p>\n<p class=\"wp-block-paragraph\">Moore agreed, and then took the point further. \u201cI think Hari said it really well. It\u2019s not around the right tool. It\u2019s a little bit about reinvention,\u201d she said. \u201cWhat am I trying to solve for here? And where can this technology take me?\u201d<\/p>\n<p class=\"wp-block-paragraph\">Inside S&amp;P, that has meant a central transformation office that brings together technologists and, more recently, data operations.<\/p>\n<p class=\"wp-block-paragraph\">In the closing lightning round, Moore pointed to \u201cembedded intelligence,\u201d which she said \u201ccreates an opportunity to go beyond the clients that you serve today.\u201d<\/p>\n<p class=\"wp-block-paragraph\">Gopalkrishnan had the last word: \u201cI think anticipating your client needs and serving them where they are will differentiate you in otherwise commoditized space.\u201d<\/p>\n<p class=\"wp-block-paragraph\"><em>For this story,\u00a0<\/em>Fortune<em>\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.<\/em><\/p>\n<\/div>\n<p>#regulated #industries #BofA #huge #gains #risks #rushing<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Bank of America\u2019s chief techno&hellip; <\/p>\n","protected":false},"author":1,"featured_media":5828,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[3631,8919,6653,1872,2251,7834,1951,8920],"class_list":["post-5827","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-finance-news","tag-bank-of-america","tag-bofa","tag-gains","tag-huge","tag-industries","tag-regulated","tag-risks","tag-rushing"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI in regulated industries: BofA and S&amp;P on the huge gains to be had, and the risks of rushing in - Finance News<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.vaultinsider.top\/?p=5827\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI in regulated industries: BofA and S&amp;P on the huge gains to be had, and the risks of rushing in - 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