Felipe Sinisterra and Dave Wang cashed large checks and told Wall Street bankers what was missing in their AI plans.
One afternoon in March, two popular finance trainers spoke to employees of a venture capital fund in New York. Wang, 31, showed how Gemini, an AI model developed by Alphabet Inc.’s Google, can be used to analyze founders’ pitch videos. He demonstrated how a web application that incorporates behavioral analysis techniques used by the FBI can help identify potential red flags by comparing transcripts with visual cues such as body language and facial expressions.
Sinisterra, 30, then showed the class how to use OpenAI’s ChatGPT and Anthropic’s Claude to scan transcripts of earnings calls to find the statements that most move the market. The machine performed sentiment analysis and translated executives’ statements into numerical inputs in spreadsheets to predict future financial performance. Attendees were able to see how AI can help streamline some of the most labor-intensive parts of their jobs.
What is the bill for that day? $25,000. And they have been delayed for two months.
“What’s happening now is that people are seeing AI as a source of edge, a source of attack,” Sinistera said. “In the future, people will see it as a necessity.”
Big banks, caught up in the AI scare, are hiring more AI experts and shrinking the role of traditional banks. Standard Chartered is preparing to make thousands of support jobs redundant over the next four years. Citigroup, Wells Fargo and Bank of America have cut more than 5,000 jobs combined in the first quarter of 2026, despite a record earnings season.
Executives are willing to spend significant amounts of money to deploy technology beyond basic operations, are experimenting with AI tools themselves, and are increasing pressure to embed technology at all levels. Mr. Sinisterra and Mr. Wang, a former SoftBank fund manager, sell confidence and fluency to companies looking to transform.
Wall Street Prompt, which they founded in July 2025, has worked with T. Rowe Price Group, Citigroup and Bank of America, according to people familiar with the matter. T. Rowe Price brought on the pair to train investment professionals, the people said. Citigroup and Bank of America used them to run sessions for external fund clients. Wall Street Prompt is bound by a non-disclosure agreement and declined to confirm its client list. T. Rowe Price, Citigroup and Bank of America also declined to comment on vendor-specific training.
rising skill bar
Financial institutions weren’t necessarily enthusiastic about AI. When ChatGPT was launched in 2022, major world banks restricted chatbot access on their internal networks due to concerns about security lapses.
Since then, JPMorgan has rolled out LLM Suite, a generative AI tool used by most employees. Goldman Sachs is working with Anthropic to develop an AI agent. Bank of America claims that the productivity of its 18,000 developers increased by 20% to 25% after using AI.
“What’s happening now is that people are seeing AI as a source of edge, a source of attack.”
Still, many bankers are not trained to use AI tools effectively, while others are stuck with outdated models, and this discrepancy creates a need for trainers who can get the most out of these AI systems.
“The biggest challenge inside the big banks is not technology, it’s talent,” said Jake Bridge, APAC managing director at UK-based technology recruitment firm Evolution. “There is a huge spectrum from Luddites to AI super-adapters, and the biggest challenge for banks is how to respond to both.”Asia is leading the way in incorporating AI into banking and finance, where payments, lending and customer service are increasingly automated.
Especially in Singapore, AI fluency is increasingly becoming a prerequisite for those seeking a career in this field. The city-state ranks first among 174 countries on the International Monetary Fund’s AI Readiness Index, with 64% of the country’s financial institutions implementing AI in key business functions, according to a 2026 study by London-based financial software company Finastra.
Mr. Wang and Mr. Sinisterra are now considering moving there to tap into demand from banks and financial professionals who are struggling to protect their positions and retain jobs.
Mr Duncan, 55, who lives in Singapore and declined to give his full name, spent nights and weekends last year in classes supported by Nanyang Technological University, practicing how to use AI. His employer, a major bank, had previously moved its Singapore operations to a lower-cost overseas center.
After being unemployed for nine months, I landed a back-office job at a bank in Singapore last month and am excited about my new skills.
While some executives say AI has improved productivity, there are growing concerns that strong balance sheets are no longer enough to protect jobs. Igor Sidorenko, chief executive of AI consultancy Neurons Lab, whose clients include HSBC and AXA, says the role of analyst will not disappear, but will fade from the bottom up. “Highly skilled people will be able to do their work 10, 20 times better and much faster with AI tools,” he said. “They don’t need junior financial analysts or associates. They’ll just do it on their own.”
Justin Tan, who lives in Singapore, knows the anxiety of trying to bridge that gap. The buy-side analyst at hedge fund Legal Funds Management spent three years teaching himself AI in the spare moments of his day: while riding the bus, between meetings, and during quiet moments when most people are scrolling. Then, last year, he met Mr. Wang and Mr. Sinisterra. “It was like a lightbulb went on,” Tan said. “It used to take hours to analyze a company. Now I can type in a prompt and in 90 seconds find out the key points: what the company does, its core revenue drivers, its story, and more.”
Since then, Mr Tan has attended numerous Wall Street Prompt training sessions, including one sponsored by Bank of America. He said each class typically operates with 20 to 30 people, and the seats are covered by the host bank.
“I wasn’t surprised when top banks started offering Wall Street Prompt classes to customers like us,” Tan said. “It was more a matter of when than if.”
Although Tan uses the techniques he has learned primarily for personal purposes, he also applies them to his day-to-day work. Legal limits its tools to publicly available materials such as tax returns and revenue records. No client data is entered.
children of immigrants
Mr. Sinisterra and Mr. Wang have both been involved in finance since their formative years and developed an early interest in technology. Mr. Sinisterra immigrated to the United States from Colombia with his parents when he was 6 years old, and Mr. Wang was born in New York City, but his parents immigrated from China in the 1980s.
Wang said he sold the script for the online game RuneScape when he moved to Ohio at age 8. Wang, who was an undergraduate at Harvard University, said he was one of five students hired by Lyft to promote Boston’s expansion by handing out business cards on the streets. Rather than sticking to that, he said he collected student email addresses from local universities, ran an email merge campaign, and created targeted coupon codes to get enough referrals to pay for his tuition.
After interning at Blackstone in 2016 and working at Morgan Stanley for over two years in 2017, he joined SoftBank’s Latin America Fund in 2019 and led cryptocurrency investments. He left after about two and a half years and founded 99 Capital, a digital asset fund. He sold the fund’s general partnership and exited after making a profit for investors.
“It was very clear to me,” Wang said. “If you’re spending about 30% of your time developing an AI playbook and this is clearly your best year of returns ever, then you should be spending 100% of your time on this.”
Sinisterra joined Facebook as a software engineer after graduating from college, but his desk was 20 feet from Mark Zuckerberg’s. After working at Goldman Sachs and Bank of America, he joined SoftBank in 2019 as head of fintech, where he helped develop over $1.5 billion in investments.
“What’s happening now is that people are seeing AI as a source of edge, a source of attack.”
The two, who worked together at a Japanese technology investment firm, were in constant conversation and each developed their own AI playbooks.
Mr. Wang will leave SoftBank in 2022 and Sinistera in 2023. In the summer of 2025, the two shared an apartment in San Francisco for a month, working from a co-working space and publishing newsletters and posts about AI and finance. The readers who keep coming back are hedge fund managers and financial analysts. The original plan was to build a data business, but the education opportunity proved more attractive, they said.
“People kept saying we have the tools, but we just don’t know how to use them like you guys,” Sinisterra said. “They wanted to learn rather than buy more software.”
Within two months of founding Wall Street Prompt in July 2025, they were approached by a major investment firm, and the two took a two-hour train ride from New York to its headquarters, where they trained staff in the equities, fixed income and macro teams, the people said. Attendees ranged from senior strategists to junior analysts.
Sinistera said nearly all of his clients have returned for additional sessions, including funds with more than $50 billion in assets that are currently finalizing contracts. He declined to give his name.
Wang and Sinisterra also repeat to maintain their advantage. They built a library of AI agents trained to understand how financial companies think. The goal, they say, is for AI to handle 90% of the logistics and technical work, allowing people to focus on relationships, judgment, and profit-making decisions.
The field is getting crowded. Multiverse, a London-based skills development platform founded by former British Prime Minister Tony Blair’s eldest son Ewan Blair, is working with clients including Citigroup, Microsoft and KPMG to train 15,000 AI apprentices over two years. Earlier this year, Logo Technologies, a New York startup whose founders include former Lazard and JPMorgan bankers, raised a $160 million Series D round at a $2 billion valuation for software that automates the research and hard work that once occupied an analyst’s day.
Sinisterra and Wang are currently building a live webinar product for financial professionals who feel inadequately trained in AI and are willing to pay about $1,500 each.
“What people are actually paying for is transformation, not just prompts or templates,” Sinistera says. “What we’re doing is getting in there and causing that change. Everyone is already thinking about these changes. They just don’t know which direction to go in.”
Suvarna and Poe write for Bloomberg.
