AI Specialists Command $25,000 Daily Fees from Wall Street Banks

Felipe Sinisterra and Dave Wang are gaining attention for their guidance to Wall Street bankers on improving their AI tactics.

On a bright March afternoon, this well-respected duo in finance training addressed a venture capital firm’s team in New York. Wang, aged 31, demonstrated how Google’s AI model, Gemini, could analyze founder pitch videos.

He showcased a web application that employed behavioral analysis techniques used by the FBI to match transcripts with visual cues like body language and facial expressions, helping to pinpoint potential issues.

Later, Sinisterra, 30, educated attendees on using OpenAI’s ChatGPT and Anthropic’s Claude to review earnings call transcripts for critical statements that could impact the market. The AI performed sentiment analysis and translated executives’ verbal remarks into quantifiable data for forecasting. Attendees realized how AI could streamline tedious tasks in their work.

Read: Wall Street prepares for a looming AI bubble and speculation on its potential burst

The price for this day’s session? $25,000. They now have a two-month waiting list.

“What we’re witnessing is that companies are regarding AI as a competitive edge, a proactive tool,” Sinisterra remarked. “In the future, it will be viewed as a fundamental necessity.”

As concerns regarding AI rise, major banks are strategically hiring more AI specialists while downsizing traditional banking roles. Standard Chartered Plc plans to cut thousands of support positions in the next four years. Citigroup Inc, Wells Fargo & Co, and Bank of America Corp collectively laid off over 5,000 employees in the first quarter of 2026, even amidst record-breaking profits.

Top executives are willing to invest heavily in advanced AI technologies, creating a push to incorporate these tools into their organizations.

Former fund managers at SoftBank, Sinisterra and Wang are instilling confidence and expertise in companies eager for transformation.

Founded in July 2025, Wall Street Prompt has partnered with T. Rowe Price Group Inc, Citigroup, and Bank of America, according to sources.

T. Rowe Price sought out the duo to train its investment team, while Citigroup and Bank of America employed them for sessions with external fund clients. Due to confidentiality agreements, Wall Street Prompt did not reveal its client roster. T. Rowe Price, Citigroup, and Bank of America opted not to comment on vendor-specific training.

Read: Wall Street banks cut 5,000 jobs despite record profits

The rising skill bar

Initially, financial institutions hesitated to embrace AI. In 2022, following the launch of ChatGPT, many global banks restricted the chatbot’s usage on their internal networks over security concerns.

Since then, JPMorgan has introduced the LLM Suite, a generative AI tool employed by most of its workforce. Goldman Sachs is collaborating with Anthropic to develop AI agents, while Bank of America claims its 18,000 developers have become 20-25% more efficient after adopting AI.

However, many bankers lack the training needed to effectively use AI tools, and others are stuck in outdated methods, presenting a chance for trainers who can enhance these AI systems.

“The main obstacle in large banks is not the technology; it’s the personnel,” noted Jake Bridge, APAC managing director at Evolution, a tech recruitment firm based in the UK.

“The range from Luddite to AI super adopter is vast; the biggest challenge in a bank is addressing both extremes.”

Asia is leading the charge in AI integration within banking and finance, with growing automation in payments, lending, and customer service.

Notably, Singapore is making AI literacy essential for anyone wanting to work in the sector. The city-state ranks first in the International Monetary Fund’s AI Preparedness Index among 174 countries, with 64% of its financial institutions implementing AI across critical business operations, according to a 2026 survey by the financial software company Finastra.

Wang and Sinisterra are contemplating a move to Singapore to cater to demands from banks and finance professionals looking to secure their roles and boost their employability.

Read: Why the world’s banks are wary of Anthropic’s latest AI model

Duncan, a 55-year-old Singaporean who preferred to remain anonymous, dedicated his evenings and weekends last year to a course sponsored by Nanyang Technological University to learn about AI applications. His previous employer, a major bank, had moved its Singapore operations to a more economical location overseas.

After nine months of job hunting, he recently landed a back-office position at a Singaporean bank and is optimistic about his newly acquired skills.

While many executives link productivity improvements to AI, there are rising concerns that even strong balance sheets may not ensure job security.

Although analyst roles are unlikely to disappear completely, they are expected to diminish from entry-level upwards, predicts Igor Sydorenko, CEO of Neurons Lab, an AI consultancy serving clients such as HSBC and AXA.

“Highly skilled professionals utilizing AI tools will accomplish 10 to 20 times more work, with greater accuracy and speed,” he stated. “They won’t need junior financial analysts or associates; they can handle tasks independently.”

Read: The rise of AI in financial services: Balancing innovation with integrity

Justin Tang, a buy-side analyst at hedge fund Regal Funds Management in Singapore, understands the challenge of bridging this gap. He dedicated three years to self-learning AI amidst a busy schedule—during commutes and between meetings.

Last year, he met Wang and Sinisterra.

“It was a transformative experience,” Tang reflected. “Analyzing a company used to take me hours. Now, with a prompt, I can extract key insights in just 90 seconds: what the company does, its main earnings drivers, and its story.”

Since then, Tang has attended several Wall Street Prompt training sessions, including one organized by Bank of America. Classes typically involve 20-30 participants, with costs covered by the host bank.

“I wasn’t surprised when leading banks started offering classes from Wall Street Prompt to clients like us,” said Tang. “It was more about when rather than if.”

Primarily using the techniques for personal development, he also utilizes them at work. At Regal, he restricts the tools to publicly available data like filings and earnings transcripts to protect client information.

Children of immigrants

Both Sinisterra and Wang have early connections to finance and a growing interest in technology. Sinisterra moved from Colombia to the US with his parents at age six, while Wang was born in New York City to Chinese immigrants in the 1980s.

Wang began selling scripts for the online game RuneScape shortly after moving to Ohio at age eight. While an undergraduate at Harvard, he became one of five students hired by Lyft Inc to assist its expansion in Boston by distributing business cards.

However, he generated more student email addresses from local universities, initiated mail-merge campaigns, and crafted targeted coupon codes that yielded enough referrals to pay for his tuition.

After interning at Blackstone Inc in 2016 and working with Morgan Stanley for over two years in 2017, he joined SoftBank’s Latin America Fund in 2019, leading investments in cryptocurrency.

He left two and a half years later to establish 99 Capital, a fund for digital assets, selling its general partnership after achieving solid returns for investors.

“It became clear to me,” Wang stated. “If I’m spending about 30% of my time on AI playbooks and getting the best returns I’ve ever seen, this is where I should focus all my energy.”

Read: Trillion-dollar tech sell-off ensnares all AI-related stocks

Sinisterra started his career as a software engineer at Facebook, noting that his desk was only 20 feet from Mark Zuckerberg’s. After positions at Goldman Sachs and Bank of America, he joined SoftBank as head of fintech in 2019, overseeing over $1.5 billion in investments.

While collaborating at the Japanese tech investment firm, they often teamed up, each developing their own AI strategies.

Wang left SoftBank in 2022, with Sinisterra following in 2023. In the summer of 2025, they spent a month in San Francisco, sharing an apartment and working from a co-working space while writing articles and newsletters on AI and finance.

The duo gained a strong readership among hedge fund managers and financial analysts. Initially aiming to create a data business, they discovered that the demand for educational opportunities was more compelling.

“Individuals kept saying we have the tools; we just don’t know how to use them as you do,” Sinisterra stated. “They wanted to learn rather than buy more software.”

Within two months of launching Wall Street Prompt in July 2025, a prominent investment firm reached out, prompting the duo to take a two-hour train trip from New York to train staff across equities, fixed income, and macro teams. Participants ranged from senior strategists to junior analysts.

Almost all clients have returned for additional sessions, with Sinisterra noting that a fund managing over $50 billion in assets is finalizing an agreement. He chose not to disclose the fund’s identity.

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Wang and Sinisterra are continually adapting to stay competitive. They have compiled a library of AI agents designed to understand each financial firm’s unique mindset. Their aim is for AI to handle 90% of logistical and technical tasks, enabling humans to focus on relationship-building, judgment, and decisions that drive profitability.

The market is increasingly crowded. Multiverse, a London-based upskilling platform founded by Euan Blair, the eldest son of former British Prime Minister Tony Blair, aims to train 15,000 AI apprentices over two years, serving clients like Citigroup, Microsoft, and KPMG.

Rogo Technologies Inc, a New York startup founded by ex-Lazard and JPMorgan bankers, raised $160 million in a Series D funding round this year, achieving a $2 billion valuation for software aimed at automating research and due diligence tasks traditionally handled by analysts.

Sinisterra and Wang are currently developing a live webinar product for financial professionals seeking AI training, intended to cost around $1,500 per participant.

“Ultimately, individuals are investing in transformation, not merely prompts or templates,” Sinisterra remarked. “We come in to spark that change. People are already considering these transformations; they just need guidance.”

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