Wall Street banks paying ₹21 lakh a day to learn AI from two ex-SoftBank investors

Banks and investment firms across Wall Street are paying as much as $25,000, or roughly ₹21 lakh, per day for specialised artificial intelligence training sessions led by two former SoftBank investors, reflecting the growing urgency around AI adoption inside the global finance industry.

According to a syndicated report published by NDTV, former SoftBank executives Felipe Sinisterra and Dave Wang are helping banks, hedge funds and investment professionals learn how to integrate AI tools into core financial workflows ranging from earnings analysis to investment research and behavioural assessments.

The pair’s company, Wall Street Prompt, founded in July 2025, is reportedly booked out for nearly two months as demand surges among firms seeking to build AI capabilities quickly.

AI moves from experiment to workplace necessity

During one recent training session in New York, Wang demonstrated how Google’s Gemini AI model could analyse startup pitch videos by combining transcript reviews with behavioural analysis methods linked to facial expressions and body language.

Sinisterra, meanwhile, showed participants how tools such as OpenAI’s ChatGPT and Anthropic’s Claude could scan earnings call transcripts, identify market-moving comments, conduct sentiment analysis and convert management commentary into spreadsheet-based financial forecasts.

The sessions are designed to automate some of the most time-consuming tasks traditionally handled by junior analysts and research teams.

Speaking in the report, Sinisterra said AI is no longer being treated merely as an experimental tool.

“What is happening now is that people are seeing AI as a source of edge, a source of offense,” he said. “What we'll see in the future is that people will see it as a necessity.”

Global banks intensify AI adoption

The rapid rise in demand for AI training comes as major financial institutions deepen investments in automation and generative AI systems.

Several large banks have already begun integrating AI across internal operations:

• JPMorgan has rolled out its generative AI platform, LLM Suite, to most employees
• Goldman Sachs is reportedly working with Anthropic to build AI agents
• Bank of America said its 18,000 developers became 20% to 25% more productive after using AI tools
• Standard Chartered is preparing to cut thousands of support roles over the next four years

The report also noted that Citigroup, Wells Fargo and Bank of America collectively cut more than 5,000 jobs during the first quarter of 2026 despite reporting strong earnings.

Industry experts increasingly believe AI will reshape traditional finance roles rather than eliminate entire professions outright.

Rising pressure on finance professionals

While banks are investing heavily in AI systems, many employees are still struggling to adapt to rapidly changing expectations.

According to the report, a growing gap now exists between employees who actively use AI tools and those who remain unfamiliar with newer systems.

Jake Bridge, APAC Managing Director at technology recruitment firm Evolution, said the challenge for banks is no longer about access to technology itself.

“The biggest challenge inside a large bank isn't the technology, it's the people,” he said in the report.

The transition is becoming especially visible in Asia, where financial institutions are embedding AI across payments, lending and customer service operations.

Singapore has emerged as one of the leading AI-focused finance hubs globally. According to a 2026 survey by financial software company Finastra, 64% of financial institutions in Singapore are already deploying AI across key business functions.

The report also cited International Monetary Fund rankings showing Singapore leading 174 countries on AI preparedness.

AI reshapes analyst roles across banking

Experts cited in the report warned that AI could significantly reduce demand for entry-level finance roles over time.

Igor Sydorenko, chief executive of AI consultancy Neurons Lab, said highly skilled professionals using AI systems would eventually be able to handle workloads previously distributed across multiple junior employees.

“Highly skilled people, with AI tools, will be able to do 10, 20 times more, much better, much faster,” Sydorenko said.

The changes are already influencing career decisions inside the industry.

Singapore-based hedge fund analyst Justin Tang told the publication that AI tools had drastically reduced the time required for company analysis.

“It used to take me hours to analyse a company. Now I plug in a prompt, and in 90 seconds, I get the key points,” Tang said.

Tang has reportedly attended multiple AI workshops hosted through Wall Street Prompt, including sessions organised by Bank of America.

From finance investors to AI educators

Both Wang and Sinisterra built careers across finance and technology before launching their AI training venture.

Wang previously worked at Blackstone, Morgan Stanley and SoftBank’s Latin America Fund, where he focused on crypto investments.

Sinisterra earlier worked as a software engineer at Facebook before joining Goldman Sachs, Bank of America and later SoftBank as Head of Fintech.

The two began collaborating on AI workflows while working together at SoftBank and later decided to focus entirely on AI education after seeing growing demand from finance professionals.

According to the report, their company is now developing a webinar-based AI training product for finance professionals willing to pay around $1,500 individually for advanced AI learning programmes.

Finance industry enters next phase of AI transformation

The rapid growth of firms such as Wall Street Prompt highlights how artificial intelligence is shifting from a productivity tool to a strategic workforce requirement inside banking and investment management.

As financial institutions continue cutting operational costs while expanding AI spending, employees across the sector are facing increasing pressure to build AI fluency to remain competitive.

For banks, the challenge now extends beyond deploying AI systems. The larger test may be whether employees can adapt quickly enough to keep pace with the industry’s accelerating transformation.