Inside Singapore’s AI bootcamp to retrain 35,000 bankers

[SINGAPORE] Kelvin Chiang knew the five agentic AI models built by his team could in ten minutes do what used to take a private banker an entire day. With that in place, he went to show Singapore’s banking regulator the safeguards would sufficiently control the risks.

Before rolling out the tool that drafts documents for relationship managers at the private wealth arm of OCBC Bank, he took his team of data scientists less than a mile across the city’s downtown finance district to the Monetary Authority of Singapore (MAS). Chiang highlighted steps the bank would take if things went wrong with their blueprints and how staff would react if the system hallucinated.

After the presentation and discussion with representatives at MAS, he left feeling that engineers at the regulator embraced it, said Chiang, 52, the head of financial crime compliance analytics at Bank of Singapore. “They were quite happy.”

Singapore’s AI efforts underscore a unique balancing act: The Government is working hand in glove with the country’s largest banks to teach new technology skills. The unspoken intent is to limit the large-scale job losses seen at some financial firms in the US and Europe. At stake is the future of thousands of bank workers at a time when giants of the industry, such as Goldman Sachs Group, have told staff to expect more job cuts as they take advantage of AI.

Companies around the world are turning to agentic AI as it’s more powerful than earlier technology iterations, with its models able to take actions independently and do multiple steps at once. In Singapore, the country is banking on a higher level of government involvement to help carve out a path for workers that focuses on improving skill sets and cushions the need for mass layoffs.

Singapore’s Minister for National Development Chee Hong Tat, who’s also deputy chairman of the MAS, has said the three large banks DBS, OCBC and UOB are retraining all 35,000 of their domestic staff over the next one to two years.

“The government is doing something about it because they realise that this capability and this change is actually infusing potentially a lot of fear,” said Violet Chung, a senior partner at McKinsey. “Given what we’ve seen in other markets like the US where we’re seeing much more aggressive job cuts and reductions, the government is essentially aware that we need to do something as a country to do something for these leading companies.”

For David, 39, who manages money for a bank’s wealthy clients, smarter technology is helping him work faster than at any time in his 16-year career, but that’s raising the expectations of his bosses and has left him feeling unsettled. He would typically spend around an hour preparing a single customer order form – now, it takes him 10-to-12 minutes. That means more time in front of clients, he said. He declined to give his full name discussing private details about his work.

Banks will be able to increase the number of customers that each of their relationship managers can cover, say from 50 up to 60 or 70, according to Mohan Jayaraman, senior partner at Bain.

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“The argument is that if you are able to spend more time with customers, you get better coverage,” he said. “You are increasing the ambit of people covered with your proposition, and at the same time giving the RM more ability to earn on a larger pool.”

Singapore’s National Jobs Council, which sprang out of the country’s employment needs during the Covid-19 pandemic, now also works with the not-for-profit Institute of Banking and Finance as a key partner to foster job growth for the finance industry. In some cases, as roles change, the institute works with and pays for finance firms to map out how staffers can take on redesigned roles or pivot to new career paths. In one scenario it offers banks up to 90 per cent salary support to reskill mid-career staff or new hires, according to its website.

The MAS says it works closely with the IBF, financial institutions and unions to prepare the sector’s workforce for AI adoption.

OCBC and UOB have said they are not making AI-related job cuts. DBS has said it won’t lay off permanent staff, but expects to reduce about 4,000 temporary and contract roles over the next three years as vendor contracts end. A Bloomberg Intelligence analysis forecasts DBS will make bigger AI-derived cost savings than its peers and help boost pretax profit by up to S$1.6 billion, or about 17 per cent, in the next few years.

Staff at DBS now use an internal AI assistant that handles more than one million prompts a month. It’s also built role-specific tools, including one for customer service officers that has reduced call handling time by up to 20 per cent. UOB has given all its employees access to Microsoft Copilot and deployed more than 300 AI use cases across the bank.

Watching from the inside, Vania Lim, 22, spent last summer as an AI intern in the global payments team at HSBC Holdings. She’s optimistic about new roles emerging in digital assets and improving use cases for wallets, but worries that some of the skills for junior hires aren’t all that unique anymore.

“Everyone is so well versed with AI nowadays,” she says. “It’s no longer so much of a competitive advantage.”

Meantime, older staff like Woon Leng, in her 60s, says the training to keep up with new technology feels like one more thing piled on top of an already demanding job of managing a branch.

She’s worked at a local bank for more than 40 years and now uses ChatGPT at her branch to help answer customer questions about products. Staff also have to take online courses on AI after work as it’s too busy during the day and try to pass a test afterwards, she added. She declined to give her full name discussing her employer.

Many banks are choosing not to fill roles when staff move on either within the firm or outside it, said Walter Theseira, associate professor of economics at Singapore University of Social Sciences.

“Of course, companies don’t like to do layoffs and redundancies, especially if they are major firms that the Singapore economy and government watches very closely,” he said. “But firms can pursue a headcount reduction simply by not filling roles when you have natural attrition.”

At OCBC, there were fewer than a handful of people in the AI lab when Kenneth Zhu joined in 2018. Eight years later, the 36-year old executive director of data science and AI oversees a lab that sits within a data office of more than 100 staff. Some 400 models make six million decisions every day from flagging suspicious transactions, to scoring credit risk and filtering out false positives in anti money laundering systems that once chewed up compliance officers’ time.

While it is too early to assess if the Singapore approach will pay off for banks and their staff, Jochen Wirtz, vice dean of MBA programmes and professor of marketing at National University of Singapore, says the technology’s potential remains huge and cautions against firms holding back.

“My hunch is that we haven’t really scratched the surface yet,” he said. “Banks would be completely stupid now to load up on employees who they will then have to let go again in three or four years. You’re much better off freezing now, trying to retrain whatever you can.”

At UOB, the bank is busy building AI fluency across the organisation as well as training staff, such as via an internal “Better U Pivot” programme.

“Inaction is not really an option for us or anybody,” said Alvin Eng, its head of enterprise AI. “It’s a slow path to irrelevance.” BLOOMBERG