India banks dabble in Wall Street-lite job culls
RPT-BREAKINGVIEWS-India banks dabble in Wall Street-lite job culls The author is a Reuters Breakingviews columnist. The opinions expressed are her own.
By Shritama Bose
MUMBAI, Aug 4 (Reuters Breakingviews) - India's banks may need to take some lessons in layoffs from Wall Street. Staffing levels at HDFC Bank HDBK.NS, ICICI, Axis AXBK.NS and Kotak Mahindra KTKM.NS fell by up to 4% during the 12 months to the end of March after years of increases. It's largely the result of businesses maturing, revenue growth slowing and more tasks getting automated. Goldman Sachs GS.N, Morgan Stanley MS.N and others routinely dump more. But India generally frowns on making people redundant. AI is likely to force its financial services firms – and others – to look past the taboo and embrace deeper cuts.
Western lenders and investment banks tend to slash their ranks when a downturn hits. But some, like Goldman, also oust those performing poorly – as much as 5% of employees – each year. By that metric, their Indian peers are only dabbling. Moreover, natural attrition seems to account for most, if not all, of the reductions.
That does the job for now as the businesses weaken somewhat. Total revenue at $41 billion Axis for the financial year to the end of March grew at nearly a quarter of its pace the previous year, while Kotak's fell slightly. Yet the compensation ratio for both, and for $122 billion HDFC, stayed flat, suggesting the softly-softly downsizing is working, Breakingviews calculates, using data disclosed by the lenders. Increased outsourcing of tasks like loan collection and IT management weighs on headcount too.
The rise of automation, though, whether due to AI or less advanced technology, is likely to increase pressure to reduce staff numbers. A substantial share of new business, for example, now comes from attracting new retail customers digitally, reducing the need to keep expanding and staffing branches. And AI capabilities are making humans increasingly redundant at routine functions like fraud monitoring and data analysis.
At Axis Bank, where staff numbers fell 3%, CEO Amitabh Chaudhry has set targets that include using AI to automate and augment half of its customer calls in the current financial year. HDFC, which reported a 2% workforce reduction, is applying AI to retail credit decisions and trade transactions.
As banks commit to adopting AI across a growing chunk of their operations, more job functions will have to go, though they are likely to find more productive jobs for some. The impact will eventually show up at government-owned lenders like State Bank of India SBI.NS and intensify a slow-burn shrinkage underway there for years.
Their executives are likely to rely on natural attrition, retirements and reduced hiring for as long as possible. But the bigger the impact of AI and the more their businesses mature, the greater the chance that they will have to follow Wall Street's lead by breaking with convention to give more people the boot.
Follow Shritama Bose on LinkedIn and X.
CONTEXT NEWS
HDFC Bank, ICICI Bank, Axis Bank and Kotak Mahindra Bank reported an up to 4% year-on-year fall in their employee counts as of March 31.
In its annual report for the 12 months ended March, released on July 11, HDFC said the number of permanent employees on its rolls stood at 211,178, 2% lower than the level as on March 31, 2025. ICICI's filings show a 4% fall in the metric to 124,029, while Axis and Kotak reported declines of 3% and 1% respectively.
(Editing by Antony Currie; Production by Aditya Srivastav and Ujjaini Dutta)
((For previous columns by the author, Reuters customers can click on BOSE/shritama.bose@thomsonreuters.com))
Recent news on State Bank Of India
See all newsIndia bank capital fail is more farce than tragedy
India bank capital fail is more farce than tragedy
State Bank of India reports cyberattack involving nearly 3,900 customer records (updated)
State Bank of India reports cyberattack involving customer records
Brief: State Bank Of India Experienced An Incident Involving The Loss Of Certain Data