Fibe, the Pune-based digital consumer lending platform backed by notable investors, plans to raise ₹750 crore through an IPO to expand its AI-powered lending operations across India, amid rapid asset growth and enhanced profitability.
Fibe, the digital consumer lending platform operated by Social Worth Technologies, is preparing to raise ₹750 crore through a fresh issue, with the money earmarked mainly for its lending subsidiary and broader corporate needs, according to draft papers cited by Business Standard and other reports. The planned fund-raise comes as the Pune-based company pushes deeper into technology-led lending and expands its presence across India through mobile and web channels.
The draft prospectus, filed with the Securities and Exchange Board of India in late June, also includes a sizeable offer for sale by existing shareholders, among them The Rise Fund III, Norwest Capital, Eight Roads Ventures India and Piramal Finance, according to Business Standard and Moneycontrol. The company intends to channel most of the fresh proceeds into EarlySalary Services, its lending arm, to strengthen capital and support onward lending, with the balance set aside for general corporate purposes.
Fibe has built its business around artificial intelligence and machine learning, and says those systems now run across customer engagement, risk assessment, credit decisions, portfolio management and staff productivity. The company’s internal tools include Fibe Mind, which gives managers live business data, and an AI engineering agent that helps development teams with tasks such as code generation, testing and deployment. According to the draft papers reported by HDFC Sky, its assets under management rose 63.31% year on year to ₹8,603 crore as of March 31, 2026, from ₹4,064 crore two years earlier.
That growth has also translated into stronger earnings. The Hindu BusinessLine reported that Fibe’s profit rose to ₹257 crore in FY26 from ₹114 crore in FY25, while its technology platform processed about 1.31 million loan applications a month and handled 15.74 million unique applicants during the year. Of those applicants, 2.02 million were approved through the company’s scorecard-based underwriting process, which uses bureau data, income estimates, behavioural signals and other checks alongside borrower-provided details such as income, residence and employment information.
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