Fibe plans ₹750 crore raise to scale lending, technology and AI

Consumer-financing fintech Fibe plans to raise ₹750 crore for its lending subsidiary and technology and AI capabilities. It reported ₹8,603 crore in AUM as of March 2026, up from ₹4,064 crore in March 2024, alongside FY26 profit of ₹257 crore.

— Source publishedTue, 1 Sept, 2026, 18:10 IST·First seen Tue, 1 Sept, 2026, 18:19 IST·Source The Hindu BusinessLine

What happened

Indian consumer-financing fintech Fibe plans to raise ₹750 crore to strengthen its lending subsidiary, technology and AI capabilities. The platform reported 45%

Key facts

  • ₹750 crore planned raise
  • 45% AUM CAGR
  • ₹8,603 crore AUM as of March 2026
  • ₹4,064 crore AUM as of March 31, 2024
  • ₹257 crore FY26 profit
  • ₹114 crore FY25 profit
  • 1.31 million monthly loan applications processed in FY26
  • ₹7,614 crore fresh disbursals in FY26
  • 15.74 million unique applicants in FY26
  • 2.02 million applicants approved

Why this matters

Fibe’s investment in lending, technology and AI could make it a more relevant partnership or strategic-option candidate for retailers, platforms and financial institutions seeking embedded consumer-credit capabilities.

What to watch

  • Final fundraise size, valuation, investor mix and timing of capital infusion into the lending subsidiary.
  • Quarterly AUM growth versus disbursement growth, indicating whether expansion is driven by repeat customers or new borrower acquisition.
  • GNPA, net credit losses, write-offs, collection efficiency and provisioning trends.
  • Changes in cost of funds, lender concentration and securitization/assignment activity.
  • Evidence of AI deployment improving approval rates, fraud losses, operating costs or collection outcomes.
  • RBI actions or consumer-protection scrutiny affecting digital lending, data use, fee disclosure or recovery practices.
  • Close the ₹750 crore fundraise with a mix of institutional equity and strategic capital.
  • Inject capital into the lending subsidiary to support larger borrowing lines and loan-book growth.
  • Expand AI use in underwriting, fraud detection, collections prioritization and customer service.
  • Pursue additional bank, NBFC, merchant and embedded-finance distribution partnerships.
  • Increase risk, compliance and data-governance investment as lending volumes scale.