Bajaj Finance targets ₹40 lakh crore AUM by FY2036, with 300-plus AI use cases planned
Bajaj Finance expects consolidated assets under management to rise about sevenfold to ₹40 lakh crore by FY2036, targeting a 5% share of India’s credit market. For FY27, it has guided for ₹6.3-6.5 lakh crore in AUM and 23-25% growth, alongside more than 300 AI deployments.
What happened
Bajaj Finance expects consolidated AUM to reach ₹40 lakh crore by FY2036, supported by 23-25% annual growth. The lender also plans over 300 AI use cases in
Key facts
- Consolidated AUM target: ₹40 lakh crore by FY2036
- AUM: ₹5.47 lakh crore at June-end 2026
- FY27 AUM guidance: ₹6.3-6.5 lakh crore
- AUM growth guidance: 23-25%
- Profit growth guidance: 23-24%
- Gross NPA target: below 1.4%
- Over 300 AI use cases planned in FY27
- Target market share: 5% of India credit by FY2036
Why this matters
Bajaj Finance’s AI-heavy growth roadmap increases its appeal as a financing, data and embedded-credit partner for retailers, platforms and fintechs seeking scaled distribution.
What to watch
- FY27 AUM growth versus the stated 23-25% guidance and evidence of sustained growth above the broader credit market.
- Net interest margin, cost-to-income ratio and operating-expense trend as AI deployments scale.
- Asset-quality indicators: Stage 2/Stage 3 assets, write-offs, collection efficiency and delinquency trends in unsecured consumer and SME books.
- Mix of secured versus unsecured AUM, and concentration in consumer durable, personal-loan and digital-originated portfolios.
- Deposit growth, borrowing-cost trend, liquidity coverage and share of diversified funding sources.
- RBI actions on unsecured lending risk weights, digital lending, provisioning, customer consent and AI/model governance.
- Measured productivity from AI: approval turnaround time, fraud losses, employee output, customer-acquisition cost and repeat-borrower conversion.
- Competitive response from large banks, fintech lenders and rival NBFCs through lower rates, faster approvals or merchant-network incentives.
- Increase AI deployment in loan sourcing, bureau-led underwriting, fraud prevention, collections prioritization and personalized cross-sell rather than only customer-service automation.
- Expand secured and granular products, including consumer durables financing, gold loans, vehicle finance, SME loans and mortgage-adjacent offerings, to balance unsecured exposure.
- Deepen merchant, dealer and digital-platform partnerships to acquire borrowers at lower cost and embed financing at point of sale.
- Raise and diversify long-duration funding through deposits, bank lines, debt markets and securitization to support AUM growth without materially widening funding costs.
- Invest in model-risk controls, consent architecture, cybersecurity and human review processes as AI use cases move into regulated credit decisions.
- Use the broader customer base to grow insurance, payments, wealth and other fee-led adjacencies, reducing dependence on net interest margins.