AI moves deeper into banking with agentic workflows
- Indian lenders deploy agentic AI for loan origination and personalisation
- Loan decision cycles are shortening from days to hours
- 81% of financial services firms now use AI at some level
- Mahindra Finance and Sarvam handled 10 million-plus calls in 12 languages
MUMBAI, INDIA — Indian lenders are deploying agentic artificial intelligence (AI) systems capable of executing multi-step workflows, moving from chatbots toward systems that interpret borrower intent and act within agreed parameters, with loan decision cycles shortening from days to hours.
Economic Times identifies agentic AI shift in Indian banking
An Economic Times Enterprise AI report found that Indian banks are deploying AI beyond assistants into agentic systems, integrating personalisation with workflow automation to match borrowers against lender profiles and execute decisions in real time.
The Economic Times report identified loan origination and customer personalisation as the primary agentic deployment areas, with systems shifting from user-led interaction to intent-driven execution within defined risk and regulatory parameters.
A 2026 global study by Cambridge Judge Business School, the Bank for International Settlements (BIS), the International Monetary Fund (IMF), and the World Economic Forum (WEF) found that 81% of financial services firms use AI at some level, marking a shift toward production-scale agentic deployment.
Lenders apply voice AI and workflow automation at production scale
At Global Fintech Fest (GFF) 2026 in Mumbai, Mahindra Finance and Sarvam demonstrated voice AI agents handling over 10 million customer calls across 12 Indian languages for payment reminders, loan-related queries, debt collection, and cross-selling.
Gnani AI’s GFF 2026 platform featured more than 200 pre-built workflows automating loan processing, underwriting, payment reconciliation, and risk management across lending, insurance, and financial services operations.
McKinsey estimates that generative AI could generate US$200 billion to US$340 billion in annual value for global banking, with the highest returns projected in customer operations and risk modelling.
The agentic deployment pattern Economic Times identifies connects directly to the sourcing case for offshore outsourcing and business process outsourcing (BPO), where managed service models provide the human oversight, exception resolution, and cross-lingual support autonomous systems still require.
When lenders scale agentic AI across multilingual markets, top BPO companies worldwide with financial services expertise and cross-lingual delivery capability are positioned to provide the human-AI integration layer that autonomous banking operations across language markets require.
Economic Times analysis confirms that India’s banking sector has moved from AI pilots to production-scale agentic deployment, with loan origination and customer personalisation as the leading use cases.
For enterprise buyers in financial services evaluating AI transformation, the agentic deployment pattern Economic Times identifies requires multilingual human-AI integration infrastructure that standalone automation cannot replicate.
BPO operators with financial services delivery capability and multilingual operations are positioned to capture managed service mandates as lenders scale agentic AI beyond the reach of in-house automation teams.
Related news
- AI agent deployments more than doubled in a year: Salesforce · 14 Aug
- India’s agentic AI returns set to hit $14.4Mn, a 5x surge: SAP · 18 Jun
- AI strategies help banks close the fintech innovation gap · 1 May
Disclosure: Outsource Accelerator uses AI tools in the backend of its editorial workflow. Every article is reviewed and verified by a human editor before publication.
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