How Hero FinCorp automated two-wheeler loan processing with Agentforce
Indian lender Hero FinCorp used Agentforce, with MuleSoft document processing, to automate two-wheeler loan processing from application to disbursal. Salesforce reports turnaround dropped from days to minutes.
The problem
Loan processing was manual and error-prone. Each application passed through two teams, six workflows and around 100 touchpoints. In peak season, including Diwali with up to 75,000 requests a day, backlogs reached 12 days.
How they did it
- Used MuleSoft Intelligent Document Processing to read application documents.
- Connected government databases for PAN and Aadhaar identity checks, plus third-party credit checks.
- Automated e-signature collection and loan disbursement through coordinated flows.
- Built and launched the first agent in about three weeks.
Results
- Salesforce reports turnaround cut from 2 days to 30 minutes, an 80% reduction.
- 35% reduction in time to action, 75% fewer handoffs and 37% fewer errors.
- 35% ROI over 3 years, as reported.
As reported by the source (Salesforce customer story); AgentGid did not measure these figures.
This suits a lender or similar team with Salesforce and MuleSoft already in place, plus integration engineers for identity and credit-check connections; the setup is advanced. Treat the turnaround and 35% ROI figures as Salesforce-reported, and note that per-action pricing (Free + $0.10/action) scales with volume. Rasa (Free) is an open-source option, though it is a support bot platform rather than a loan-processing stack.
The agent used here
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