A borrower misses an EMI, receives an automated call and is asked to make the payment. But what if the borrower wants to explain why the payment is delayed, understand the available repayment options or ask a question in a regional language?
This is where Voice AI could change how lenders interact with borrowers.
Moving beyond pre-recorded messages and scripted payment reminders, conversational AI systems are being developed to understand queries, interpret responses and guide borrowers through different stages of the lending process.
In India, where borrowers often switch between Hindi, English and regional languages within the same conversation, the technology could make financial interactions more accessible. However, understanding the language is only one part of the challenge. Systems also need to interpret the context, protect borrower information and know when a human representative should take over.
Here are five things to know about the emerging role of Voice AI in lending.
It can do more than make EMI reminder calls
Voice AI could be used across several stages of the lending lifecycle, including customer onboarding, loan servicing, repayment queries and collections.
During loan onboarding, conversational systems could ask borrowers follow-up questions about their income patterns and existing financial obligations. During collections, they could attempt to understand why an EMI has been missed, respond to repayment-related queries and provide information about options permitted by the lender.
Gautam Rege, Co-founder and Director of Josh Software, a software development and IT services company, said conversational AI could also help borrowers understand how changes in loan tenure may affect their monthly repayment obligations. Such interactions would depend on the lender’s systems and the options available to the borrower.
Understanding borrower intent is as important as recognising language
A borrower saying ‘I will pay next week’ could be making a genuine repayment commitment or simply trying to end the conversation. Similarly, someone explaining financial difficulties may be seeking an extension, information about delayed payments or an alternative repayment schedule.
Rohit Arora, CEO and Co-Founder of Biz2Credit and Biz2X, a pair of connected fintech platforms that specialise in small-to-medium-sized business (SMB) lending and digital credit infrastructure, said Voice AI needs to recognise cues such as hesitation, stress and urgency instead of merely processing words and following a predefined script.
Anand Agrawal, Co-founder of Credgenics, Prix AI and FixMyScore, said the technology would need multilingual capabilities, contextual intelligence and the ability to understand changes in borrower intent during a conversation.
Lenders need to measure outcomes, not just automated calls
The number of calls handled by AI may indicate the extent of automation, but it does not necessarily establish whether collections have improved.
Kumar Abhishek, Founder and CEO of ToneTag, a deep-tech Indian financial technology company, said lenders should assess repayment rates, promise-to-payment conversions, query resolution and the cost of collections while evaluating conversational AI.
Santanu Agarwal, Deputy Managing Director of Paisalo Digital, a RBI-registered, non-deposit-taking NBFC, said other parameters should include sustainable recovery rates, borrower satisfaction and complaint levels.
For lenders, relevant indicators could include:
- Repayment completion and successful recovery rates.
- Promise-to-payment conversion rates.
- Resolution of borrower queries without repeated follow-ups.
- Cost per successful collection or resolved interaction.
- Borrower satisfaction and complaints.
Multilingual conversations can create accuracy challenges
Voice AI could help borrowers who are less comfortable using app-based interfaces or communicating in English. However, India’s linguistic diversity also makes it challenging for automated systems to interpret different accents, dialects, regional expressions and conversations involving multiple languages.
Abhishek said customised multilingual models and integration with lending systems could help address these challenges. ToneTag, for instance, uses its eKosha voice-first banking platform, which processes a significant part of the workload on-device to support customised multilingual models.
However, recognising a borrower’s language does not automatically mean that the system understands their financial circumstances. Lenders would still need to verify account information and ensure that repayment-related responses are consistent with their policies.
Human intervention, consent and data protection remain important
A borrower discussing financial stress or an inability to repay may require assistance that an automated system cannot adequately provide.
Arora said borrowers should be informed when they are speaking to an AI system and should have the option of reaching a human representative.
Rege also highlighted the need for borrower authentication, consent, auditable interactions and human intervention when the system cannot confidently interpret a request.
Agarwal and Agarwal said responsible implementation would also require attention to data privacy, regulatory compliance and the dignity of borrowers during collection interactions.
What should borrowers keep in mind?
As lenders explore conversational AI, borrowers should check a few things during such interactions:
- Know whether you are speaking to AI: The lender should make it clear when an interaction is handled by an automated system.
- Ask for human assistance: If the system does not understand your query or you are discussing a complicated repayment issue, seek assistance from a human representative.
- Verify repayment information: Check any repayment amount, schedule or alternative communicated during the call against the lender’s official channels.
- Be careful with personal information: Do not share passwords, OTPs, PINs or other confidential credentials during an automated call.
- Understand repayment options: An AI-generated response should not be treated as confirmation of a loan restructuring, extension or change in repayment terms unless the lender formally approves it.