Debt collection has traditionally relied on large telecalling teams, manual follow-ups, and repetitive outbound efforts. However, rising borrower volumes, regulatory scrutiny, and changing customer expectations have made manual collection processes increasingly inefficient and costly. Financial institutions today need scalable solutions that boost recovery confidence while maintaining compliance and customer experience.
This is where using an AI voicebot for debt collection is becoming essential. By automating high-volume borrower outreach while maintaining structured, compliant conversations, AI voicebots are helping BFSI organisations improve recovery outcomes without increasing operational risk. SquadStack’s AI voicebot is designed specifically for these real-world collection challenges. At SquadStack, we’ve built an enterprise-grade AI Voice Agent trained on real Indian telephony data- designed to improve recoveries, ensure compliance, and reduce cost per collection without compromising customer experience.
What Is an AI Voicebot for Debt Collection?
An AI voicebot for debt collection is a conversational AI platform that automates borrower interactions through voice-based communications, making contact centre collections easier to manage. In contrast to traditional IVR (interactive voice response) systems that rely on preset menu options and keypad navigation, AI voicebots enable human-like conversations with borrowers through Natural Language Understanding and Speech Recognition.
AI voicebots are tailored explicitly to address the needs of debt collection and can:
- Automatically contact borrowers to remind them of their payment obligations and assist with follow-up calls
- Receive incoming calls from borrowers who would like assistance with making a payment or have a question about their account.
- Provide information regarding outstanding balances, loan information, and options for repayment.
- Capture borrower responses, including promises to pay, disputes with the account, and requests for a follow-up call.
- Trigger actions such as sending out payment links or setting reminders.
In debt collection processes, AI voicebots serve as a primary point of contact for handling reminders, soft collection efforts, and determining intent. By handling large volumes of repetitive interactions, AI voicebots enable human representatives to focus on resolving complex negotiations and assisting borrowers with sensitive issues.
How AI Voicebots Work in Debt Collection?
To conduct structured interactions with borrowers, AI Voicebots use Natural Language Processing (NLP), Speech Recognition, and predefined Call Flows. When the AI Voicebot makes an outbound call, it listens for responses, recognises intent, adapts the conversation, while ensuring compliance with approved guidelines.
The results of the call, including willingness to pay, promised payment dates, disputes, and unreachability, are automatically tagged and synced with Collection Systems / CRMs. This feature helps the BFSI sector manage large borrower portfolios efficiently by standardising the outreach process and ensuring consistent, accurate borrower data.
The following demonstrates how AI Voicebots operate in the Actual Collections Process:
1. Data and Systems Integration
AI Voicebots fully integrate with Loan management systems, CRMs, and Payment Gateways, providing access to live/real-time borrower data, including Loan Type, amount due, due date, and delinquency classification.
2. Intelligent Schedule Creation for Calls
AI Voicebots auto-schedule outbound calls using business triggers such as Pre-due Date, Missed Payments, or delinquent payments tracking, ensuring correct scheduling to avoid regulatory violations (compliance) while maximising the number of borrowers reached.
3. Natural Human-Like Conversations
Using voice transcription, natural language processing (NLP), and text messaging software, the voicebot can listen to and respond to a borrower's voice in a natural-sounding way. This gives the impression that they are having a natural conversation with the borrower rather than acting like a robot.
4. Intent Recognition & Decisioning
The Voicebot recognises borrower intent, such as agreeing to pay, requesting an extension, reporting hardship, or disputing a bill. It will then use the pre-defined decision trees to provide the appropriate response to the borrower.
5. Smart Actions & Escalation
Based on the outcome of the conversation, the Voicebot can text or message payment links (via SMS or WhatsApp), schedule follow-ups, or transfer the call to a human representative to assist the borrower.
6. Compliance Logging & Analytics
Every interaction with a voicebot is logged with a complete audit trail, including the call time, outcome, recording, and the ability to analyse calls for performance evaluation.
The Need for AI Automation in Debt Collection
Debt collection in India is under growing pressure as contact centres for banks, NBFCs, and fintech lenders handle millions of conversations each month. Manual and agent-led debt recovery processes are no longer scalable, leading to low contact rates, delayed follow-ups, rising costs, and compliance challenges. By partnering with an AI-powered debt collection agency in India, such as SquadStack, organisations can improve recovery rates and ensure consistent borrower engagement across languages and regions of India. Below are the top reasons why AI voice bots are essential for debt collection operations in Indian banks.
High Customer Volume and Limited Agent Capacity
Lenders often manage millions of borrower accounts across different stages of the debt collection funnel. Human agents can make only a limited number of calls per day, resulting in delayed or missed follow-ups. AI voicebots for scale effortlessly, ensuring consistent outreach across the entire portfolio. Banks, NBFCs, and fintech lenders often manage collections for thousands or even millions of borrowers. Manual calling teams struggle to keep pace with this scale, leading to delayed outreach and missed recovery opportunities. AI voicebots help address this gap by handling high call volumes simultaneously.
Compliance Risks in Manual Processes
Debt collection regulations mandate strict rules around call timing, frequency, language, and consent. Manual calling increases the risk of non-compliance due to human error. AI voicebots operate on predefined, policy-driven scripts, significantly reducing compliance risks. Debt collection is a regulated activity where tone, timing, and phrasing matter. Manual agents can unintentionally deviate from approved scripts, increasing compliance risk. AI voicebots operate on predefined, policy-aligned call flows, reducing the chances of violations.
Demand for Faster, More Efficient Payment Communication
Borrowers expect timely reminders, clear payment instructions, and quick resolution of queries. AI voicebots deliver instant, accurate responses and enable faster payment actions, reducing delinquency cycles.
Rising Opex and Operational Inefficiencies
Hiring, training, and managing a large collection team increases operational expenses. AI voicebots reduce cost per contact, improve agent productivity, and deliver higher ROI by automating repetitive tasks. Maintaining large call-centre teams significantly increases operational expenses. AI voicebots reduce cost per contact and help organisations scale collections without proportional increases in headcount.
SquadStack’s AI Voicebot for Debt Collection in Indian Languages
AI Voicebot from SquadStack maximises operational efficiency through a dedicated, customised solution for high-volume debt collections across several compliance-sensitive districts. SquadStack AI voicebot for debt collection is trained on 10 million hours of real customer interactions. The AI Voicebot uses technology and extensive domain knowledge to deliver maximum value to operators and borrowers alike.
Multilingual, Compliant Communication across Borrowers
By supporting 10 vernacular languages, SquadStack's debt collection service reaches borrowers across a broad range of demographics while ensuring compliance with applicable lending laws and regulations. India is home to millions of borrowers from various linguistic backgrounds.
The AI Voicebot for debt collection by SquadStack allows operators and borrowers to communicate in English, Hindi, Hinglish, and a host of regional dialects. The AI Voicebot's ability to proceduralize conversations and deliver instructional messages through dynamic language switching is particularly advantageous for Tier 2 and Tier 3 borrowers while upholding compliance standards.
Human-Like Conversations That Improve Recovery Rates
For borrowers to establish trust with a voicebot, they must have conversational exchanges with contextual awareness and an empathetic flow. SquadStack's AI Voicebot can replicate the conversational exchanges of thousands of borrowers, drawing on experience from hundreds of millions of minutes of real customer/sales dialogues. Consequently, the voicebot recognises natural pauses in conversation, accent variations based on geographic origin, and language mixing when communicating with borrowers. This enables more human-like interactions and increases borrowers' willingness to cooperate during repayment discussions.
Smart Follow-Ups, Escalations, and AI-to-Human Handoffs
SquadStack's AI Voicebot intelligently determines follow-up needs and schedules the most appropriate time based on the borrower's level of intent. The AI Voicebot is programmed to identify high-intent borrowers and can skillfully escalate complex and sensitive matters to qualified human agents.
Secure, Policy-Driven Collections with Full Audit Trails
Each interaction is logged & recorded securely, providing complete transparency, simple auditing, and full compliance with both government and internal regulations governing collections. Every interaction is completed using an approved call flow & monitored continuously through AI and Human supervisors. Each call has a detailed call log, with outcomes tagged in compliance with current BFSI regulations.
Use Cases: How Businesses Use SquadStack’s AI Voicebot for Debt Collection
An AI voicebot for debt collection is most effective when it is applied to clearly defined stages of the recovery journey. Rather than replacing human collectors entirely, businesses use SquadStack’s AI voicebot to handle high-volume, repetitive, and time-sensitive interactions- freeing human teams to focus on complex or high-risk cases. Below are the most common and practical ways organisations deploy SquadStack’s AI voicebot in debt collection workflows.
Early-Stage Overdue Payment Reminders
One of the primary use cases for SquadStack’s AI voicebot is early-stage collections, where timely reminders can prevent accounts from slipping further into delinquency. The voicebot reaches customers shortly after a missed payment, clearly explains the overdue status, and communicates repayment options in a calm, non-confrontational tone.
Multilingual conversations help improve response rates, especially in Tier 2 and Tier 3 regions, where customers are more comfortable engaging in their preferred language. Early outreach through AI-led calling helps increase recoveries while reducing the need for escalations. Banks and NBFCs use SquadStack’s AI voicebot to contact customers shortly after a missed EMI or credit card payment. These early reminders inform customers of the outstanding balance, the due date, and available payment channels.
BFSI examples:
- Retail banks are sending EMI reminders for personal loans and auto loans
- NBFCs handling early delinquency in consumer durable financing
- Credit card issuers are reminding customers about minimum due payments
Multilingual outreach improves engagement, especially among customers in Tier 2 and Tier 3 regions.
High-Volume Soft Collections at Scale
For lenders and financial institutions managing large portfolios, manual soft collections can become operationally expensive. SquadStack’s AI voicebot is used to conduct large-scale soft collection campaigns, reaching lakhs of customers per week without increasing manpower.
The system automatically handles call scheduling, retries, and follow-ups, ensuring consistent outreach while adhering to frequency and compliance guidelines. This allows businesses to maintain steady recovery efforts even during peak periods.
BFSI examples:
1. MoneyView: Digital lenders like MoneyView demonstrate how AI-powered voice engagement can deliver high connectivity while maintaining strict data security- critical for modern debt collection operations.
Segment: Digital Lending / Fintech
SquadStack's Metrics:
- 89% connectivity
- 40% more loan applications
- Secure, compliant outreach at scale.
2. Kissht: Consumer lending platforms such as Kissht show how AI voice automation can scale borrower communication across the loan lifecycle, including repayment reminders and collections.
Segment: Consumer Lending / BNPL
SquadStack’s Metrics:
- 82% conversion boost
- 50% CAC reduction
- High-scale loan disbursals
3. Choice India: BFSI firms like Choice India leverage AI-driven calling to maintain high customer reach while controlling costs- an approach equally valuable in debt collection workflows.
Segment: Brokerage & Financial Services - SquadStack’s Metrics:
- 72% connectivity
- 70% CAC reduction
4. Upstox: At scale, platforms like Upstox rely on AI-led voice engagement to handle millions of customer interactions reliably- making the same infrastructure effective for collections use cases.
Segment: Brokerage / Fintech
SquadStack’s Highlights:
- 2 Cr+ leads processed
- 75% connectivity
- 119+ campaigns
Payment Intent Identification and Segmentation
Another key use case is identifying customer intent during debt collection calls. SquadStack’s AI voicebot is trained to recognise signals such as willingness to pay, requests for extensions, disputes, or inability to pay.
Based on the conversation, the system automatically tags outcomes and segments customers into relevant categories. High-intent or sensitive cases can then be routed to human agents, while low-risk cases continue to be managed through automated follow-ups.
BFSI examples:
- Identifying borrowers willing to pay immediately versus those requesting extensions
- Flagging disputed cases in personal or business loans
- Separating unreachable accounts for alternate recovery strategies
This allows collection teams to focus their efforts on high-priority accounts.
Multilingual Outreach for Improved Engagement
India’s linguistic diversity poses a significant challenge for collections. Businesses use SquadStack’s AI voicebot to conduct debt collection calls in multiple Indian languages, including English, Hindi, Hinglish, and regional languages.
The voicebot can adapt mid-conversation if the customer switches languages, reducing friction and improving cooperation. Language familiarity often leads to better engagement, higher pickup rates, and smoother repayment discussions.
BFSI examples:
- Regional NBFCs collecting EMIs in local languages
- Microfinance institutions engaging borrowers in native dialects
- Fintech platforms operating across multiple states
Familiarity with the language reduces resistance and increases cooperation during repayment discussions.
Automated Follow-Ups and Callback Management
Regular follow-ups are an essential aspect of debt collection. Because of their manual nature, however, follow-up systems often do not provide timely callbacks. SquadStack’s AI voicebot automates callback scheduling based on customer-reported interests, ensuring the callback occurs when the customer wants it without repeatedly contacting them. This method will enable sustained persistence while providing an enjoyable experience for customers and adhering to contact standards.
BFSI examples:
- Scheduling callbacks after salary credit dates
- Following up on promised payments without agent intervention
- Managing retries for unreachable borrowers
This structured follow-up process improves recovery rates without over-contacting customers.
Pre-Escalation and Data Validation Before Human Handoff
To minimise the time human collectors and legal teams spend on unproductive phone calls, a business can use AI voicebot technology to verify customer details, confirm their current payment intentions, and record their location information before escalating any accounts. This helps ensure that the existing account information, when escalated to either type of company representative, is as accurate and relevant as possible.
BFSI examples:
- Banks validating customer availability before assigning field collectors
- NBFCs reconfirming repayment intent before escalation
- Fintech lenders updating borrower status in loan management systems
This reduces wasted effort and improves the efficiency of escalated collections.
Cost-Efficient Collections Operations
By handling first-level outreach and qualification, SquadStack’s AI voicebot significantly reduces the operational cost of debt collection. Organisations have reported 45–70% cost reductions compared to fully manual calling setups.
The AI voicebot enables teams to manage larger portfolios without proportional increases in staffing or infrastructure.
BFSI examples:
- NBFCs are reducing the cost per successful contact
- Digital lenders scaling collections without increasing headcount
- Credit card issuers are optimising outbound calling budgets
Organisations have reported 45–70% lower operational costs compared to manual calling models.
Quality-Controlled and Compliant Outreach
Debt collection calls require a consistent tone and compliance. SquadStack’s AI voicebot conversations are continuously monitored using AI-led and human quality checks to ensure accuracy, clarity, and adherence to approved call flows.
This makes it easier for businesses to scale their collections while maintaining compliance and customer experience.
BFSI examples:
- Ensuring compliant language in regulated collection calls
- Maintaining a consistent tone across languages and regions
- Auditing conversations for accuracy and intent capture
This allows BFSI teams to scale collections while maintaining regulatory control.
During peak campaigns, businesses have used SquadStack to reach 15 lakh+ customers in a single week, while maintaining consistent quality and compliance. Organisations have also reported 45–70% reductions in operational costs compared to manual calling models.
Conclusion
AI voicebots are transforming debt collection by making it scalable, compliant, and borrower-friendly. For lenders and collection agencies aiming to improve recovery rates while controlling costs, an AI voicebot for debt collection is no longer optional- it is essential.
SquadStack’s AI Voicebot empowers businesses to automate outreach intelligently, ensure regulatory compliance, and deliver superior borrower experiences- driving faster, more sustainable recoveries. It combines real conversational intelligence, compliance-ready workflows, and large-scale operational reliability, making it a practical solution for modern debt collection in India.
