Best AI Calling Software for Collections in India
The best AI calling software for collections in India handles reminders and early-stage follow-up politely, in the borrower's own language, inside RBI's conduct limits, and passes anything contentious to a person. It should capture a promise to pay, not pressure anyone. Outpero publishes this guide and sells an AI voice agent, so test every vendor, including us.
Outpero sells an AI voice agent. Facts about other vendors come from their own public pages, checked on 14 October 2026, and are claims unless stated otherwise. This is general information, not legal advice. Have your compliance officer review any collections script before it goes live.
Collections is three jobs, and AI suits them unevenly
Software vendors say 'collections' as if it were one call. Lenders know it is a ladder, and the right tool depends on which rung you want to automate. Buying a product built for one rung and using it on another is the commonest mistake.
| Stage | Purpose of the call | Fit for an AI voice agent | Main risk |
|---|---|---|---|
| Pre-due reminder (3 to 7 days before) | Tell the borrower the amount and date, confirm intent to pay | Strong. Short, predictable, low emotion | Wrong amount or wrong person reached |
| Early overdue (1 to 30 days past due) | Find out why it was missed, get a promise-to-pay date | Good, with a script boundary and an easy route to a human | Tone, repeated calls, calling at the wrong hour |
| Mid and late overdue | Negotiate, restructure, resolve disputes | Weak. Needs judgement and authority | Harassment complaints, regulatory attention |
| Legal or field recovery | Notices, visits, settlements | Not suitable | Not a calling job |
Most Indian lenders get the best return from automating the first two rows, because they are high volume and low drama. A 5,000-account book has thousands of reminder calls a month that no human team enjoys making and that borrowers would often prefer to get as a polite call rather than an SMS they ignore.
What the regulator expects of the call
The Reserve Bank of India's Fair Practices Code expects lenders to communicate in a language the borrower understands, to treat borrowers with courtesy and to avoid harassment, including calls at inconvenient hours. The commonly cited window for recovery contact is 8 am to 7 pm. The lender stays responsible for what a service provider does on its behalf, and an AI calling vendor is a service provider.
Telecom rules sit alongside. TRAI's regulations cover registered calling headers, DND screening for promotional calls and consent. Reminders about an existing loan are service communication, not promotion, but the distinction is for your compliance team to confirm, not for a vendor's marketing page. Ask every vendor how it records consent, discloses that the call is automated and logs opt-outs.
Seven criteria for collections calling software
- 01Guardrails you can read. Ask for the exact script boundary: what the agent may say, what it may never say and what happens when a borrower is abusive, distressed or silent. Vague 'compliance built in' is not an answer.
- 02Calling windows enforced in the product. You should set 8 am to 7 pm, or tighter, in campaign settings, not rely on a promise.
- 03Language the borrower is comfortable in. A reminder in a language the borrower reads slowly lands as a threat. Check which languages are named, and test each with a native speaker.
- 04A live look-up of the due amount. Reading from a spreadsheet or calling your API during the call avoids quoting last week's balance.
- 05A clean route to a human. The agent should be able to transfer a call to your team when a borrower disputes, pleads hardship or asks for a person, and log why.
- 06Memory across calls. A borrower who said 'I will pay on Friday' should hear the Friday call begin there, not start over.
- 07A record you can audit. Recording, full transcript, summary, sentiment and captured fields such as promise-to-pay date, for every call, exportable to your system.
Vendors on published facts
This table covers vendors that name collections, EMI reminders or lender use on their own pages. 'Not published' means no price or language list was found on the pages checked, not that none exists.
| Vendor | Collections position (own pages) | Pricing published | Indian languages named | Where it wins |
|---|---|---|---|---|
| Skit.ai | Built for debt collection since 2019; guardrails listed for US rules (FDCPA, TCPA, Reg F, UDAAP) | No; a case study mentions performance-based pricing | None listed; 'multiple regional languages' claimed | Collections-only depth, SOC 2 Type II, 100+ enterprise customers claimed |
| Convin | Dedicated AI collections product plus EMI reminder flows; also audits human calls | No | 70+ for transcription incl. Telugu, Tamil, Kannada, Malayalam, Marathi; demo agent in English, Hindi, Hinglish | Quality audit of human collectors, on-premise option |
| Gnani.ai | Collections listed as a use case; a customer cites calling over 360,000 people | No | Nine: Hindi, Tamil, Telugu, Kannada, Malayalam, Bengali, Gujarati, Marathi, Punjabi | Bengali, Gujarati and Punjabi, private and air-gapped deployment |
| Exotel | AI agents for EMI reminders; humans can monitor and take over | AI agent pricing not published | Hindi, English, Hinglish named; others 'regional' | Full contact-centre and dialer stack |
| Ozonetel | Predictive, power and preview dialers with DND scrubbing, plus voice AI | No | 12+ claimed, not named | Large human collections floors |
| Zingaro AI | Collections among its listed uses; custom builds | No; scoped on a call | Common Indian languages, not named | Own-data model training, on-premise |
| Outpero | Reminders, early follow-up and document chase; not a case-management system | Yes: ₹5 or ₹6.8 per connected minute, no setup fee | Hindi, Telugu, Tamil, Marathi, Kannada, Malayalam, Indian English | Published price, regional-language specialism, self-serve start |
The honest reading: if you are a bank or large NBFC that needs SOC 2, private deployment, a collections workflow engine and a vendor team to run it, Skit.ai, Convin, Gnani or an Exotel or Ozonetel stack is probably the right shortlist, and Outpero is not. Skit.ai's own guardrail list is written around US collection rules, so ask it to map those controls to RBI expectations. If your book includes borrowers who need Bengali, Gujarati or Punjabi, Gnani names them and Outpero does not support them.
Want to hear this working, not just read about it?
How Outpero handles collection calls
Outpero is a pay-as-you-go AI voice agent from a specialist in regional-language voice AI. For collections it does a narrow set of jobs well. A bulk campaign calls every number on an uploaded CSV, inside calling windows, with retries, callbacks and DND screening. The agent can read the due amount from a spreadsheet or call your API during the call, send a WhatsApp message with your payment link during or after it, and transfer the call to your team when a person should take it.
Caller memory means a returning borrower is recognised and the call picks up from the last conversation. After each call you get the recording, full transcript, summary, sentiment and the custom fields you asked for, in the dashboard and at your webhook. Unanswered calls are not billed. A sample opening for a reminder to a Hindi-speaking borrower follows.
नमस्ते, मैं Kaveri Finance की तरफ़ से बात कर रहा हूँ। यह call recorded है। आपकी EMI की due date 5 तारीख़ है, और मैं बस reminder देने के लिए call कर रहा हूँ। क्या आप इस हफ़्ते payment कर पाएँगे?
Note what the line does. It names the lender, discloses the recording, states the date and asks a question the borrower can answer in one word. It does not mention the amount outstanding in a way a family member could overhear, and it contains no consequence. Those omissions are deliberate.
Language is a collections feature
A reminder lands very differently in a language the borrower thinks in. A microfinance borrower in Tumakuru, a gold-loan customer in Kochi and a two-wheeler buyer in Nashik each deserve the call in Kannada, Malayalam and Marathi, with the English words they use, such as EMI and due date, left in English. Outpero's per-minute price is the same in every language it supports, so a regional campaign costs no more than a Hindi one.
| Borrower base | Language to use | Words typically left in English |
|---|---|---|
| Hyderabad, Vijayawada, Warangal | Telugu | EMI, due date, payment link |
| Chennai, Coimbatore, Madurai | Tamil | EMI, loan, reminder |
| Pune, Nashik, Nagpur | Marathi | EMI, instalment, receipt |
| Bengaluru, Mysuru, Mangaluru | Kannada | EMI, bank, due date |
| Kochi, Thrissur, Kozhikode | Malayalam | EMI, loan, gold loan |
| Delhi NCR, Lucknow, Jaipur | Hindi | EMI, due date, payment |
Worked cost: one reminder round for 5,000 accounts
This is an illustration with stated assumptions, not a promise of results. A lender sends one reminder round to 5,000 accounts. Half of calls connect and a connected call lasts about 1.2 minutes.
| Item | Assumption or rate | Amount |
|---|---|---|
| Connected calls | 5,000 dials × 50% connect | 2,500 calls |
| Connected minutes | 2,500 × 1.2 minutes | 3,000 minutes |
| Calling charge, Standard | 3,000 × ₹5 | ₹15,000 |
| Number plus channels | 5 channels in all: one included with the number, 4 extra at ₹649 | ₹3,245 a month |
| Total before GST | ₹18,245 | |
| Total with 18% GST | ₹21,529 | |
| Time to dial everyone | 5,000 ÷ (55 dials an hour × 5 channels) | about 18 hours |
Two telecallers at the ₹18,000 reference salary cost ₹36,000 a month and would take weeks over the same list. Cost is not the main point. Coverage is: the reminder reaches every borrower before the due date, in the right language, with a record of each call. The same arithmetic with the Premium voice at ₹6.8 a minute gives ₹20,400 in calling charges for the same volume.
Run a 100-account pilot before you commit
- 01Pick 100 accounts in the pre-due or early-overdue bucket, stratified by language, and keep a matched group for your human team.
- 02Give the agent a one-page script boundary approved by compliance: remind, record a promise-to-pay date, never threaten, never discuss the debt with a third party.
- 03Set the calling window to 8 am to 7 pm or tighter and cap the number of attempts per account per week.
- 04Read every transcript for the first week. Mark each call as paid, promise, dispute, wrong person or complaint.
- 05Compare promise-to-pay rate, paid-after-reminder rate and complaints against your human-called group, and cost per rupee collected on both sides.
- 06Expand only if complaints are no higher than the human group. Add the next bucket after that.
Define the metrics before you start. Right-party contact is the share of connected calls that reached the borrower, not a relative. Promise-to-pay rate is the share of those that gave a date. Keep rate is the share of promises actually paid. No honest vendor can quote your numbers in advance, so treat any promised recovery uplift as a red flag.
Frequently asked questions
Can an AI voice agent make EMI reminder calls in India?
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Yes. Reminder calls are the strongest fit: the message is short, the answer is predictable and the borrower often prefers a polite call to an ignored SMS. The agent should state the lender's name, disclose the recording, avoid discussing the debt with third parties, and call only inside agreed hours.
What are the RBI rules on calling borrowers for collections?
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RBI's Fair Practices Code expects courtesy, a language the borrower understands and no harassment, including calls at inconvenient hours. The commonly cited window for recovery contact is 8 am to 7 pm. The lender is responsible for its service providers, so confirm the details with your compliance officer.
How much does AI collections calling cost per month?
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On Outpero, connected minutes cost ₹5 (Standard) or ₹6.8 (Premium), with no setup fee, a ₹649 monthly number including one channel, and extra channels at ₹649 each. A 5,000-account reminder round at the assumptions above is about ₹18,245 before 18% GST. Many other vendors publish no price.
Which is better for collections, a specialist platform or a general AI voice agent?
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A specialist platform suits banks and large NBFCs needing workflow engines, certifications and managed rollout. A general agent such as Outpero suits smaller lenders, DSAs and microfinance firms that want reminders and early follow-up in regional languages and a published price. Neither replaces human judgement on disputes.
Can the AI agent speak the borrower's regional language?
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Outpero speaks Hindi, Telugu, Tamil, Marathi, Kannada, Malayalam and Indian English, switching to English when the borrower does, at the same per-minute price in each. Bengali, Gujarati and Punjabi are outside its list. Gnani.ai names those on its own site, so pick a vendor that covers your borrowers.
What happens when a borrower says they cannot pay?
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The agent should not argue or pressure. It should acknowledge, record the stated reason, and either capture a new promise date or transfer the call to your team. Log hardship statements and route them to a person within a day. Outpero records every call, with transcript, summary and sentiment, so you can audit how each was handled.
The Outpero team builds AI voice agents for Indian businesses, in Hindi, Telugu, Tamil, Marathi, Kannada, Malayalam and English. Figures are from Outpero's own product unless another source is named.