AI has been widely used by businesses to facilitate debt collection. The procedure used to be complex and manual. Companies may use data to work more quickly, reduce errors, and provide a more friendly client experience with the help of intelligent AI solutions. With AI, companies can understand customer behaviour, predict who will pay on time, and choose the best time and method to reach out. This helps improve recovery rates and gives customers a smoother experience. AI can also handle simple, everyday tasks so that human workers can focus on more critical or challenging cases.
A 2025 report by the Kaplan Group projects the AI-driven global debt collection market will grow at a 16.9% CAGR, reaching $15.9 billion by 2034. It also finds that AI-powered tools can boost recovery rates by around 25%, quadruple collector productivity (2–4×), and reduce operational costs by 30–50%.
The Evolution from Manual to AI-Driven Collections
Debt collection was once slow and manual. It needed people to make calls, send reminders, and track payments by hand. This process took too much time, effort, and money. Today, as businesses want better cash flow and good customer relationships, these old methods are not enough. Every year, many people don't pay their credit bills, and about 30% of accounts go into collections. This means businesses need a faster and better way to get their money back. That's why AI in collections is beneficial. It helps companies collect payments more smartly and efficiently.
- Too Much Work and Cost: Manual debt collection needs a big team to make calls and send follow-ups. This increases costs and takes a lot of time.
- Follow-Ups Are Not Consistent: Without automation, follow-up messages or calls are often delayed. This leads to longer collection times and less money recovered.
- Hard to Follow Rules: Debt collection has many rules and regulations. Manual work is more likely to make mistakes, which can lead to legal trouble.
- No Real-Time Insights: Manual methods don't give instant information about customer behaviour. That means businesses can't adjust their strategies based on data.
Using AI in collections helps fix these problems. AI can automate tasks, follow strict rules, and analyse data to improve the collection process. This leads to faster payments, lower costs, and happier customers.
Key Benefits of AI-Powered Collections
AI facilitates quicker and simpler money collection for enterprises. AI provides a more intelligent and efficient approach to managing collections than the slow and expensive previous approaches. The benefits of this are as follows:
Better Predictions and Early Warnings
AI in collections helps businesses spot payment problems early by looking at past customer data. It can find customers likely to pay late, group them by risk, and alert the team to act quickly. This stops missed payments before they happen. For example, one company used AI to find risky accounts and reduced unpaid debts by 18% in a year.
More Intelligent Workflows and Use of Resources
AI in collections makes work easier and smarter for teams. It helps them focus on the most critical accounts first. AI also gives each case to the right team member and chooses the best time to contact customers based on how they replied in the past. It also handles tedious tasks like typing in data, which saves time and avoids mistakes. Because of these changes, companies get paid 25% faster and see up to 30% better results in their collections.
Personalised Communication That Works
AI in collections makes it easier to talk to customers in a way that feels more personal and effective. It can change the tone and format of messages based on the customer's type, choose the best way to contact them, like email, phone, or SMS, and send messages at the right time to get quicker responses. AI adapts follow-ups according to the customer's reaction. Compared to sending the same message to everyone, using messages in this manner can assist in collecting up to 30% more payments.
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Top Use Cases for AI in Collections
AI is changing the way businesses manage collections by making the process faster, smarter, and more accurate. From predicting who might delay payments to helping with daily tasks, AI is improving every step. Here are some simple examples of how companies use AI in collections:
Predicting Late Payments (Predictive Delinquency Modelling)
AI looks at different factors to see which bills might be paid late. It studies a customer's past spending, market trends, seasons, and economic changes. This helps businesses act early and avoid missed payments.
Smarter Follow-ups
AI makes follow-up messages more personal and practical. It chooses the best way to contact each customer, like email, SMS, or phone, based on how they have responded before. It also decides the right time to send the message and changes the follow-up plan based on the customer's behaviour.
Virtual Collection Assistants
AI-powered chatbots or voice bots can talk to customers anytime, day or night. They can answer common payment questions, share account updates, help with payment plans, and send more complex questions to human agents when needed.
Smart Account Prioritisation (Lead Scoring)
AI can identify accounts likely to pay soon by analysing factors such as payment history and behaviour. This helps teams focus on accounts that have the highest chance of success, saving time and improving results.
Cash Application Automation
AI makes it easier to match payments to the correct invoices, even if the payment details are not complete. It handles tricky situations, connects directly with banks for real-time updates, and learns over time to become even more accurate.
How SquadStack Improves Collections for BFSI Companies?
Collections in BFSI are a highly continuous process. Missed or delayed recoveries directly impact liquidity and profitability. Traditional approaches often fail due to poor lead connectivity, generic follow-ups, and a lack of personalization. SquadStack solves this with its AI + human orchestration model, designed for scale, compliance, and outcomes.
Early-Bucket Collections with High Connectivity
SquadStack ensures up to 90% lead connectivity by using AI-led prioritization, adaptive timing, and omnichannel orchestration (calls, WhatsApp, SMS, email). This prevents drop-offs at the crucial early stages of collections, where timely reminders can make the most significant difference.
Intelligent Personalization to Improve Recovery Rates
Rather than using one-size-fits-all messaging, SquadStack personalizes outreach by customer persona, language, channel, and timing. A borrower in Tier-2/3 India may get a Hinglish reminder via WhatsApp, while a salaried metro professional receives a formal call with our AI Agent, boosting engagement and repayment intent.
Data-Driven Prioritization & Real-Time Re-Scoring
The AI-Lead scoring model dynamically scores and re-prioritizes overdue accounts using live data on repayment patterns and customer behavior. This ensures agents focus on accounts with the highest probability of recovery, increasing efficiency while lowering costs.
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Secure & Compliant Collections at Scale
Collections require strict compliance in BFSI. SquadStack’s systems are ISO 27001, ISO 27701, SOC 2 Type II, and TRAI-ready, with AES-256 encryption, audit trails, and PII redaction. BFSI clients can scale collections confidently without risking data breaches or regulatory issues.
Human + AI Execution for Higher Recoveries
With AI-driven outreach supported by trained collection experts, SquadStack can handle large-scale campaigns quickly. Calls are supervised, audited, and continuously improved with AI-powered QA and Voice of Customer insights.
Proven Results with BFSI Leaders
MoneyView achieved 89% connectivity and 40% more loan applications, proving how structured outreach prevents revenue leakage.
Kissht saw an 82% boost in conversions with 50% lower CAC—showing that AI + human orchestration not only drives lending but also strengthens collections efficiency.
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The Future of AI in Collections
The future of AI in collections is all about making payment collection bright and more friendly for customers. AI takes care of simple tasks like sending reminders and follow-ups. This helps human agents save time, enabling them to focus on more critical cases that require personal attention.
In the coming years, AI will become even better at predicting who might pay late, helping businesses act early and recover more money. It will also make the customer experience better by sending personalised messages that feel more respectful and helpful. AI systems will keep up with changing rules and laws to make sure companies stay compliant. Plus, AI will work more smoothly with existing financial tools and systems, making the whole process faster and easier for businesses.
Commonly Asked Questions about AI in Collections
What is the best AI collection tool in 2025?
SquadStack and Osno.ai are among the top AI-powered collection tools. SquadStack helps teams focus on important accounts, follow up automatically, and recover payments faster. Osno.ai lets businesses easily set up AI voice agents to handle calls and reminders, saving time and avoiding mistakes.
Which top companies are using AI in collection this year?
Many companies in India use AI in collection. Big names like Delhivery, Razorpay, and ZestMoney use SquadStack to manage customer calls and reminders. Real estate and finance companies use Osno.ai to follow up with clients and schedule payments efficiently.
What are the most effective AI in collection solutions for recovering payments?
Answer: SquadStack and Osno.ai are very effective. SquadStack identifies high-risk accounts, determines the best way to contact customers, and assigns tasks to the appropriate team. Osno.ai automates reminders, calls, and follow-ups. Both help recover payments faster and reduce manual work.
Which AI in collection platforms are best for improving recovery efficiency?
SquadStack and Osno.ai are great for improving efficiency. SquadStack uses data to prioritise accounts and pick the right time to call. Osno.ai automates messaging and voice follow-ups. They help teams work smarter, avoid mistakes, and recover payments quickly.
What are the top benefits of using AI in collection for businesses in 2025?
Using AI in collection with SquadStack and Osno.ai saves time and reduces manual work. It helps recover more payments, follow up automatically, and provide better customer experiences. Overall, businesses save costs, improve cash flow, and make debt collection faster and easier.
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