Automated debt collection is using technology to manage the collections process, and increasingly, this technology is AI-driven.

All the stages of the debt-cycle can be largely automated, which keeps operations running smoothly and with tighter controls. From reminders to final payments, automated debt collection platforms manage the customer journey workflow.  

Personalised Customer Engagement via Multiple Digital Channels 

When it comes to talking about their debt to creditors, people prefer to be contacted via their preferred digital messaging channels, like Web Chat, and opt-in messaging like SMSs and WhatsApp. They also respond better when the messages are personalised and delivered in a conversational tone.  

Natural Language Processing (NLP) and AI Chatbots 

Through NLP and Machine Learning, the software learns to understand human language and how best to respond, and these sophisticated AI chatbots can recognise entities (such as dates), context and intent, and then answer meaningfully in a two-way conversation.  

AI collections chatbots are faster, less error-prone and less expensive than using only live agents for debt collection. 

Blend Automated Chatbots with Live Collection Agents 

Although digital assistants can deal with up to 70% of customer engagement tasks, there are times when the customer needs to talk to a live agent. Automated debt collection software will route a person to an agent if needs be, or once the more straightforward tasks like ID&V are taken care of. 

API Integration for Data-Driven Conversations 

Integration allows for data-rich conversations which increases accuracy and personalisation as useful data such as account history and payment status can be accessed in real-time.

Digital Record of Conversations 

By keeping a record of all customer engagement, the debt collection software keeps companies audit-friendly. 

The Results of Automated Debt Collection Speak for Themselves

See here how automating your debt collection results in measurable upticks in agency and operational efficiency which can be seen in real figures, such as an increase of daily closed conversations to 300+ per agent.