The debt collections industry is moving on from phone calls and letters to the more effective multichannel digital approach using conversational text messaging, such as SMS, WhatsApp, Viber and Web Chat.
This shift is made possible by the development of conversational AI used in debt collection technology, for example, AI chatbots and virtual digital assistants. It also enables conversational messaging at scale since it is asynchronous so each agent can handle many conversations at the same time.
Once the AI chatbot has dealt with the straightforward, mundane conversations (ID&V, I&E, simple queries, etc.), customers may be routed to a live agent for a more complex task.
Since debt collection platforms are cloud-based, integrated and fully digital, customers can do many actions themselves without needing to go through an agent, for example, checking their account balance.
In order to have a complete debt collection and payments platform, API integration is used to access customer data to inform the customer conversations in real-time.
AI and machine learning are brought into play to optimise the debt collection process. This is best seen in intent recognition where the app can read the context and sentiment in a live conversation to understand what a person is actually sayong and wanting to do and make guided decisions. Entities are useful piececs of information such as dates, names and post codes that the AI can extract from unstructured text, while propensity is deciphering the most likely outcome of a conversation, e.g. a payment or a default, and then routing the conversation down the most appropriate path.
Any worthwhile debt collection platform will provide comprehensive reporting and analytics for insights into the customer journey and debt cycle.
The benefits of using a debt collection platform are multifold:
Example of a Debt Collection Platform in Action
(From webinar: How to Increase Agents' Daily Closed Conversations from 60 to 300+)