A Custom Collections Language Model (CCLM) is a specialised AI tool designed specifically for the collections industry.
Unlike general AI models that operate across a wide range of topics, a Custom Collections Language Model is tailored to understand and interact within the specific context of debt collection.
Here’s how it works:
Industry-Specific Knowledge
The model is built with a deep understanding of the collections sector, including industry-specific terminology, compliance requirements, and customer engagement practices. This allows it to handle conversations and tasks that are unique to the collections industry more effectively than a general AI model.
Entity Recognition
The model is adept at recognising key pieces of information, such as customer identification details (e.g., date of birth, account numbers) even if they are provided in different formats. This capability ensures that the initial steps of a customer interaction are handled smoothly, reducing the chances of errors and improving customer experience.
Intent Detection
It can accurately identify what the customer wants to achieve in the conversation—whether it's making a payment, discussing a repayment plan, or something else. This allows for a more personalised and efficient conversation, addressing the customer’s needs directly.
Outcome Prediction (Propensities)
The model can predict the most likely outcomes of a conversation based on the information provided. For instance, it can detect potential customer vulnerabilities and automatically route the case to a specialised team trained to handle such situations.
Integration with Human Agents
While the AI can automate many parts of the collections process, it also works alongside human agents. It provides suggested responses to agents, helping them handle customer interactions more efficiently by reducing their cognitive load and speeding up response times.
Benefits of a Custom Collections Language Model
- Increased Automation: Automates repetitive tasks, freeing up human agents for more complex issues.
- Personalisation: Enhances customer experience by tailoring interactions to individual needs.
- Cost Efficiency: Reduces the cost per collected dollar/euro by streamlining operations.
- Improved Collection Performance: Leads to better overall performance in collecting debts.
Most Popoular FAQs
What is a Custom Collections Language Model? 
