Insights inspired by the Singapore FinTech Festival
Our partner and Sales Consulting Director, Ádám Kocsis, recently attended the Singapore FinTech Festival, where he had the opportunity both to immerse himself in the latest trends reshaping the financial services sector – notably AI-driven innovation – and to meet some of our valued clients who rely on our end-to-end credit management business solutions.
In ways ranging from ground-breaking presentations to impactful discussions, the event showcased how emerging technologies are enabling banks to approach complex challenges, such as debt collection, in smarter and more customer-centric ways.
Moreover, hearing directly from satisfied clients about how our technology is enhancing operational efficiency and customer satisfaction was not only rewarding, but also inspiring. It reminded us of the unique role that these innovative technologies play in creating seamless, customer-first debt collection processes.
This experience, which resonated with Loxon’s approach to AI-driven solutions and the many related use cases we see among our clients in real life, inspired us to take a closer look at how large language models are used to transform the future of client interaction and communication in the debt collection in banking industry.
In this article – which mostly focuses on chatbot and voice bot support – we’ll explore how AI agents and RAG (Retrieval-Augmented Generation) technology are evolving to support a more efficient, personalised, and customer-first approach to debt collection, fully aligned with our commitment to human-centric business solutions.
Types of chatbots and voice bots in modern debt collection
Chatbots have come a long way from basic rule-based systems to today’s hybrid, AI-enhanced models, where they provide increasingly effective support to customer service in debt collection. Let’s look at the main types of bots currently in use:
- Rule-based bots: These early-stage chatbots operate on pre-defined scripts, ideal for handling common, straightforward interactions based on set rules. They’re generally limited to “if-then” scenarios, where specific keywords trigger a set response. However, when combined with human support, rule-based bots offer a basic level of assistance before escalating complex issues to human agents. These bots evolved to include Natural Language Processing (NLP) capabilities, allowing them to handle more nuanced conversations, interpret customer intent, and interact in a more conversational way.
- Generative AI-supported bots: Generative AI chatbots mark a significant advancement by not relying solely on scripted responses. Powered by large language models like GPT, these chatbots can generate real-time responses based on context, customer history, and vast datasets. In debt collection, this means they can offer customised guidance, adapt to individual customer scenarios, and even maintain empathetic, contextually aware conversations.
- Hybrid bots: A popular choice in complex customer service environments, hybrid bots combine rule-based functions with generative AI. In these setups, the chatbot begins with rule-based interactions for standard questions but automatically escalates to an AI agent when the customer’s query goes beyond programmed rules. In debt collection, this is especially valuable: routine questions or requests can be handled quickly and efficiently, while nuanced cases that require contextual understanding or judgment can be addressed by AI. Hybrid bots bridge the gap, ensuring both efficiency and a high level of support.
Each type of bots has strengths, but the trend points toward hybrid solutions and generative AI as the ideal models for today’s customer-focused and flexible debt collection strategies.
AI agents and RAG Technology in debt collection
AI agents represent the next frontier in automated customer service, particularly in complex environments like debt collection. Unlike traditional chatbots, which rely on pre-defined scripts or rules, AI agents are provided with a comprehensive toolset, including access to large datasets and advanced processing capabilities, to handle more intricate customer interactions. In the context of debt collection, AI agents are equipped with several essential capabilities, including RAG (Retrieval-Augmented Generation) technology, which allows them to not only generate responses based on predefined data but also retrieve information from relevant sources to provide highly personalized, context-aware interactions.
This enhances the AI agent’s ability to access a vast repository of knowledge – such as client delinquency data, historical transaction records, and even legal regulations – during a conversation. By combining retrieval-based techniques with generative AI, the agent can pull relevant, client related information in real-time, ensuring that responses are not only accurate but highly relevant to the customer’s situation. For example, if a customer requests details about their missed payments AI agent can retrieve specific data, such as the overdue amounts, payment history, and relevant account statuses, and provide an informed response.
One of the key advantages of AI agents in debt collection is their real-time access to client delinquency data. With this access, AI agents can evaluate customer behaviour, access their payment history, and even anticipate the likelihood of repayment. Coupled with knowledge of predefined rules, AI agents can tailor conversations to ensure that communication remains professional, transparent, and compliant with all necessary regulations. This combination of client-specific data and legal knowledge enables AI agents to act with empathy and professionalism, ensuring both operational efficiency, higher recovery rates and customer satisfaction.
Use case: AI agents with RAG Technology in personalised Promise-to-Pay (PTP) in debt collection
In debt collection, AI agents with RAG technology are transforming the process of negotiating Promise to Pay (PTP) agreements. These agents are able to pull relevant client data and external sources in real time, offering hyper-personalised payment plans that are tailored to each customer’s specific financial situation.
Personalised PTPs vs. standard approaches: Traditional debt collection often relies on standard PTP proposals, which can be less effective as they don’t account for the diverse circumstances of each customer. AI agents with access to relevant data sources can personalise the payment terms by analysing individual factors such as income, outstanding debt and prior payment behaviour, and integrating it with external legal or financial regulations the AI can calculate an optimal repayment plan. This enables the AI to suggest more tailored payment plans that are more likely to be accepted, improving the chances of successful repayment.
In summary, AI agents which have access to relevant external sources offer a more intelligent, data-driven approach to PTP agreements, delivering personalised, context-aware solutions that improve customer engagement and enhance debt recovery.
Conclusion and Summary
AI agents enhanced with RAG technology are transforming debt collection by improving efficiency and customer satisfaction through automation and personalisation. The key benefits include:
- Standardised yet personalised responses: AI agents deliver consistent responses tailored to individual customer data, enhancing engagement and increasing successful debt recovery rates.
- Cost and workforce efficiency: These solutions minimise reliance on human agents, reducing training costs and providing scalable, reliable support.
- Full control over client interactions: Businesses maintain control over rules and responses, ensuring compliance with policies and regulations.
In summary, as banks and financial institutions continue to embrace these technologies, the future of debt collection looks smarter, more streamlined, and more customer-centric than ever before.
If you’re interested in discovering how integrating AI into debt collection can improve recovery rates and enhance the customer experience, stay tuned as we continue to explore innovations transforming financial services.
If you prefer, schedule a session with our expert who can provide in-depth insights with a live demo.