Most businesses aren’t thinking about if they’re going to use AI to communicate with consumers, but how they can put the technology in action. For companies in highly regulated industries like debt collection, it’s essential for AI to consumer conversations to be compliant and operate under responsible engagement.
To make this notion a reality, there are four key pillars businesses should follow to implement AI for consumer communications ethically and responsibly.
Pillar 1 – Building a Proper AI Data Integrity Foundation
For top musicians and athletes, an amazing performance is the product of countless hours of practice. In the world of AI, that grounding all happens in the foundational data layer. The best AI foundations are set up to prevent hallucinations (cases where AI models make-up facts) and limit the number of context gaps the technology fills in.
The first step to achieve this is the idea of “treasures In, treasures out”. This means setting up a highly structured and vetted knowledge base for AI tools to pull from. One of the best ways to put this into practice is with a RAG (Retrieval-Augmented Generation). Think of RAG as an open book test. Instead of the AI guessing at the answer for a certain situation, there’s a verified source of truth from your business that it can rely on to formulate its real-time response with consumers. Other key aspects of reliable foundation include:
- Knowledge Base Curation: Build a single source of truth for your compliance data.
- Structured Templates: Create response templates for sensitive consumer interactions.
- Vetted & Restricted Terminology: Maintain a list of approved industry terms and any banned language.
Pillar 2 – Designing the Right Omnichannel Blueprint
After the AI is trained, your communication strategy needs a playbook to follow, using both AI and human agents, for effective communication with consumers. This way, organizing email, text and phone call conversations is done in accordance with your omnichannel strategy. It’s important for AI tools to have clear paths to be highly efficient, while always displaying the empathy consumers expect from businesses. To help with this goal, it’s important to never let an AI operate in a silo, there needs to be human oversight.
Modern AI technology excels at dynamic intent recognition. By analyzing consumer data points in real time, the system can use this information to shift its approach in real time. For an omnichannel strategy, this equates to AI optimizing interactions based on data unique to interaction with a specific consumer, in contrast to the traditional a one-size-fits-all approach. While human agents are needed for more complex cases, AI can be effectively leveraged to take care of low-risk interactions and repetitive tasks.
Pillar 3 – Transparency in AI to Consumer Interactions
Now it’s time for AI systems to interact directly with consumers, and it’s essential for the digital handshake between them to go off without a hitch. First, responsible AI begins with disclosing to the customer that they’re talking to AI. By starting off with honesty, your business will build baseline trust and lower the risk of customers being caught off guard and ending the conversation.
In debt-related conversations with businesses, consumers can have an undertone of shame, anxiety or even embarrassment. In these situations, many consumers may prefer interacting with AI since it strips away the emotional friction of human judgement. It often makes it easier for the consumer to calmly explore their options for repayment, smoothing out the debt collection process.
AI systems can also monitor positive and negative keywords, which is beneficial in each scenario. If a negative keyword is mentioned by a consumer, or the AI picks up on escalating frustration, it can be trained to hand off the conversation to a human agent. Conversely, AI can match a consumer’s positivity and guide them more effectively to self-service solutions.
Pillar 4 – AI Post-Performance Review
The final and most crucial pillar of an AI tool’s communication with consumers is a performance review to foster continuous improvement and human-in-the-loop governance. Similar to a car, AI models experience performance drift as real-world consumer behavior shifts, requiring continuous calibration to keep outputs accurate. By running continuous testing on AI models, your business reduces the risk of errors or hallucinations occurring during customer interactions.
It’s important for businesses to treat AI systems the same way as a human agent. This means working to create the following:
- Human-in-the-Loop Accountability: Assign clear owners who will audit AI transcripts and decisions made for consumers.
- Reinforced Learning: Take time to steer the AI system through feedback loops, mark optimal outcomes and manually correct missed opportunities.
Stop Lever: Have a definitive “stop button” mechanism so if a system mistake is detected, supervisors have the ability to process immediately.
A Consumer-Friendly Experience for High Performance Recovery
TrueAccord is the premier omnichannel debt collection agency that leverages data science and AI technology to deliver a consumer-centric experience. With full-lifecycle recovery solutions, our team gets rid of any guesswork to find consumers a way forward. Contact our team to learn more about our first and third party services.