AI

Flipping the Switch: Getting Started in AI

Learn how to get started with AI in credit and collections. Assess your processes, define goals, and choose the right tools to boost efficiency and success.


Back in 1891, the White House had electric lighting installed. It was a massive project that also included wiring the State, Navy, and War building next door to the White House. Wires were buried into the plaster, and switches were installed in each room to turn the lights on and off. President Benjamin Harrison, and his wife, First Lady Caroline Harrison, were so afraid of being shocked if they touched the switches that they both refused to do so. They had the staff around the building turn the lights on and off for them. 

That is a fascinating little story in and of itself, but there is a parallel in today’s world of credit and collections. Companies that refuse to embrace technology are being left in the dark. All it takes is the courage to flip one switch and your world will be forever brighter because of it. 

But identifying that first switch to flip when it comes to artificial intelligence is not that easy. Vendors of all shapes and sizes are touting their use of artificial intelligence in some way, shape, or form. For professionals in the credit and collection industry, though, the decision to integrate AI into your office can be daunting. Where should you start? How do you decide where to use it first? 

Step 1: Assess Your Current Processes

The first step in deploying AI is to conduct a comprehensive assessment of your current processes. You can’t figure out how to get somewhere if you don’t know where you are right now. Identify areas where inefficiencies exist and where AI may be able to add the most value. Common areas to consider include:

  • Customer Service: AI chatbots and virtual assistants can handle routine queries normally handled by a collector. 
  • Payment Reminders: Automate the sending of payment reminders based on consumer behavior.
  • Data Analysis: Use predictive analytics to prioritize accounts and predict payment probabilities.

Step 2: Define Your Goals

Clearly define what you hope to achieve by deploying an AI-driven solution. Whether it’s increasing recovery rates, reducing operational costs, or improving customer satisfaction, having specific goals will guide your implementation strategy.

Step 3: Start Small with Pilot Projects

Deploying AI doesn’t have to be an all-or-nothing approach. Start small with pilot projects in areas where you expect the highest impact. 

Step 4: Choose the Right AI Tools

Selecting the right AI tools is crucial for success. Look for solutions that are specifically designed for the credit and collection industry. There are plenty of them out there today. These tools should integrate seamlessly with your existing tech stacks. Some key features to look for include:

  • Natural Language Processing (NLP): For understanding and responding to debtor inquiries.
  • Machine Learning Algorithms: For predictive analytics and prioritizing accounts.
  • Robotic Process Automation (RPA): For automating repetitive tasks.

Step 5: Invest in Training 

The successful deployment of AI requires more than just technology; it requires people who understand how to use it. Invest in training programs for your team to ensure they are comfortable and proficient with AI tools. 

Step 6: Monitor, Evaluate, and Adjust

Once AI is deployed, continuously monitor its performance. Collect data on key metrics such as recovery rates, customer satisfaction, and operational efficiency. Use this data to evaluate the effectiveness of your AI implementation and make necessary adjustments. 

All of this may seem overwhelming, and in a lot of ways, it may be. But imagine yourself, standing next to a light switch, too afraid to turn it on. How does the story end for that individual? Do you imagine that he or she survives? Or are they left behind, in the dark, wondering “what if” and worried about something that will never happen. 

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