C&R Software presents Collecting Thoughts. A podcast featuring conversations with industry experts and insiders throughout the finance, software, and collections industries.
On this week’s episode, Christina is joined by Chris Hopkins, Director of Product Management at C&R Software. Chris gives us a fascinating rundown on the key technologies affecting the debt recovery industry and how companies can implement them to benefit staff and customers.
Name: Chris Hopkins
Profession: Senior Director of Product Management, C&R Software
With decades of experience in product management, Chris brings expertise in leveraging cutting-edge technological solutions to improve customer experience and organizational efficiency in collections and recovery.
A graduate of Cambridge University, Chris joined the C&R Software team in 2021 after nine years as Director of Product Management at FICO—an organization known for its leading role in analytics and credit scoring.
Find Chris on LinkedIn
Chris speaks about a recent change in mindset for collections companies, in which a focus on a human-first approach has come to the forefront. While many debt and recovery organizations aren’t often seen as progressive, many are coming to terms with the idea that customers in hardship are simply at a temporary point in the overall customer journey.
“If I think of my time in collections and recoveries, for the majority of that time, a customer who owed money wasn’t a customer—we called them a debtor. We’d categorize debtors. ‘Oh, no, you’re a debtor…Are you a can’t pay? Or are you a won’t pay?’”
Until only a few years ago, this kind of attitude was the norm, according to Chris. But nowadays, customer-centric creditors provide capabilities to help the consumer, benefiting both parties.
Making data-driven decisions
When it comes to decision-making in business—not only in the collection sphere—making informed decisions is paramount to success. For Chris, that means implementing data analytics and empowering the right people to act on the information.
For those in management of companies that don’t currently employ much or any data analytics, Chris says the obstacle isn’t necessarily a lack of willingness—many don’t know where to start and worry that it’s too great an undertaking.
“I was talking to…an expert in this field, and his advice was to try to identify small steps you can take so it’s easy to implement models. Don’t try to solve everything at once. Identify applications where [data-]enhanced decisions would really help the business.”
With the right approach, using analytics to inform a decision-making process that positively impacts both the business and the customer is highly feasible.
A key technology Chris recommends collections companies implement right away is customer service chatbots. While common in retail sites, banks, and organizations, they’re not so common in debt recovery businesses.
“If the consumer trusts the chatbot, then they’ll be able to resolve [their issue] without calling in. And that means that there’ll be more room for people who have a very specific problem that chatbots might not necessarily be able to help with, and that way, that problem can be resolved. The business runs smoothly, and all is fine.”
Chris referenced a company he’s familiar with whose number of calls to the customer service center dropped by 25% after implementing chatbots. Not only does that mean the chatbot is resolving customer issues, but it’s also supporting call center employees by reducing their administrative burden.
“The employee’s job is kind of being enriched in a way because, rather than dealing with the more mundane things like taking a payment from the customer or setting up a simple payment arrangement, they are engaged in truly helping consumers.”
We asked Chris to give us one final example of a piece of technology that could positively affect an organization in the debt collection industry. He recommended audio analytics and used the example of deploying it to create efficiencies in customer service.
“There is another aspect of audio analytics, which is sentiment analysis. Sentiment analysis is basically looking at emotionally charged words [It can] provide warning information like a virtual assistant on the agents’ screens that says this customer is potentially vulnerable, and that’s going to help the agent in how they converse with that customer.”
Besides sentiment analysis, audio analytics are great for training purposes, in which, for example, the agent’s calls deviate from an ideal script.
To discover more topics like Chris’ work with cutting-edge tech in collections, visit the C&R Software blog.
Stay tuned for future episodes of Collecting Thoughts, where host Christina interviews experts and thinkers across the finance and software industries.