Welcome to Credit Shift, the podcast that dives into the challenges and opportunities, tools, and strategies shaping the world of credit, digital debt collection, and digital transformation. Brought to you by Aryza.com, Credit Shift explores key industry trends and innovations, featuring insights from Aryza experts and industry leaders. Whether you're navigating AI in credit and collections, customer engagement strategies, or the future of digital debt collection, this podcast is your go-to resource for staying ahead.
From SMS to Rich Conversations: Exploring RBM in Debt Collection
In this episode of Credit Shift, Mark Oppermann and Graham Bragg dive into the move from traditional SMS to Rich Business Messaging (RBM) — and why it’s a big deal for debt collection and business communication.
They chat about how messaging has evolved, what makes RBM stand out, and why branding and trust matter more than ever in customer conversations. From richer content and better engagement to improved security and cost-effectiveness, this episode breaks down the real-world impact of RBM and why it's something every business should be thinking about.
Whether you’re in collections, customer service, or just trying to stay ahead of the messaging curve, this one’s worth a listen.
Key Takeaways
The shift from SMS to RBM represents a significant evolution in messaging.
RBM allows for richer content and branding in business communications.
Every modern smartphone supports RBM, making it widely accessible.
RBM messages can include company branding, enhancing trust and recognition.
Higher engagement rates are observed with branded messages compared to unbranded ones.
RBM provides read receipts, offering insights into message engagement.
The cost of RBM is comparable to SMS, making it a cost-effective solution.
Security is enhanced with RBM, as messages are end-to-end encrypted.
The adoption of RBM is expected to grow rapidly in the coming years.
Businesses can leverage RBM for various applications beyond debt collection.
Keywords
Credit Shift, SMS, RBM, Rich Business Messaging, Digital Transformation, Debt Collection, Communication Strategies, Customer Engagement, Branding, Security
11 Mar 2025
The Overlooked Potential of SMS in Debt Collection
In this episode of Credit Shift, Mark Oppermann and Graham Bragg chat about the often overlooked power of SMS in digital debt collection and customer engagement. While it might be one of the older technologies in the mix, SMS still has loads to offer – and many businesses aren't using it to its full potential.
They dig into how personalisation, automation, and AI can take SMS beyond the basics, helping businesses create smarter, more effective conversations. There’s also a reminder that compliance is key when it comes to messaging strategies.
With its broad reach and low costs, SMS remains a seriously effective tool, especially for the debt collection industry. Mark and Graham wrap up by sharing what’s next for SMS, including rich business messaging and other exciting updates on the horizon.
Key Takeaways
SMS is still one of the most underused channels for customer engagement.
Younger generations? They’d much rather get a message than answer a phone call.
Adding a personal touch to your SMS can make a big difference in how people respond.
Automation helps keep those conversations flowing smoothly without adding extra work.
AI can take SMS to the next level—making it smarter and keeping things compliant.
It’s affordable, easy to use, and works on pretty much any mobile phone.
People aren’t as fed up with SMS as they once were—message fatigue has really eased off.
Hooking SMS up to your backend systems makes for a much smoother customer journey.
Real-time messaging means customers get what they need, right when they need it.
And looking ahead? Rich business messaging is set to make SMS even more powerful.
19 Feb 2025
Choosing the Right AI for Debt Collections: Custom Language Models vs. Large Language Models
In this episode of Credit Shift, we dive into the world of AI in debt collection. They break down the key differences between custom language models and large language models, tackling the big question—why does it matter?
The conversation gets into the challenges of using AI in regulated industries, the importance of truly understanding customer intent, and where AI is headed in customer interactions.
We also chat about why one-size-fits-all AI doesn’t cut it in debt collection and how tailored solutions can boost efficiency and compliance.
Key Takeaways:
Custom language models are built for specific industries, making them more accurate and reliable.
Large language models can sometimes miss the mark, generating irrelevant or incorrect responses.
AI improves customer interactions by recognizing intent and understanding context.
Industry-specific training is essential to ensure AI provides meaningful and compliant responses.
AI hallucinations can be risky, especially in finance, where accuracy is critical.
Recognsing customer vulnerabilities is key to ethical and effective debt collection.
AI isn’t a magic fix—it’s a tool that needs the right setup and oversight.
The future of AI includes smarter features like conversational summaries and co-pilot assistance.
Tailored AI models can dramatically cut down failed conversations in debt collection.
Keywords
AI, debt collection, custom language models, large language models, digital transformation, finance, generative AI, digital debt collection, NLP, compliance
Watch On YouTube
https://youtu.be/rqjK9lhXFSM
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