Technology & Innovation
Exploring cutting-edge tools and emerging tech trends that transform how the debt collection and financial services industries operate, from automation to AI-driven analytics.
Abstract: Artificial intelligence and machine learning are fundamentally changing the way debt collection organizations interact with consumers. What was once
Abstract: In 2026, digital collections performance depends less on adding channels and more on orchestrating them with measurable, compliance-engineered
Abstract: Artificial intelligence is reshaping receivables management, but not in the way many expected. Rather than replacing human roles,
Self-service payments are no longer a peripheral feature in debt collection; they are the new norm across the entire
Artificial intelligence has moved rapidly from experimentation to expectation across receivables operations. Collection agencies, debt buyers, and creditors increasingly
The U.S. receivables industry continues to operate on infrastructure and behavioral assumptions developed decades ago. Many of these no
AI context orchestration for collections is increasingly recognized as a structural requirement rather than a technical enhancement. As artificial
Digital settlement platforms are often discussed as if they are a simple channel change, moving a negotiation from phone
Artificial intelligence is now a permanent component of debt collection operations. While early adoption focused on experimentation and proof-of-concept
The deployment of conversational AI in collections has progressed beyond experimentation. AI voice systems are now interacting with consumers,
Artificial intelligence has moved rapidly from experimentation to expectation across receivables operations. Collection agencies, debt buyers, and creditors increasingly
The U.S. receivables industry continues to operate on infrastructure and behavioral assumptions developed decades ago. Many of these no
AI context orchestration for collections is increasingly recognized as a structural requirement rather than a technical enhancement. As artificial
Digital settlement platforms are often discussed as if they are a simple channel change, moving a negotiation from phone
Artificial intelligence is now a permanent component of debt collection operations. While early adoption focused on experimentation and proof-of-concept
The deployment of conversational AI in collections has progressed beyond experimentation. AI voice systems are now interacting with consumers,
The challenge of responding to security threats has expanded far beyond the confines of information technology departments. Across regulated
Artificial intelligence in debt collection has evolved from experimental to operational. It is no longer a future ambition and
The receivables industry is entering a critical 18-month window where AI adoption will shape operations for years to come.
The adoption of AI in receivables has accelerated, but vendor selection remains a high-stakes decision. This article outlines a compliance-first
Abstract Evaluating digital consumer journeys is about far more than user experience design. In this article, I share why
By Adam Parks Millennials and Gen Z are changing the rules for debt collection. These digital-native generations have grown
By Michael Walsh, EXL Holdings AbstractAs artificial intelligence reshapes the debt collection landscape, operationalizing AI in a compliant, scalable, and effective
Abstract The evolution of AI in business has brought remarkable efficiencies—but it has also introduced new complexities around accuracy,
Submit a Press Release
Submit your press release editorial consideration. We welcome articles highlighting trends, innovations, and updates in the collections industry.
Latest News
- Bessent Could Add AI Czar Role to Treasury Duties; Formerly Led CFPB
- Maryland Federal Court Denies TCPA Class Certification in ExamWorks Prerecorded Call Case
- Understanding the Digital Payment Journey in Debt Collection
- Supreme Court to Resolve VPPA Split Over Who Qualifies as a “Consumer”
- South Korea Adds Debt and Lending Risks to Welfare Detection System